From 3654de1f7b0bd033149d6a743e557ce4f3e6a4f7 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 19 Dec 2025 15:22:21 -0500 Subject: [PATCH 01/31] Make plot functions much more terse by passing kwargs and fetching a couple defaults --- lyopronto/plot_styling.py | 136 ++++++++------------------------------ 1 file changed, 27 insertions(+), 109 deletions(-) diff --git a/lyopronto/plot_styling.py b/lyopronto/plot_styling.py index 0df05fa..45f2f52 100644 --- a/lyopronto/plot_styling.py +++ b/lyopronto/plot_styling.py @@ -34,134 +34,52 @@ def axis_tick_styling( ax.xaxis.labelpad = labelPad ax.yaxis.labelpad = labelPad -def axis_style_pressure( - ax, - gcafontSize = 60, - labelPad = 30, - color = 'b', - majorTickWidth = 5, - minorTickWidth = 3, - majorTickLength = 30, - minorTickLength = 20, - ): +def axis_style_pressure(ax, **kwargs): """ Function to set styling for axes, with time on x and pressure on y """ - + color = kwargs.get('color','b') + gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") ax.set_ylabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") - - axis_tick_styling( - ax, - color = color, - gcafontSize = gcafontSize, - majorTickWidth = majorTickWidth, - minorTickWidth = minorTickWidth, - majorTickLength = majorTickLength, - minorTickLength = minorTickLength, - labelPad = labelPad, - ) + axis_tick_styling(ax, **kwargs) -def axis_style_subflux( - ax, - gcafontSize = 60, - labelPad = 30, - color = [0, 0.7, 0.3], - majorTickWidth = 5, - minorTickWidth = 3, - majorTickLength = 30, - minorTickLength = 20, - ): +def axis_style_subflux(ax, **kwargs): """ Function to set styling for axes, with time on x and sublimation flux on y """ - + color = kwargs.get('color',[0, 0.7, 0.3]) + gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + axis_tick_styling(ax, **kwargs) - axis_tick_styling( - ax, - color = color, - gcafontSize = gcafontSize, - majorTickWidth = majorTickWidth, - minorTickWidth = minorTickWidth, - majorTickLength = majorTickLength, - minorTickLength = minorTickLength, - labelPad = labelPad, - ) - -def axis_style_percdried( - ax, - gcafontSize = 60, - labelPad = 30, - color = 'k', - majorTickWidth = 5, - minorTickWidth = 3, - majorTickLength = 30, - minorTickLength = 20, - ): +def axis_style_percdried( ax, **kwargs): """ Function to set styling for axes, with time on x and percent dried on y """ - + color = kwargs.get('color','k') + gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") ax.set_ylabel("Percent Dried",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + axis_tick_styling(ax, **kwargs) - axis_tick_styling( - ax, - color = color, - gcafontSize = gcafontSize, - majorTickWidth = majorTickWidth, - minorTickWidth = minorTickWidth, - majorTickLength = majorTickLength, - minorTickLength = minorTickLength, - labelPad = labelPad, - ) - -def axis_style_temperature( - ax, - gcafontSize = 60, - labelPad = 30, - color = 'k', - majorTickWidth = 5, - minorTickWidth = 3, - majorTickLength = 30, - minorTickLength = 20, - ): +def axis_style_temperature(ax, **kwargs): """ Function to set styling for axes, with time on x and temperature on y """ - + color = kwargs.get('color','k') + gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") ax.set_ylabel("Product Temperature [°C]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + axis_tick_styling(ax, **kwargs) - axis_tick_styling( - ax, - color = color, - gcafontSize = gcafontSize, - majorTickWidth = majorTickWidth, - minorTickWidth = minorTickWidth, - majorTickLength = majorTickLength, - minorTickLength = minorTickLength, - labelPad = labelPad, - ) +def axis_style_designspace(ax,**kwargs): + """ Function to set styling for axes, with time on x and sublimation flux on y """ + color = kwargs.get('color', [0, 0.7, 0.3]) + gcafontSize = kwargs.get('gcafontSize',60) + ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + axis_tick_styling(ax, **kwargs) -def axis_style_rp( - ax, - gcafontSize = 60, - labelPad = 30, - color = 'k', - majorTickWidth = 5, - minorTickWidth = 3, - majorTickLength = 30, - minorTickLength = 20, - ): +def axis_style_rp(ax, **kwargs): """ Function to set styling for axes, with dry layer height on x and product resistance on y """ - + color = kwargs.get('color','k') + gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Dry Layer Height [cm]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") ax.set_ylabel('Product Resistance [cm$^2$ hr Torr/g]',fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") - - axis_tick_styling( - ax, - color = color, - gcafontSize = gcafontSize, - majorTickWidth = majorTickWidth, - minorTickWidth = minorTickWidth, - majorTickLength = majorTickLength, - minorTickLength = minorTickLength, - labelPad = labelPad, - ) + axis_tick_styling(ax, **kwargs) From 7ed86c167cefe395189f6ebc67d471f055979da2 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 19 Dec 2025 15:54:37 -0500 Subject: [PATCH 02/31] Further plot recipe cleanup, add two more --- lyopronto/plot_styling.py | 47 ++++++++++++++++++++++++++------------- 1 file changed, 32 insertions(+), 15 deletions(-) diff --git a/lyopronto/plot_styling.py b/lyopronto/plot_styling.py index 45f2f52..7b229ac 100644 --- a/lyopronto/plot_styling.py +++ b/lyopronto/plot_styling.py @@ -13,6 +13,10 @@ # You should have received a copy of the GNU General Public License # along with this program. If not, see . + +default_font_spec = {"fontweight":"bold", "font_family":"Arial"} + +# TODO: document these kwargs def axis_tick_styling( ax, color = 'k', @@ -27,7 +31,7 @@ def axis_tick_styling( ax.minorticks_on() ax.tick_params(axis='both',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) ax.tick_params(axis='both',which='minor',direction='in',width=minorTickWidth,length=minorTickLength) - ax.tick_params(axis='both',labelsize=gcafontSize,labelfontfamily='Arial') + ax.tick_params(axis='both',labelsize=gcafontSize,labelfontfamily=default_font_spec['font_family']) ax.tick_params(axis='y',which='both',color=color, labelcolor=color) for tick in [*ax.get_xticklabels(), *ax.get_yticklabels()]: tick.set_fontweight('bold') @@ -38,48 +42,61 @@ def axis_style_pressure(ax, **kwargs): """ Function to set styling for axes, with time on x and pressure on y """ color = kwargs.get('color','b') gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") - ax.set_ylabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_subflux(ax, **kwargs): """ Function to set styling for axes, with time on x and sublimation flux on y """ color = kwargs.get('color',[0, 0.7, 0.3]) gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") - ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_percdried( ax, **kwargs): """ Function to set styling for axes, with time on x and percent dried on y """ color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") - ax.set_ylabel("Percent Dried",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel("Percent Dried",fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_temperature(ax, **kwargs): """ Function to set styling for axes, with time on x and temperature on y """ color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") - ax.set_ylabel("Product Temperature [°C]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel("Product Temperature [°C]",fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_designspace(ax,**kwargs): - """ Function to set styling for axes, with time on x and sublimation flux on y """ - color = kwargs.get('color', [0, 0.7, 0.3]) + """ Function to set styling for axes, with pressure on x and sublimation flux on y """ + gcafontSize = kwargs.get('gcafontSize',60) + ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,**default_font_spec) + axis_tick_styling(ax, **kwargs) + +def axis_style_ds_percdried(ax,**kwargs): + """ Function to set styling for axes, with chamber pressure on x and fraction dried on y """ + gcafontSize = kwargs.get('gcafontSize',60) + ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel("Fraction Dried",fontsize=gcafontSize,**default_font_spec) + axis_tick_styling(ax, **kwargs) + +def axis_style_ds_temperature(ax,**kwargs): + """ Function to set styling for axes, with chamber pressure on x and product temperature on y """ gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") - ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel("Product Temperature [°C]",fontsize=gcafontSize,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_rp(ax, **kwargs): """ Function to set styling for axes, with dry layer height on x and product resistance on y """ color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Dry Layer Height [cm]",fontsize=gcafontSize,fontweight='bold',fontname="Arial") - ax.set_ylabel('Product Resistance [cm$^2$ hr Torr/g]',fontsize=gcafontSize,color=color,fontweight='bold',fontname="Arial") + ax.set_xlabel("Dry Layer Height [cm]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel('Product Resistance [cm$^2$ hr Torr/g]',fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) From c8c0037844a063e60f4f34dedfdd11439ae66ce1 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 19 Dec 2025 15:56:03 -0500 Subject: [PATCH 03/31] Refactor the main script to call functions defined in lyopronto package --- lyopronto/__init__.py | 454 ++++++++++++++++++++++++++++++++++++++- main.py | 484 ++++-------------------------------------- 2 files changed, 489 insertions(+), 449 deletions(-) diff --git a/lyopronto/__init__.py b/lyopronto/__init__.py index 5a4e6ad..5c23963 100644 --- a/lyopronto/__init__.py +++ b/lyopronto/__init__.py @@ -14,6 +14,9 @@ # You should have received a copy of the GNU General Public License # along with this program. If not, see . +# ---------------------- +# Import submodules + from . import constant from . import freezing from . import calc_knownRp @@ -23,4 +26,453 @@ from . import opt_Pch from . import opt_Tsh from . import functions -from . import plot_styling \ No newline at end of file +from . import plot_styling + +# ---------------------- +# Provide functionality for running LyoPRONTO as a module +import numpy as np +import csv +import matplotlib.pyplot as plt +from matplotlib import rc as matplotlibrc +import scipy.optimize as sp + +def execute_simulation(config): + """ + Run the selected simulation tool with the provided configuration. + Returns output data based on the chosen simulation mode. + """ + sim_type = config['sim']['tool'] + output_data = None + + if sim_type == 'Freezing Calculator': + output_data = freezing.freeze( + config['vial'], + config['product'], + config['h_freezing'], + config['Tshelf'], + config['dt'] + ) + + elif sim_type == 'Primary Drying Calculator': + if config['sim']['Kv_known'] and config['sim']['Rp_known']: + output_data = calc_knownRp.dry( + config['vial'], + config['product'], + config['ht'], + config['Pchamber'], + config['Tshelf'], + config['dt'] + ) + elif not config['sim']['Kv_known'] and config['sim']['Rp_known']: + output_data = _optimize_kv_parameter(config) + elif config['sim']['Kv_known'] and not config['sim']['Rp_known']: + output_data = _optimize_rp_parameter(config) + else: + raise ValueError("With the current implementation, either Kv or Rp must be specified.") + + elif sim_type == 'Design-Space-Generator': + output_data = design_space.dry( + config['vial'], + config['product'], + config['ht'], + config['Pchamber'], + config['Tshelf'], + config['dt'], + config['eq_cap'], + config['nVial'] + ) + + elif sim_type == 'Optimizer': + output_data = _run_optimizer(config) + + return output_data + +# TODO: bisection search, rather than iteration over a range? +def _optimize_kv_parameter(config): + """Helper to determine Kv based on experimental drying time.""" + Kv_range = config['Kv_range'] + best_Kv = Kv_range[0] + min_deviation = float('inf') + best_output = None + + for Kc in Kv_range: + output = calc_knownRp.dry( + config['vial'], + config['product'], + {'KC': Kc, 'KP': 0.0, 'KD': 0.0}, + config['Pchamber'], + config['Tshelf'], + config['dt'] + ) + simulated_time = output[-1, 0] + deviation = abs(config['t_dry_exp'] - simulated_time) / config['t_dry_exp'] * 100 + + if deviation < min_deviation: + min_deviation = deviation + best_Kv = Kc + best_output = output + + print(f"Optimal Kv: {best_Kv}, Deviation: {min_deviation}%") + return best_output + + +def _optimize_rp_parameter(config): + """Helper to determine Rp from experimental product temperature.""" + + exp_data = np.loadtxt(config['product_temp_file']) + time_data = exp_data[:, 0] + temp_data = exp_data[:, 1] + + output, product_res = calc_unknownRp.dry( + config['vial'], + config['product'], + config['ht'], + config['Pchamber'], + config['Tshelf'], + time_data, + temp_data + ) + + params, _ = sp.curve_fit( + functions.Rp_FUN, + product_res[:, 1], + product_res[:, 2], + p0=[1.0, 0.0, 0.0] + ) + + print(f"R0: {params[0]}, A1: {params[1]}, A2: {params[2]}") + return output + + +def _run_optimizer(config): + """Helper to run optimization with variable parameters.""" + args = ( config['vial'], config['product'], config['ht'], + config['Pchamber'], config['Tshelf'], config['dt'], + config['eq_cap'], config['nVial']) + if config['sim']['Variable_Pch'] and config['sim']['Variable_Tsh']: + return opt_Pch_Tsh.dry(*args) + elif config['sim']['Variable_Pch']: + return opt_Pch.dry(*args) + elif config['sim']['Variable_Tsh']: + return opt_Tsh.dry(*args) + + +def save_configuration_legacy(config, timestamp): + """ + Persist configuration parameters to a CSV file with timestamped filename. + """ + filename = f'lyopronto_input_{timestamp}.csv' + sim = config['sim'] + vial = config['vial'] + product = config['product'] + + with open(filename, 'w', newline='') as csvfile: + writer = csv.writer(csvfile) + + writer.writerow(['Simulation Tool', sim['tool']]) + writer.writerow(['Kv Known', sim['Kv_known']]) + writer.writerow(['Rp Known', sim['Rp_known']]) + writer.writerow(['Variable Chamber Pressure', sim['Variable_Pch']]) + writer.writerow(['Variable Shelf Temperature', sim['Variable_Tsh']]) + writer.writerow([]) + + writer.writerow(['Vial Cross-Section [cm²]', vial['Av']]) + writer.writerow(['Product Area [cm²]', vial['Ap']]) + writer.writerow(['Fill Volume [mL]', vial['Vfill']]) + writer.writerow([]) + + writer.writerow(['Fractional solute concentration:',product['cSolid']]) + if sim['tool'] == 'Freezing Calculator': + writer.writerow(['Intial product temperature [C]:',product['Tpr0']]) + writer.writerow(['Freezing temperature [C]:',product['Tf']]) + writer.writerow(['Nucleation temperature [C]:',product['Tn']]) + elif not(sim['tool'] == 'Primary Drying Calculator' and sim['Rp_known'] == 'N'): + writer.writerow(['R0 [cm^2-hr-Torr/g]:',product['R0']]) + writer.writerow(['A1 [cm-hr-Torr/g]:',product['A1']]) + writer.writerow(['A2 [1/cm]:',product['A2']]) + if not(sim['tool'] == 'Freezing Calculator' and sim['tool'] == 'Primary Drying Calculator'): + writer.writerow(['Critical product temperature [C]:', product['T_pr_crit']]) + + if sim['tool'] == 'Freezing Calculator': + writer.writerow(['h_freezing [W/m^2/K]:',config['h_freezing']]) + elif sim['Kv_known']: + writer.writerow(['KC [cal/s/K/cm^2]:',config['ht']['KC']]) + writer.writerow(['KP [cal/s/K/cm^2/Torr]:',config['ht']['KP']]) + writer.writerow(['KD [1/Torr]:',config['ht']['KD']]) + elif not sim['Kv_known']: + writer.writerow(['Kv range [cal/s/K/cm^2]:',config['Kv_range'][:]]) + writer.writerow(['Experimental drying time [hr]:',config['t_dry_exp']]) + + + if sim['tool'] == 'Freezing Calculator': + 0 + elif sim['tool'] == 'Design-Space-Generator': + writer.writerow(['Chamber pressure set points [Torr]:',config['Pchamber']['setpt'][:]]) + elif not(sim['tool'] == 'Optimizer' and sim['Variable_Pch'] == 'Y'): + for i in range(len(config['Pchamber']['setpt'])): + writer.writerow(['Chamber pressure setpoint [Torr]:',config['Pchamber']['setpt'][i],'Duration [min]:',config['Pchamber']['dt_setpt'][i]]) + writer.writerow(['Chamber pressure ramping rate [Torr/min]:',config['Pchamber']['ramp_rate']]) + else: + writer.writerow(['Minimum chamber pressure [Torr]:',config['Pchamber']['min']]) + writer.writerow(['Maximum chamber pressure [Torr]:',config['Pchamber']['max']]) + writer.writerow(['']) + + if sim['tool'] == 'Design-Space-Generator': + writer.writerow(['Intial shelf temperature [C]:',config['Tshelf']['init']]) + writer.writerow(['Shelf temperature set points [C]:',config['Tshelf']['setpt'][:]]) + writer.writerow(['Shelf temperature ramping rate [C/min]:',config['Tshelf']['ramp_rate']]) + elif not(sim['tool'] == 'Optimizer' and sim['Variable_Tsh'] == 'Y'): + for i in range(len(config['Tshelf']['setpt'])): + writer.writerow(['Shelf temperature setpoint [C]:',config['Tshelf']['setpt'][i],'Duration [min]:',config['Tshelf']['dt_setpt'][i]]) + writer.writerow(['Shelf temperature ramping rate [C/min]:',config['Tshelf']['ramp_rate']]) + else: + writer.writerow(['Minimum shelf temperature [C]:',config['Tshelf']['min']]) + writer.writerow(['Maximum shelf temperature [C]:',config['Tshelf']['max']]) + + writer.writerow(['Time Step [hr]', config['dt']]) + writer.writerow(['Equipment Parameter a [kg/hr]', config['eq_cap']['a']]) + writer.writerow(['Equipment Parameter b [kg/hr/Torr]', config['eq_cap']['b']]) + writer.writerow(['Number of Vials', config['nVial']]) + +def save_csv(output_data, config, timestamp): + """ + Export simulation results to CSV file with appropriate formatting. + """ + filename = f'lyopronto_output_{timestamp}.csv' + + sim = config['sim'] + + + if sim['tool'] == 'Freezing Calculator': + assert output_data.shape[1] == 3 + header = "Time [hr], Shelf Temp [°C], Product Temp [°C]" + np.savetxt(filename, output_data, delimiter=', ', header=header) + elif sim['tool'] == 'Design-Space-Generator': + assert output_data.shape[1] == 6 + header = "Chamber Pressure [mTorr], Max Product Temperature [°C], Drying Time [hr], Avg Sublimation Flux [kg/hr/m²], Max/Min Sublimation Flux [kg/hr/m²], Final Sublimation Flux [kg/hr/m²]" + ds_shelf, ds_pr, ds_eq_cap = output_data + Tshelf = config['Tshelf'] + Pchamber = config['Pchamber'] + + # TODO: This CSV has a weird format. Consider revising, or at least redoing as a few tables. + try: + csvfile = open(filename, 'w') + writer = csv.writer(csvfile) + writer.writerow(['Chamber Pressure [mTorr]','Maximum Product Temperature [C]','Drying Time [hr]','Average Sublimation Flux [kg/hr/m^2]','Maximum/Minimum Sublimation Flux [kg/hr/m^2]','Final Sublimation Flux [kg/hr/m^2]']) + for i in range(np.size(Tshelf['setpt'])): + writer.writerow(['Shelf Temperature = ',str(Tshelf['setpt'][i])]) + for j in range(np.size(Pchamber['setpt'])): + writer.writerow([Pchamber['setpt'][j]*constant.Torr_to_mTorr,ds_shelf[0,i,j],ds_shelf[1,i,j],ds_shelf[2,i,j],ds_shelf[3,i,j],ds_shelf[4,i,j]]) + writer.writerow(['Product Temperature = ',str(config['product']['T_pr_crit'])]) + writer.writerow([Pchamber['setpt'][0]*constant.Torr_to_mTorr,ds_pr[0,0],ds_pr[1,0],ds_pr[2,0],ds_pr[3,0],ds_pr[4,0]]) + writer.writerow([Pchamber['setpt'][-1]*constant.Torr_to_mTorr,ds_pr[0,1],ds_pr[1,1],ds_pr[2,1],ds_pr[3,1],ds_pr[4,1]]) + writer.writerow(['Equipment Capability']) + for k in range(np.size(Pchamber['setpt'])): + writer.writerow([Pchamber['setpt'][k]*constant.Torr_to_mTorr,ds_eq_cap[0,k],ds_eq_cap[1,k],ds_eq_cap[2,k],ds_eq_cap[2,k],ds_eq_cap[2,k]]) + finally: + csvfile.close() + + else: + header =",".join([ + 'Time [hr]', + 'Sublimation Front Temp [°C]', + 'Vial Bottom Temperature [°C]', + 'Shelf Temp [°C]', + 'Chamber Pressure [mTorr]', + 'Sublimation Flux [kg/hr/m²]', + 'Percent Dried' + ]) + np.savetxt(filename, output_data, delimiter=', ', header=header) + +#TODO: add more kwargs, proper documentation, possibly refactor to make +# each subfunction part of the API +def generate_visualizations(output_data, config, timestamp): + """ + Create and save publication-quality plots based on simulation results. + """ + #TODO: move these to kwargs for the function + figure_props = { + 'figwidth': 30, + 'figheight': 20, + 'linewidth': 5, + 'marker_size': 20, + } + matplotlibrc('text.latex', preamble=r'\usepackage{color}') + matplotlibrc('text',usetex=False) + plt.rcParams['font.family'] = 'Arial' + + if config['sim']['tool'] == 'Freezing Calculator': + _plot_freezing_results(output_data, figure_props, timestamp) + elif config['sim']['tool'] in ['Primary Drying Calculator', 'Optimizer']: + _plot_drying_results(output_data, figure_props, timestamp) + elif config['sim']['tool'] == 'Design-Space-Generator': + _plot_design_space(output_data, config, figure_props, timestamp) + + +def _plot_freezing_results(data, props, timestamp): + """Generate freezing process visualization.""" + fig, ax = plt.subplots(figsize=(props['figwidth'], props['figheight'])) + ax.plot(data[:, 0], data[:, 1], '-k', linewidth=props['linewidth'], label='Shelf Temperature') + ax.plot(data[:, 0], data[:, 2], '-b', linewidth=props['linewidth'], label='Product Temperature') + ax.set_xlabel('Time [hr]', fontsize=props['axis_fontsize'], fontweight='bold') + ax.set_ylabel('Temperature [°C]', fontsize=props['axis_fontsize'], fontweight='bold') + ax.legend(prop={'size': 40}) + plt.tight_layout() + plt.savefig(f'Temperatures_{timestamp}.pdf') + plt.close() + + +def _plot_drying_results(data, props, timestamp): + """Generate primary drying process visualizations.""" + + figwidth = props['figwidth'] + figheight = props['figheight'] + linewidth = props['linewidth'] + marker_size = props['marker_size'] + # Pressure and sublimation flux + fig = plt.figure(0,figsize=(figwidth,figheight)) + ax1 = fig.add_subplot(1,1,1) + ax2 = ax1.twinx() + ax1.plot(data[:,0],data[:,4],'-o',color='b',markevery=5,linewidth=linewidth, markersize=marker_size, label = "Chamber Pressure") + ax2.plot(data[:,0],data[:,5],'-',color=[0,0.7,0.3],linewidth=linewidth, label = "Sublimation Flux") + + plot_styling.axis_style_pressure(ax1) + plot_styling.axis_style_subflux(ax2) + + plt.tight_layout() + plt.savefig(f'lyo_Pressure_SublimationFlux_{timestamp}.pdf') + plt.close() + + # Drying progress + fig = plt.figure(0,figsize=(figwidth,figheight)) + ax = fig.add_subplot(1,1,1) + plot_styling.axis_style_percdried(ax) + ax.plot(data[:,0],data[:,-1],'-k',linewidth=linewidth, label = "Percent Dried") + plt.tight_layout() + plt.savefig(f'lyo_DryingProgress_{timestamp}.pdf') + plt.close() + + # Temperatures + fig = plt.figure(0,figsize=(figwidth,figheight)) + ax = fig.add_subplot(1,1,1) + plot_styling.axis_style_temperature(ax) + ax.plot(data[:,0],data[:,1],'-b',linewidth=linewidth, label = "Sublimation Front Temperature") + ax.plot(data[:,0],data[:,2],'-r',linewidth=linewidth, label = "Maximum Product Temperature") + ax.plot(data[:,0],data[:,3],'-o',color='k',markevery=5,linewidth=linewidth, markersize=marker_size, label = "Shelf Temperature") + plt.legend(fontsize=40,loc='best') + ll,ul = ax.get_ylim() + ax.set_ylim([ll,ul+5.0]) + plt.tight_layout() + plt.savefig(f"lyo_Temperatures_{timestamp}.pdf") + plt.close() + +#TODO: work through this logic and see how much can be refactored out +def _plot_design_space(data, config, props, timestamp): + """Generate design space boundary visualization.""" + # Implementation for design space plotting + + ds_shelf, ds_pr, ds_eq_cap = data + Tshelf = config['Tshelf'] + Pchamber = config['Pchamber'] + figwidth = props['figwidth'] + figheight = props['figheight'] + lineWidth = props['linewidth'] + color_list = ['b','m','g','c','r','y','k'] # Line colors + + # Design space: sublimation flux vs pressures + + x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr + y1 = ((ds_eq_cap[2,-1]-ds_eq_cap[2,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_eq_cap[2,0] # equipment capability sublimation flux in kg/hr/m^2 + y2 = ((ds_pr[3,-1]-ds_pr[3,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_pr[3,0] # product temperature limited sublimation flux in kg/hr/m^2 + x = x*constant.Torr_to_mTorr # pressure range in mTorr + i = np.where(y1>=y2)[0][0] + y = np.append(y1[:i],y2[i:]) + x1 = np.append(x,x[::-1]) + + fig = plt.figure(0,figsize=(figwidth,figheight)) + ax = fig.add_subplot(1,1,1) + plt.axes(ax) + ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_eq_cap[2,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") + ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[3,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(config['product']['T_pr_crit'])+"°C")) + for i in range(np.size(Tshelf['setpt'])): + ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_shelf[3,i,:],'--',color=str(color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) + plot_styling.axis_style_designspace(ax) + plt.legend(prop={'size':40}) + ll,ul = ax.get_ylim() + if np.min(ds_eq_cap[2,:])>np.max(ds_pr[3,:]): + ul = (ds_eq_cap[2,0]+ds_eq_cap[2,1])/3 + elif np.min(ds_pr[3,:])>np.max(ds_eq_cap[2,:]): + ul = (ds_pr[3,0]+ds_pr[3,1])/4 + ax.set_ylim([ll,ul]) + x2 = np.append(y,ll*x/x) + ax.fill(x1,x2,color=[1.,1.,0.6]) + plt.tight_layout() + figure_name = f"lyo_DesignSpace_SublimationFlux_{timestamp}.pdf" + plt.savefig(figure_name) + plt.close() + + # Drying progress vs pressures + + x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr + y1 = ((ds_eq_cap[1,-1]-ds_eq_cap[1,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_eq_cap[1,0] # equipment capability drying time in hr + y2 = ((ds_pr[1,-1]-ds_pr[1,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_pr[1,0] # product temperature limited drying time in hr + x = x*constant.Torr_to_mTorr # pressure range in mTorr + i = np.where(y1np.max(ds_pr[3,:]): + ul = (ds_eq_cap[2,0]+ds_eq_cap[2,1])/3 + elif np.min(ds_pr[3,:])>np.max(ds_eq_cap[2,:]): + ul = (ds_pr[3,0]+ds_pr[3,1])/4 + ax.set_ylim([ll,ul]) + x2 = np.append(y,ul*x/x) + ax.fill(x1,x2,color=[1.,1.,0.6]) + figure_name = f"lyo_DesignSpace_DryingTime_{timestamp}.pdf" + plt.tight_layout() + plt.savefig(figure_name) + plt.close() + + # Product temperature vs pressures + + x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr + y1 = ((ds_eq_cap[0,-1]-ds_eq_cap[0,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_eq_cap[0,0] # equipment capability limiting product temperature in degC + y2 = ((ds_pr[0,-1]-ds_pr[0,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_pr[0,0] # product temperature limit in deg C + x = x*constant.Torr_to_mTorr # pressure range in mTorr + i = np.where(y1>=y2)[0][0] + y = np.append(y1[:i],y2[i:]) + x1 = np.append(x,x[::-1]) + + fig = plt.figure(0,figsize=(figwidth,figheight)) + ax = fig.add_subplot(1,1,1) + plt.axes(ax) + ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_eq_cap[0,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") + ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[0,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(product['T_pr_crit'])+" C")) + for i in range(np.size(Tshelf['setpt'])): + ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_shelf[0,i,:],'--',color=str(color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) + plot_styling.axis_style_ds_temperature(ax) + plt.legend(prop={'size':40}) + # The following seems incorrect: done for all three y axes, regardless of units + ll,ul = ax.get_ylim() + if np.min(ds_eq_cap[2,:])>np.max(ds_pr[3,:]): + ul = (ds_eq_cap[2,0]+ds_eq_cap[2,1])/3 + elif np.min(ds_pr[3,:])>np.max(ds_eq_cap[2,:]): + ul = (ds_pr[3,0]+ds_pr[3,1])/4 + ax.set_ylim([ll,ul]) + x2 = np.append(y,ll*x/x) + ax.fill(x1,x2,color=[1.,1.,0.6]) + figure_name = f"lyo_DesignSpace_ProductTemperature_{timestamp}.pdf" + plt.tight_layout() + plt.savefig(figure_name) + plt.close() \ No newline at end of file diff --git a/main.py b/main.py index e197971..855d056 100644 --- a/main.py +++ b/main.py @@ -55,13 +55,19 @@ # No Variable Pch and Tsh - set points must be specified # For 'Optimizer': Kv and Rp must be known, Tpr_crit must be provided # Can use variable Pch and/or Tsh -sim = dict([('tool','Primary Drying Calculator'),('Kv_known','Y'),('Rp_known','Y'),('Variable_Pch','N'),('Variable_Tsh','N')]) +sim = { + 'tool': 'Primary Drying Calculator', + 'Kv_known': True, + 'Rp_known': True, + 'Variable_Pch': False, + 'Variable_Tsh': False +} # Vial and fill properties # Av = Vial area in cm^2 # Ap = Product Area in cm^2 # Vfill = Fill volume in mL -vial = dict([('Av',3.80),('Ap',3.14),('Vfill',2.0)]) +vial = {'Av': 3.80, 'Ap': 3.14, 'Vfill': 2.0} #Product properties # cSolid = Fractional concentration of solute in the frozen solution @@ -71,11 +77,11 @@ # Product Resistance Parameters # R0 in cm^2-hr-Torr/g, A1 in cm-hr-Torr/g, A2 in 1/cm if sim['tool'] == 'Freezing Calculator': - product = dict([('cSolid',0.0),('Tpr0',15.8),('Tf',-1.54),('Tn',-5.84)]) + product = {'cSolid': 0.0, 'Tpr0': 15.8, 'Tf': -1.54, 'Tn': -5.84} elif not(sim['tool'] == 'Primary Drying Calculator' and sim['Rp_known'] == 'N'): - product = dict([('cSolid',0.05),('R0',1.4),('A1',16.0),('A2',0.0)]) + product = {'cSolid': 0.05, 'R0': 1.4, 'A1': 16.0, 'A2': 0.0} else: - product = dict([('cSolid',0.05)]) + product = {'cSolid': 0.05} # Experimental product temperature measurements: format - t(hr), Tp(C) product_temp_filename = './temperature.dat' # Critical product temperature @@ -86,11 +92,11 @@ if sim['tool'] == 'Freezing Calculator': # Heat transfer coefficient between product and surroundings h_freezing = 38.0 # in W/m^2/K -elif sim['Kv_known'] == 'Y': +elif sim['Kv_known']: # Kv = KC + KP*Pch/(1+KD*Pch) # KC in cal/s/K/cm^2, KP in cal/s/K/cm^2/Torr, KD in 1/Torr - ht = dict([('KC',2.75e-4),('KP',8.93e-4),('KD',0.46)]) -elif sim['Kv_known'] == 'N': + ht = {'KC': 2.75e-4, 'KP': 8.93e-4, 'KD': 0.46} +elif not sim['Kv_known']: Kv_range = np.arange(10.6,10.8,0.01)*1e-4; # cal/s/K/cm^2 # Primary drying time t_dry_exp = 12.62 # in hr @@ -103,30 +109,30 @@ 0 elif sim['tool'] == 'Design-Space-Generator': # Array of chamber pressure set points in Torr - Pchamber = dict([('setpt',[0.1,0.4,0.7,1.5])]) -elif not(sim['tool'] == 'Optimizer' and sim['Variable_Pch'] == 'Y'): + Pchamber = {'setpt':[0.1,0.4,0.7,1.5]} +elif not(sim['tool'] == 'Optimizer' and sim['Variable_Pch']): # setpt = Chamber pressure set points in Torr # dt_setpt = Time for which chamber pressure set points are held in min # ramp_rate = Chamber pressure ramping rate in Torr/min - Pchamber = dict([('setpt',[0.15]),('dt_setpt',[1800.0]),('ramp_rate',0.5)]) + Pchamber = {'setpt':[0.15],'dt_setpt':[1800.0],'ramp_rate':0.5} else: # Chamber pressure limits in Torr - Pchamber = dict([('min',0.05),('max',1000)]) + Pchamber = {'min':0.05,'max':1000} # Shelf Temperature if sim['tool'] == 'Design-Space-Generator': # Array of shelf temperature set points in C # ramp_rate = Shelf temperature ramping rate in C/min - Tshelf = dict([('init',-5.0),('setpt',[-5,0,2,5]),('ramp_rate',1.0)]) -elif not(sim['tool'] == 'Optimizer' and sim['Variable_Tsh'] == 'Y'): + Tshelf = {'init': -5.0, 'setpt': [-5, 0, 2, 5], 'ramp_rate': 1.0} +elif not (sim['tool'] == 'Optimizer' and sim['Variable_Tsh']): # init = Intial shelf temperature in C # setpt = Shelf temperature set points in C # dt_setpt = Time for which shelf temperature set points are held in min # ramp_rate = Shelf temperature ramping rate in C/min - Tshelf = dict([('init',-35.0),('setpt',[20.0]),('dt_setpt',[1800.0]),('ramp_rate',1.0)]) + Tshelf = {'init': -35.0, 'setpt': [20.0], 'dt_setpt': [1800.0], 'ramp_rate': 1.0} else: # Shelf temperature limits in C - Tshelf = dict([('min',-45),('max',120)]) + Tshelf = {'min': -45, 'max': 120} # Time step dt = 0.01 # hr @@ -134,11 +140,19 @@ # Lyophilizer equipment capability # Form: dm/dt [kg/hr] = a + b * Pch [Torr] # a in kg/hr, b in kg/hr/Torr -eq_cap = dict([('a',-0.182),('b',0.0117e3)]) +eq_cap = {'a': -0.182, 'b': 0.0117e3} # Equipment load nVial = 398 # Number of vials +# Get all the inputs that are defined into a config dictionary +config = {} +loc = locals() +for key in ['sim', 'vial', 'product', 'ht', 'Pchamber', 'Tshelf', 'dt', 'eq_cap', 'nVial', + 'h_freezing', 't_dry_exp', 'Kv_range', 'product_temp_filename']: + if key in loc: + config[key] = loc[key] + ######################################################## #################### Input file saved ################## @@ -146,447 +160,21 @@ # Write data to files #save input_saved.csv -csvfile = open('input_saved_'+current_time+'.csv', 'w') - -try: - writer = csv.writer(csvfile) - writer.writerow(['Tool:',sim['tool']]) - writer.writerow(['Kv known?:',sim['Kv_known']]) - writer.writerow(['Rp known?:',sim['Rp_known']]) - writer.writerow(['Variable Pch?:',sim['Variable_Pch']]) - writer.writerow(['Variable Tsh?:',sim['Variable_Tsh']]) - writer.writerow(['']) - - writer.writerow(['Vial area [cm^2]',vial['Av']]) - writer.writerow(['Product area [cm^2]',vial['Ap']]) - writer.writerow(['Vial fill volume [mL]',vial['Vfill']]) - writer.writerow(['']) - - writer.writerow(['Fractional solute concentration:',product['cSolid']]) - if sim['tool'] == 'Freezing Calculator': - writer.writerow(['Intial product temperature [C]:',product['Tpr0']]) - writer.writerow(['Freezing temperature [C]:',product['Tf']]) - writer.writerow(['Nucleation temperature [C]:',product['Tn']]) - elif not(sim['tool'] == 'Primary Drying Calculator' and sim['Rp_known'] == 'N'): - writer.writerow(['R0 [cm^2-hr-Torr/g]:',product['R0']]) - writer.writerow(['A1 [cm-hr-Torr/g]:',product['A1']]) - writer.writerow(['A2 [1/cm]:',product['A2']]) - if not(sim['tool'] == 'Freezing Calculator' and sim['tool'] == 'Primary Drying Calculator'): - writer.writerow(['Critical product temperature [C]:', product['T_pr_crit']]) - writer.writerow(['']) - - if sim['tool'] == 'Freezing Calculator': - writer.writerow(['h_freezing [W/m^2/K]:',h_freezing]) - elif sim['Kv_known'] == 'Y': - writer.writerow(['KC [cal/s/K/cm^2]:',ht['KC']]) - writer.writerow(['KP [cal/s/K/cm^2/Torr]:',ht['KP']]) - writer.writerow(['KD [1/Torr]:',ht['KD']]) - elif sim['Kv_known'] == 'N': - writer.writerow(['Kv range [cal/s/K/cm^2]:',Kv_range[:]]) - writer.writerow(['Experimental drying time [hr]:',t_dry_exp]) - writer.writerow(['']) - - if sim['tool'] == 'Freezing Calculator': - 0 - elif sim['tool'] == 'Design-Space-Generator': - writer.writerow(['Chamber pressure set points [Torr]:',Pchamber['setpt'][:]]) - elif not(sim['tool'] == 'Optimizer' and sim['Variable_Pch'] == 'Y'): - for i in range(len(Pchamber['setpt'])): - writer.writerow(['Chamber pressure setpoint [Torr]:',Pchamber['setpt'][i],'Duration [min]:',Pchamber['dt_setpt'][i]]) - writer.writerow(['Chamber pressure ramping rate [Torr/min]:',Pchamber['ramp_rate']]) - else: - writer.writerow(['Minimum chamber pressure [Torr]:',Pchamber['min']]) - writer.writerow(['Maximum chamber pressure [Torr]:',Pchamber['max']]) - writer.writerow(['']) - - if sim['tool'] == 'Design-Space-Generator': - writer.writerow(['Intial shelf temperature [C]:',Tshelf['init']]) - writer.writerow(['Shelf temperature set points [C]:',Tshelf['setpt'][:]]) - writer.writerow(['Shelf temperature ramping rate [C/min]:',Tshelf['ramp_rate']]) - elif not(sim['tool'] == 'Optimizer' and sim['Variable_Tsh'] == 'Y'): - for i in range(len(Tshelf['setpt'])): - writer.writerow(['Shelf temperature setpoint [C]:',Tshelf['setpt'][i],'Duration [min]:',Tshelf['dt_setpt'][i]]) - writer.writerow(['Shelf temperature ramping rate [C/min]:',Tshelf['ramp_rate']]) - else: - writer.writerow(['Minimum shelf temperature [C]:',Tshelf['min']]) - writer.writerow(['Maximum shelf temperature [C]:',Tshelf['max']]) - writer.writerow(['']) - - writer.writerow(['Time step [hr]:',dt]) - writer.writerow(['']) - - writer.writerow(['Equipment capability parameters:','a [kg/hr]:',eq_cap['a'],'b [kg/hr/Torr]:',eq_cap['b']]) - writer.writerow(['Number of vials:',nVial]) - -finally: - csvfile.close() +save_configuration_legacy(config, current_time) ######################################################## ################### Execute ########################## -################# - -###### Freezing Calculator -if sim['tool'] == 'Freezing Calculator': - freezing_output_saved = freezing.freeze(vial,product,h_freezing,Tshelf,dt) - -################# - -###### Primary Drying Calculator Tool -if sim['tool'] == 'Primary Drying Calculator': - - #### Known Kv and Rp - if (sim['Kv_known'] == 'Y' and sim['Rp_known'] == 'Y'): - output_saved = calc_knownRp.dry(vial,product,ht,Pchamber,Tshelf,dt) - - #### Determine Kv based on drying time - elif (sim['Kv_known'] == 'N' and sim['Rp_known'] == 'Y'): - Kv_best = Kv_range[0] - Time_dev_min = 1000000.0 - ht = dict([('KC',0.0),('KP',0.0),('KD',0.0)]) - for ht['KC'] in Kv_range: - output_saved_new = calc_knownRp.dry(vial,product,ht,Pchamber,Tshelf,dt) - time = output_saved_new[-1,0] # Total simulated drying time in hr - Time_dev = abs(t_dry_exp-time)/t_dry_exp*100; # Percentage deviation of simulated drying time from experimental - if Time_dev < Time_dev_min: - Time_dev_min = Time_dev - Kv_best = ht['KC'] - output_saved = output_saved_new - print("Best Kv = "+str(Kv_best)+"\n") - print("Drying time deviation = "+str(Time_dev_min)+"%\n") - - #### Determine Rp based on product temperature - elif (sim['Kv_known'] == 'Y' and sim['Rp_known'] == 'N'): - time = [] - Tbot_exp = [] - with open(product_temp_filename) as fi: - for line in fi: - line_string = np.fromstring(line,sep=' ') - time = np.append(time,line_string[0]) - Tbot_exp = np.append(Tbot_exp,line_string[1]) - fi.close() - output_saved, product_res = calc_unknownRp.dry(vial,product,ht,Pchamber,Tshelf,time,Tbot_exp) - params,params_covariance = sp.curve_fit(functions.Rp_FUN,product_res[:,1],product_res[:,2],p0=[1.0,0.0,0.0]) - print("R0 = "+str(params[0])+"\n") - print("A1 = "+str(params[1])+"\n") - print("A2 = "+str(params[2])+"\n") - - else: - print("Error: Either Kv or Rp must be specified") - sys.exit(1) - -################# - -###### Design Space Generator Tool -if sim['tool'] == 'Design-Space-Generator': - DS_shelf, DS_pr, DS_eq_cap = design_space.dry(vial,product,ht,Pchamber,Tshelf,dt,eq_cap,nVial) - -################# - -###### Optimizer Tool -if sim['tool'] == 'Optimizer': +output_data = execute_simulation(config) - #### Variable Pch and Tsh - if (sim['Variable_Pch'] == 'Y' and sim['Variable_Tsh'] == 'Y'): - output_saved = opt_Pch_Tsh.dry(vial,product,ht,Pchamber,Tshelf,dt,eq_cap,nVial) - - #### Variable Pch at specified Tsh - elif (sim['Variable_Pch'] == 'Y' and sim['Variable_Tsh'] == 'N'): - output_saved = opt_Pch.dry(vial,product,ht,Pchamber,Tshelf,dt,eq_cap,nVial) - - #### Variable Tsh at specified Pch - elif (sim['Variable_Pch'] == 'N' and sim['Variable_Tsh'] == 'Y'): - output_saved = opt_Tsh.dry(vial,product,ht,Pchamber,Tshelf,dt,eq_cap,nVial) - - else: - print("Error: Either Pch or Tsh must be variable for process optimization") - sys.exit(1) - ###################################################### ####################### Outputs ####################### -# LaTeX setup -matplotlibrc('text.latex', preamble=r'\usepackage{color}') -matplotlibrc('text',usetex=False) -matplotlibrc('font',family='sans-serif') - -figwidth = 30 -figheight = 20 -lineWidth = 5 -textFontSize = 60 -gcafontSize = 60 -markerSize = 20 -labelPad = 30 -majorTickWidth = 5 -minorTickWidth = 3 -majorTickLength = 30 -minorTickLength = 20 - -Color_list = ['b','m','g','c','r','y','k'] # Line colors - # Write data to files -#save output_saved.csv -# Plot data and save figures -csvfile = open('output_saved_'+current_time+'.csv', 'w') - -if sim['tool'] == 'Design-Space-Generator': - try: - writer = csv.writer(csvfile) - writer.writerow(['Chamber Pressure [mTorr]','Maximum Product Temperature [C]','Drying Time [hr]','Average Sublimation Flux [kg/hr/m^2]','Maximum/Minimum Sublimation Flux [kg/hr/m^2]','Final Sublimation Flux [kg/hr/m^2]']) - for i in range(np.size(Tshelf['setpt'])): - writer.writerow(['Shelf Temperature = ',str(Tshelf['setpt'][i])]) - for j in range(np.size(Pchamber['setpt'])): - writer.writerow([Pchamber['setpt'][j]*constant.Torr_to_mTorr,DS_shelf[0,i,j],DS_shelf[1,i,j],DS_shelf[2,i,j],DS_shelf[3,i,j],DS_shelf[4,i,j]]) - writer.writerow(['Product Temperature = ',str(product['T_pr_crit'])]) - writer.writerow([Pchamber['setpt'][0]*constant.Torr_to_mTorr,DS_pr[0,0],DS_pr[1,0],DS_pr[2,0],DS_pr[3,0],DS_pr[4,0]]) - writer.writerow([Pchamber['setpt'][-1]*constant.Torr_to_mTorr,DS_pr[0,1],DS_pr[1,1],DS_pr[2,1],DS_pr[3,1],DS_pr[4,1]]) - writer.writerow(['Equipment Capability']) - for k in range(np.size(Pchamber['setpt'])): - writer.writerow([Pchamber['setpt'][k]*constant.Torr_to_mTorr,DS_eq_cap[0,k],DS_eq_cap[1,k],DS_eq_cap[2,k],DS_eq_cap[2,k],DS_eq_cap[2,k]]) - finally: - csvfile.close() - - x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr - y1 = ((DS_eq_cap[2,-1]-DS_eq_cap[2,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + DS_eq_cap[2,0] # equipment capability sublimation flux in kg/hr/m^2 - y2 = ((DS_pr[3,-1]-DS_pr[3,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + DS_pr[3,0] # product temperature limited sublimation flux in kg/hr/m^2 - x = x*constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1>=y2)[0][0] - y = np.append(y1[:i],y2[i:]) - x1 = np.append(x,x[::-1]) - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) - plt.axes(ax) - plt.minorticks_on() - plt.setp(ax.get_xticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - plt.setp(ax.get_yticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.tick_params(axis='x',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,left=1,right=0) - ax.tick_params(axis='x',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,left=1,right=0) - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],DS_eq_cap[2,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") - ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],DS_pr[3,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(product['T_pr_crit'])+" C")) - for i in range(np.size(Tshelf['setpt'])): - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],DS_shelf[3,i,:],'--',color=str(Color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) - ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.xaxis.labelpad = labelPad - ax.yaxis.labelpad = labelPad - handles, labels = ax.get_legend_handles_labels() - plt.legend(handles, labels, prop={'size':40},loc='best') - ll,ul = ax.get_ylim() - if np.min(DS_eq_cap[2,:])>np.max(DS_pr[3,:]): - ul = (DS_eq_cap[2,0]+DS_eq_cap[2,1])/3 - elif np.min(DS_pr[3,:])>np.max(DS_eq_cap[2,:]): - ul = (DS_pr[3,0]+DS_pr[3,1])/4 - ax.set_ylim([ll,ul]) - x2 = np.append(y,ll*x/x) - ax.fill(x1,x2,color=[1.,1.,0.6]) - figure_name = 'DesignSpace_SublimationFlux_'+current_time+'.pdf' - plt.tight_layout() - plt.savefig(figure_name) - plt.close() - - x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr - y1 = ((DS_eq_cap[1,-1]-DS_eq_cap[1,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + DS_eq_cap[1,0] # equipment capability drying time in hr - y2 = ((DS_pr[1,-1]-DS_pr[1,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + DS_pr[1,0] # product temperature limited drying time in hr - x = x*constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1np.max(DS_pr[3,:]): - ul = (DS_eq_cap[2,0]+DS_eq_cap[2,1])/3 - elif np.min(DS_pr[3,:])>np.max(DS_eq_cap[2,:]): - ul = (DS_pr[3,0]+DS_pr[3,1])/4 - ax.set_ylim([ll,ul]) - x2 = np.append(y,ul*x/x) - ax.fill(x1,x2,color=[1.,1.,0.6]) - figure_name = 'DesignSpace_DryingTime_'+current_time+'.pdf' - plt.tight_layout() - plt.savefig(figure_name) - plt.close() - - x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr - y1 = ((DS_eq_cap[0,-1]-DS_eq_cap[0,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + DS_eq_cap[0,0] # equipment capability limiting product temperature in degC - y2 = ((DS_pr[0,-1]-DS_pr[0,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + DS_pr[0,0] # product temperature limit in deg C - x = x*constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1>=y2)[0][0] - y = np.append(y1[:i],y2[i:]) - x1 = np.append(x,x[::-1]) - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) - plt.axes(ax) - plt.minorticks_on() - plt.setp(ax.get_xticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - plt.setp(ax.get_yticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.tick_params(axis='x',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,left=1,right=0) - ax.tick_params(axis='x',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,left=1,right=0) - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],DS_eq_cap[0,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") - ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],DS_pr[0,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(product['T_pr_crit'])+" C")) - for i in range(np.size(Tshelf['setpt'])): - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],DS_shelf[0,i,:],'--',color=str(Color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) - ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.set_ylabel("Product Temperature [C]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.xaxis.labelpad = labelPad - ax.yaxis.labelpad = labelPad - handles, labels = ax.get_legend_handles_labels() - plt.legend(handles, labels, prop={'size':40},loc='best') - ll,ul = ax.get_ylim() - if np.min(DS_eq_cap[2,:])>np.max(DS_pr[3,:]): - ul = (DS_eq_cap[2,0]+DS_eq_cap[2,1])/3 - elif np.min(DS_pr[3,:])>np.max(DS_eq_cap[2,:]): - ul = (DS_pr[3,0]+DS_pr[3,1])/4 - ax.set_ylim([ll,ul]) - x2 = np.append(y,ll*x/x) - ax.fill(x1,x2,color=[1.,1.,0.6]) - figure_name = 'DesignSpace_ProductTemperature_'+current_time+'.pdf' - plt.tight_layout() - plt.savefig(figure_name) - plt.close() - -elif sim['tool'] == 'Freezing Calculator': - try: - writer = csv.writer(csvfile) - writer.writerow(['Time [hr]','Shelf Temperature [C]','Product Temperature [C]']) - for i in range(0,len(freezing_output_saved)): - writer.writerow(freezing_output_saved[i]) - finally: - csvfile.close() - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) - plt.axes(ax) - plt.minorticks_on() - plt.setp(ax.get_xticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - plt.setp(ax.get_yticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.tick_params(axis='x',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,left=1,right=0) - ax.tick_params(axis='x',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,left=1,right=0) - ax.plot(freezing_output_saved[:,0],freezing_output_saved[:,1],'-k',linewidth=lineWidth, label = "Shelf Temperature") - ax.plot(freezing_output_saved[:,0],freezing_output_saved[:,2],'-b',linewidth=lineWidth, label = "Product Temperature") - ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.set_ylabel("Temperature [C]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.xaxis.labelpad = labelPad - ax.yaxis.labelpad = labelPad - handles, labels = ax.get_legend_handles_labels() - plt.legend(handles, labels, prop={'size':40},loc='best') - ll,ul = ax.get_ylim() - ax.set_ylim([ll,ul+5.0]) - figure_name = 'Temperatures_'+current_time+'.pdf' - plt.tight_layout() - plt.savefig(figure_name) - plt.close() +save_csv(output_data, config, current_time) -else: - try: - writer = csv.writer(csvfile) - writer.writerow(['Time [hr]','Sublimation Temperature [C]','Vial Bottom Temperature [C]', 'Shelf Temperature [C]','Chamber Pressure [mTorr]','Sublimation Flux [kg/hr/m^2]','Percent Dried']) - for i in range(0,len(output_saved)): - writer.writerow(output_saved[i]) - finally: - csvfile.close() - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax1 = fig.add_subplot(1,1,1) - ax2 = ax1.twinx() - plt.axes(ax1) - plt.minorticks_on() - plt.axes(ax2) - plt.minorticks_on() - plt.setp(ax1.get_xticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - plt.setp(ax1.get_yticklabels(),fontsize=gcafontSize,color='b',fontweight='bold',fontname="Helvetica") - plt.setp(ax2.get_yticklabels(),fontsize=gcafontSize,color=[0,0.7,0.3],fontweight='bold',fontname="Helvetica") - ax1.tick_params(axis='x',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) - ax1.tick_params(axis='y',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,color='b') - ax2.tick_params(axis='y',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,color=[0,0.7,0.3]) - ax1.tick_params(axis='x',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,bottom=1,top=0) - ax1.tick_params(axis='y',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,color='b') - ax2.tick_params(axis='y',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,color=[0,0.7,0.3]) - ax1.plot(output_saved[:,0],output_saved[:,4],'-o',color='b',markevery=5,linewidth=lineWidth, markersize=markerSize, label = "Chamber Pressure") - ax1.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax1.set_ylabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,color='b',fontweight='bold',fontname="Helvetica") - ax2.plot(output_saved[:,0],output_saved[:,5],'-',color=[0,0.7,0.3],linewidth=lineWidth, label = "Sublimation Flux") - ax2.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,color=[0,0.7,0.3],fontweight='bold',fontname="Helvetica") - ax1.xaxis.labelpad = labelPad - ax1.yaxis.labelpad = labelPad - ax2.yaxis.labelpad = labelPad - figure_name = 'Pressure,SublimationFlux_'+current_time+'.pdf' - plt.tight_layout() - plt.savefig(figure_name) - plt.close() - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) - plt.axes(ax) - plt.minorticks_on() - plt.setp(ax.get_xticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - plt.setp(ax.get_yticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.tick_params(axis='x',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,left=1,right=0) - ax.tick_params(axis='x',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,left=1,right=0) - ax.plot(output_saved[:,0],output_saved[:,-1],'-k',linewidth=lineWidth, label = "Percent Dried") - ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.set_ylabel("Percent Dried",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.xaxis.labelpad = labelPad - ax.yaxis.labelpad = labelPad - figure_name = 'PercentDried_'+current_time+'.pdf' - plt.tight_layout() - plt.savefig(figure_name) - plt.close() - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) - plt.axes(ax) - plt.minorticks_on() - plt.setp(ax.get_xticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - plt.setp(ax.get_yticklabels(),fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.tick_params(axis='x',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,left=1,right=0) - ax.tick_params(axis='x',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,bottom=1,top=0) - ax.tick_params(axis='y',which='minor',direction='in',width=minorTickWidth,length=minorTickLength,left=1,right=0) - ax.plot(output_saved[:,0],output_saved[:,1],'-b',linewidth=lineWidth, label = "Sublimation Front Temperature") - ax.plot(output_saved[:,0],output_saved[:,2],'-r',linewidth=lineWidth, label = "Maximum Product Temperature") - ax.plot(output_saved[:,0],output_saved[:,3],'-o',color='k',markevery=5,linewidth=lineWidth, markersize=markerSize, label = "Shelf Temperature") - ax.set_xlabel("Time [hr]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.set_ylabel("Temperature [C]",fontsize=gcafontSize,fontweight='bold',fontname="Helvetica") - ax.xaxis.labelpad = labelPad - ax.yaxis.labelpad = labelPad - handles, labels = ax.get_legend_handles_labels() - plt.legend(handles, labels, prop={'size':40},loc='best') - ll,ul = ax.get_ylim() - ax.set_ylim([ll,ul+5.0]) - figure_name = 'Temperatures_'+current_time+'.pdf' - plt.tight_layout() - plt.savefig(figure_name) - plt.close() +# Plot data and save figures -####################################################### +generate_visualizations(output_data, config, current_time) \ No newline at end of file From 5e6b91d8cabd250347da27b75dfbbb05040e57ec Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 19 Dec 2025 19:35:44 -0500 Subject: [PATCH 04/31] kwarg name fix --- lyopronto/plot_styling.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lyopronto/plot_styling.py b/lyopronto/plot_styling.py index 7b229ac..45f6a33 100644 --- a/lyopronto/plot_styling.py +++ b/lyopronto/plot_styling.py @@ -14,7 +14,7 @@ # You should have received a copy of the GNU General Public License # along with this program. If not, see . -default_font_spec = {"fontweight":"bold", "font_family":"Arial"} +default_font_spec = {"fontweight":"bold", "fontname":"Arial"} # TODO: document these kwargs def axis_tick_styling( From a706d515a1ac9b5b038f8193dbe3635ba05f6c31 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 19 Dec 2025 19:38:14 -0500 Subject: [PATCH 05/31] fix --- lyopronto/plot_styling.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lyopronto/plot_styling.py b/lyopronto/plot_styling.py index 45f6a33..10c0698 100644 --- a/lyopronto/plot_styling.py +++ b/lyopronto/plot_styling.py @@ -31,7 +31,7 @@ def axis_tick_styling( ax.minorticks_on() ax.tick_params(axis='both',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) ax.tick_params(axis='both',which='minor',direction='in',width=minorTickWidth,length=minorTickLength) - ax.tick_params(axis='both',labelsize=gcafontSize,labelfontfamily=default_font_spec['font_family']) + ax.tick_params(axis='both',labelsize=gcafontSize,labelfontfamily=default_font_spec['fontname']) ax.tick_params(axis='y',which='both',color=color, labelcolor=color) for tick in [*ax.get_xticklabels(), *ax.get_yticklabels()]: tick.set_fontweight('bold') From 459868170abdeccb68db006207dd6c871b0e6403 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Tue, 3 Feb 2026 12:52:08 -0500 Subject: [PATCH 06/31] Move data load to main script, not helper function, to emphasize user changing it --- lyopronto/__init__.py | 12 ++++-------- main.py | 12 +++++++----- 2 files changed, 11 insertions(+), 13 deletions(-) diff --git a/lyopronto/__init__.py b/lyopronto/__init__.py index 5c23963..ab1e438 100644 --- a/lyopronto/__init__.py +++ b/lyopronto/__init__.py @@ -119,18 +119,14 @@ def _optimize_kv_parameter(config): def _optimize_rp_parameter(config): """Helper to determine Rp from experimental product temperature.""" - exp_data = np.loadtxt(config['product_temp_file']) - time_data = exp_data[:, 0] - temp_data = exp_data[:, 1] - output, product_res = calc_unknownRp.dry( config['vial'], config['product'], config['ht'], config['Pchamber'], config['Tshelf'], - time_data, - temp_data + config['time_data'], + config['temp_data'] ) params, _ = sp.curve_fit( @@ -425,7 +421,7 @@ def _plot_design_space(data, config, props, timestamp): ax = fig.add_subplot(1,1,1) plt.axes(ax) ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_eq_cap[1,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") - ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[1,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(product['T_pr_crit'])+" C")) + ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[1,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(config['product']['T_pr_crit'])+" C")) for i in range(np.size(Tshelf['setpt'])): ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_shelf[1,i,:],'--',color=str(color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) plot_styling.axis_style_ds_percdried(ax) @@ -458,7 +454,7 @@ def _plot_design_space(data, config, props, timestamp): ax = fig.add_subplot(1,1,1) plt.axes(ax) ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_eq_cap[0,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") - ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[0,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(product['T_pr_crit'])+" C")) + ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[0,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(config['product']['T_pr_crit'])+" C")) for i in range(np.size(Tshelf['setpt'])): ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_shelf[0,i,:],'--',color=str(color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) plot_styling.axis_style_ds_temperature(ax) diff --git a/main.py b/main.py index 855d056..f23b235 100644 --- a/main.py +++ b/main.py @@ -17,10 +17,7 @@ # along with this program. If not, see . import sys -import scipy.optimize as sp import numpy as np -import math -import csv from lyopronto import * # from . import constant @@ -82,8 +79,13 @@ product = {'cSolid': 0.05, 'R0': 1.4, 'A1': 16.0, 'A2': 0.0} else: product = {'cSolid': 0.05} - # Experimental product temperature measurements: format - t(hr), Tp(C) + product_temp_filename = './temperature.dat' + exp_data = np.loadtxt(product_temp_filename) + # Assumed: time in first column, temperature in second column + # Change as necessary to match data file, but keep these names + time_data = exp_data[:, 0] + temp_data = exp_data[:, 1] # Critical product temperature # At least 2 to 3 deg C below collapse or glass transition temperature product['T_pr_crit'] = -5 # in degC @@ -149,7 +151,7 @@ config = {} loc = locals() for key in ['sim', 'vial', 'product', 'ht', 'Pchamber', 'Tshelf', 'dt', 'eq_cap', 'nVial', - 'h_freezing', 't_dry_exp', 'Kv_range', 'product_temp_filename']: + 'h_freezing', 't_dry_exp', 'Kv_range', 'time_data', 'temp_data']: if key in loc: config[key] = loc[key] From 3a13f1fb7c8d3bb4a6006847d2da15ce5899381b Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Tue, 3 Feb 2026 14:45:08 -0500 Subject: [PATCH 07/31] Switch to bisection search for best Kv, not iteration over array --- lyopronto/__init__.py | 55 ++++++++++++++++++++++++++----------------- 1 file changed, 34 insertions(+), 21 deletions(-) diff --git a/lyopronto/__init__.py b/lyopronto/__init__.py index ab1e438..87ecfcf 100644 --- a/lyopronto/__init__.py +++ b/lyopronto/__init__.py @@ -90,30 +90,43 @@ def execute_simulation(config): # TODO: bisection search, rather than iteration over a range? def _optimize_kv_parameter(config): """Helper to determine Kv based on experimental drying time.""" - Kv_range = config['Kv_range'] - best_Kv = Kv_range[0] - min_deviation = float('inf') - best_output = None - - for Kc in Kv_range: + Kv_range = inputs.get("Kv_range", (1e-6, 1e-2)) + + def obj(Kc): output = calc_knownRp.dry( - config['vial'], - config['product'], - {'KC': Kc, 'KP': 0.0, 'KD': 0.0}, - config['Pchamber'], - config['Tshelf'], - config['dt'] + inputs["vial"], + inputs["product"], + {"KC": Kc, "KP": 0.0, "KD": 0.0}, + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], ) simulated_time = output[-1, 0] - deviation = abs(config['t_dry_exp'] - simulated_time) / config['t_dry_exp'] * 100 - - if deviation < min_deviation: - min_deviation = deviation - best_Kv = Kc - best_output = output - - print(f"Optimal Kv: {best_Kv}, Deviation: {min_deviation}%") - return best_output + return simulated_time - inputs["t_dry_exp"] + + if obj(Kv_range[0]) * obj(Kv_range[-1]) > 0: + warn( + "Given Kv bounds do not bracket the most likely value. Choosing either min or max." + ) + if abs(obj(Kv_range[0])) < abs(obj(Kv_range[-1])): + best_Kv = Kv_range[0] + else: + best_Kv = Kv_range[-1] + else: + best_Kv = brentq(obj, Kv_range[0], Kv_range[-1]) + + deviation = obj(best_Kv) + output = calc_knownRp.dry( + inputs["vial"], + inputs["product"], + {"KC": best_Kv, "KP": 0.0, "KD": 0.0}, + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + ) + + print(f"Optimal Kv: {best_Kv}, Deviation: {deviation}%") + return output def _optimize_rp_parameter(config): From 6486ec742eaf365490bb733278f0b9d20466c35c Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Tue, 3 Feb 2026 14:45:28 -0500 Subject: [PATCH 08/31] Format with ruff --- lyopronto/__init__.py | 860 ++++++++++++++++++++++++++++-------------- main.py | 133 ++++--- 2 files changed, 643 insertions(+), 350 deletions(-) diff --git a/lyopronto/__init__.py b/lyopronto/__init__.py index 87ecfcf..7215e1a 100644 --- a/lyopronto/__init__.py +++ b/lyopronto/__init__.py @@ -5,12 +5,12 @@ # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. - + # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. - + # You should have received a copy of the GNU General Public License # along with this program. If not, see . @@ -30,65 +30,72 @@ # ---------------------- # Provide functionality for running LyoPRONTO as a module +from warnings import warn import numpy as np import csv import matplotlib.pyplot as plt from matplotlib import rc as matplotlibrc -import scipy.optimize as sp +from scipy.optimize import curve_fit, brentq +from ruamel.yaml import YAML + +yaml = YAML() -def execute_simulation(config): + +def execute_simulation(inputs): """ - Run the selected simulation tool with the provided configuration. + Run the selected simulation tool with the provided inputs. Returns output data based on the chosen simulation mode. """ - sim_type = config['sim']['tool'] + sim_type = inputs["sim"]["tool"] output_data = None - - if sim_type == 'Freezing Calculator': + + if sim_type == "Freezing Calculator": output_data = freezing.freeze( - config['vial'], - config['product'], - config['h_freezing'], - config['Tshelf'], - config['dt'] + inputs["vial"], + inputs["product"], + inputs["h_freezing"], + inputs["Tshelf"], + inputs["dt"], ) - - elif sim_type == 'Primary Drying Calculator': - if config['sim']['Kv_known'] and config['sim']['Rp_known']: + + elif sim_type == "Primary Drying Calculator": + if inputs["sim"]["Kv_known"] and inputs["sim"]["Rp_known"]: output_data = calc_knownRp.dry( - config['vial'], - config['product'], - config['ht'], - config['Pchamber'], - config['Tshelf'], - config['dt'] + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], ) - elif not config['sim']['Kv_known'] and config['sim']['Rp_known']: - output_data = _optimize_kv_parameter(config) - elif config['sim']['Kv_known'] and not config['sim']['Rp_known']: - output_data = _optimize_rp_parameter(config) + elif not inputs["sim"]["Kv_known"] and inputs["sim"]["Rp_known"]: + output_data = _optimize_kv_parameter(inputs) + elif inputs["sim"]["Kv_known"] and not inputs["sim"]["Rp_known"]: + output_data = _optimize_rp_parameter(inputs) else: - raise ValueError("With the current implementation, either Kv or Rp must be specified.") - - elif sim_type == 'Design-Space-Generator': + raise ValueError( + "With the current implementation, either Kv or Rp must be specified." + ) + + elif sim_type == "Design-Space-Generator": output_data = design_space.dry( - config['vial'], - config['product'], - config['ht'], - config['Pchamber'], - config['Tshelf'], - config['dt'], - config['eq_cap'], - config['nVial'] + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + inputs["eq_cap"], + inputs["nVial"], ) - - elif sim_type == 'Optimizer': - output_data = _run_optimizer(config) - + + elif sim_type == "Optimizer": + output_data = _run_optimizer(inputs) + return output_data -# TODO: bisection search, rather than iteration over a range? -def _optimize_kv_parameter(config): + +def _optimize_kv_parameter(inputs): """Helper to determine Kv based on experimental drying time.""" Kv_range = inputs.get("Kv_range", (1e-6, 1e-2)) @@ -129,359 +136,628 @@ def obj(Kc): return output -def _optimize_rp_parameter(config): +def _optimize_rp_parameter(inputs): """Helper to determine Rp from experimental product temperature.""" - + output, product_res = calc_unknownRp.dry( - config['vial'], - config['product'], - config['ht'], - config['Pchamber'], - config['Tshelf'], - config['time_data'], - config['temp_data'] + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["time_data"], + inputs["temp_data"], ) - - params, _ = sp.curve_fit( - functions.Rp_FUN, - product_res[:, 1], - product_res[:, 2], - p0=[1.0, 0.0, 0.0] + + params, _ = curve_fit( + functions.Rp_FUN, product_res[:, 1], product_res[:, 2], p0=[1.0, 0.0, 0.0] ) - + print(f"R0: {params[0]}, A1: {params[1]}, A2: {params[2]}") return output -def _run_optimizer(config): +def _run_optimizer(inputs): """Helper to run optimization with variable parameters.""" - args = ( config['vial'], config['product'], config['ht'], - config['Pchamber'], config['Tshelf'], config['dt'], - config['eq_cap'], config['nVial']) - if config['sim']['Variable_Pch'] and config['sim']['Variable_Tsh']: + args = ( + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + inputs["eq_cap"], + inputs["nVial"], + ) + if inputs["sim"]["Variable_Pch"] and inputs["sim"]["Variable_Tsh"]: return opt_Pch_Tsh.dry(*args) - elif config['sim']['Variable_Pch']: + elif inputs["sim"]["Variable_Pch"]: return opt_Pch.dry(*args) - elif config['sim']['Variable_Tsh']: + elif inputs["sim"]["Variable_Tsh"]: return opt_Tsh.dry(*args) -def save_configuration_legacy(config, timestamp): +def save_inputs_legacy(inputs, timestamp): """ - Persist configuration parameters to a CSV file with timestamped filename. + Save inputs to a CSV file with timestamped filename. """ - filename = f'lyopronto_input_{timestamp}.csv' - sim = config['sim'] - vial = config['vial'] - product = config['product'] - - with open(filename, 'w', newline='') as csvfile: + filename = f"lyopronto_input_{timestamp}.csv" + sim = inputs["sim"] + vial = inputs["vial"] + product = inputs["product"] + + with open(filename, "w", newline="") as csvfile: writer = csv.writer(csvfile) - - writer.writerow(['Simulation Tool', sim['tool']]) - writer.writerow(['Kv Known', sim['Kv_known']]) - writer.writerow(['Rp Known', sim['Rp_known']]) - writer.writerow(['Variable Chamber Pressure', sim['Variable_Pch']]) - writer.writerow(['Variable Shelf Temperature', sim['Variable_Tsh']]) + + writer.writerow(["Simulation Tool", sim["tool"]]) + writer.writerow(["Kv Known", sim["Kv_known"]]) + writer.writerow(["Rp Known", sim["Rp_known"]]) + writer.writerow(["Variable Chamber Pressure", sim["Variable_Pch"]]) + writer.writerow(["Variable Shelf Temperature", sim["Variable_Tsh"]]) writer.writerow([]) - - writer.writerow(['Vial Cross-Section [cm²]', vial['Av']]) - writer.writerow(['Product Area [cm²]', vial['Ap']]) - writer.writerow(['Fill Volume [mL]', vial['Vfill']]) + + writer.writerow(["Vial Cross-Section [cm²]", vial["Av"]]) + writer.writerow(["Product Area [cm²]", vial["Ap"]]) + writer.writerow(["Fill Volume [mL]", vial["Vfill"]]) writer.writerow([]) - - writer.writerow(['Fractional solute concentration:',product['cSolid']]) - if sim['tool'] == 'Freezing Calculator': - writer.writerow(['Intial product temperature [C]:',product['Tpr0']]) - writer.writerow(['Freezing temperature [C]:',product['Tf']]) - writer.writerow(['Nucleation temperature [C]:',product['Tn']]) - elif not(sim['tool'] == 'Primary Drying Calculator' and sim['Rp_known'] == 'N'): - writer.writerow(['R0 [cm^2-hr-Torr/g]:',product['R0']]) - writer.writerow(['A1 [cm-hr-Torr/g]:',product['A1']]) - writer.writerow(['A2 [1/cm]:',product['A2']]) - if not(sim['tool'] == 'Freezing Calculator' and sim['tool'] == 'Primary Drying Calculator'): - writer.writerow(['Critical product temperature [C]:', product['T_pr_crit']]) - - if sim['tool'] == 'Freezing Calculator': - writer.writerow(['h_freezing [W/m^2/K]:',config['h_freezing']]) - elif sim['Kv_known']: - writer.writerow(['KC [cal/s/K/cm^2]:',config['ht']['KC']]) - writer.writerow(['KP [cal/s/K/cm^2/Torr]:',config['ht']['KP']]) - writer.writerow(['KD [1/Torr]:',config['ht']['KD']]) - elif not sim['Kv_known']: - writer.writerow(['Kv range [cal/s/K/cm^2]:',config['Kv_range'][:]]) - writer.writerow(['Experimental drying time [hr]:',config['t_dry_exp']]) - - - if sim['tool'] == 'Freezing Calculator': + + writer.writerow(["Fractional solute concentration:", product["cSolid"]]) + if sim["tool"] == "Freezing Calculator": + writer.writerow(["Intial product temperature [C]:", product["Tpr0"]]) + writer.writerow(["Freezing temperature [C]:", product["Tf"]]) + writer.writerow(["Nucleation temperature [C]:", product["Tn"]]) + elif not ( + sim["tool"] == "Primary Drying Calculator" and sim["Rp_known"] == "N" + ): + writer.writerow(["R0 [cm^2-hr-Torr/g]:", product["R0"]]) + writer.writerow(["A1 [cm-hr-Torr/g]:", product["A1"]]) + writer.writerow(["A2 [1/cm]:", product["A2"]]) + if not ( + sim["tool"] == "Freezing Calculator" + and sim["tool"] == "Primary Drying Calculator" + ): + writer.writerow(["Critical product temperature [C]:", product["T_pr_crit"]]) + + if sim["tool"] == "Freezing Calculator": + writer.writerow(["h_freezing [W/m^2/K]:", inputs["h_freezing"]]) + elif sim["Kv_known"]: + writer.writerow(["KC [cal/s/K/cm^2]:", inputs["ht"]["KC"]]) + writer.writerow(["KP [cal/s/K/cm^2/Torr]:", inputs["ht"]["KP"]]) + writer.writerow(["KD [1/Torr]:", inputs["ht"]["KD"]]) + elif not sim["Kv_known"]: + writer.writerow(["Kv range [cal/s/K/cm^2]:", inputs["Kv_range"][:]]) + writer.writerow(["Experimental drying time [hr]:", inputs["t_dry_exp"]]) + + if sim["tool"] == "Freezing Calculator": 0 - elif sim['tool'] == 'Design-Space-Generator': - writer.writerow(['Chamber pressure set points [Torr]:',config['Pchamber']['setpt'][:]]) - elif not(sim['tool'] == 'Optimizer' and sim['Variable_Pch'] == 'Y'): - for i in range(len(config['Pchamber']['setpt'])): - writer.writerow(['Chamber pressure setpoint [Torr]:',config['Pchamber']['setpt'][i],'Duration [min]:',config['Pchamber']['dt_setpt'][i]]) - writer.writerow(['Chamber pressure ramping rate [Torr/min]:',config['Pchamber']['ramp_rate']]) + elif sim["tool"] == "Design-Space-Generator": + writer.writerow( + ["Chamber pressure set points [Torr]:", inputs["Pchamber"]["setpt"][:]] + ) + elif not (sim["tool"] == "Optimizer" and sim["Variable_Pch"] == "Y"): + for i in range(len(inputs["Pchamber"]["setpt"])): + writer.writerow( + [ + "Chamber pressure setpoint [Torr]:", + inputs["Pchamber"]["setpt"][i], + "Duration [min]:", + inputs["Pchamber"]["dt_setpt"][i], + ] + ) + writer.writerow( + [ + "Chamber pressure ramping rate [Torr/min]:", + inputs["Pchamber"]["ramp_rate"], + ] + ) else: - writer.writerow(['Minimum chamber pressure [Torr]:',config['Pchamber']['min']]) - writer.writerow(['Maximum chamber pressure [Torr]:',config['Pchamber']['max']]) - writer.writerow(['']) - - if sim['tool'] == 'Design-Space-Generator': - writer.writerow(['Intial shelf temperature [C]:',config['Tshelf']['init']]) - writer.writerow(['Shelf temperature set points [C]:',config['Tshelf']['setpt'][:]]) - writer.writerow(['Shelf temperature ramping rate [C/min]:',config['Tshelf']['ramp_rate']]) - elif not(sim['tool'] == 'Optimizer' and sim['Variable_Tsh'] == 'Y'): - for i in range(len(config['Tshelf']['setpt'])): - writer.writerow(['Shelf temperature setpoint [C]:',config['Tshelf']['setpt'][i],'Duration [min]:',config['Tshelf']['dt_setpt'][i]]) - writer.writerow(['Shelf temperature ramping rate [C/min]:',config['Tshelf']['ramp_rate']]) + writer.writerow( + ["Minimum chamber pressure [Torr]:", inputs["Pchamber"]["min"]] + ) + writer.writerow( + ["Maximum chamber pressure [Torr]:", inputs["Pchamber"]["max"]] + ) + writer.writerow([""]) + + if sim["tool"] == "Design-Space-Generator": + writer.writerow(["Intial shelf temperature [C]:", inputs["Tshelf"]["init"]]) + writer.writerow( + ["Shelf temperature set points [C]:", inputs["Tshelf"]["setpt"][:]] + ) + writer.writerow( + [ + "Shelf temperature ramping rate [C/min]:", + inputs["Tshelf"]["ramp_rate"], + ] + ) + elif not (sim["tool"] == "Optimizer" and sim["Variable_Tsh"] == "Y"): + for i in range(len(inputs["Tshelf"]["setpt"])): + writer.writerow( + [ + "Shelf temperature setpoint [C]:", + inputs["Tshelf"]["setpt"][i], + "Duration [min]:", + inputs["Tshelf"]["dt_setpt"][i], + ] + ) + writer.writerow( + [ + "Shelf temperature ramping rate [C/min]:", + inputs["Tshelf"]["ramp_rate"], + ] + ) else: - writer.writerow(['Minimum shelf temperature [C]:',config['Tshelf']['min']]) - writer.writerow(['Maximum shelf temperature [C]:',config['Tshelf']['max']]) - - writer.writerow(['Time Step [hr]', config['dt']]) - writer.writerow(['Equipment Parameter a [kg/hr]', config['eq_cap']['a']]) - writer.writerow(['Equipment Parameter b [kg/hr/Torr]', config['eq_cap']['b']]) - writer.writerow(['Number of Vials', config['nVial']]) - -def save_csv(output_data, config, timestamp): + writer.writerow(["Minimum shelf temperature [C]:", inputs["Tshelf"]["min"]]) + writer.writerow(["Maximum shelf temperature [C]:", inputs["Tshelf"]["max"]]) + + writer.writerow(["Time Step [hr]", inputs["dt"]]) + writer.writerow(["Equipment Parameter a [kg/hr]", inputs["eq_cap"]["a"]]) + writer.writerow(["Equipment Parameter b [kg/hr/Torr]", inputs["eq_cap"]["b"]]) + writer.writerow(["Number of Vials", inputs["nVial"]]) + + +def save_inputs(inputs, timestamp): + "Save inputs to a YAML file with timestamped filename." + try: + yamlfile = open("lyopronto_input_" + timestamp + ".yaml", "w") + yaml.dump(inputs, yamlfile) + finally: + yamlfile.close() + + +def read_inputs(filename): + "Read inputs from a YAML file." + try: + yamlfile = open(filename, "r") + inputs = yaml.load(yamlfile) + return inputs + finally: + yamlfile.close() + + +def save_csv(output_data, inputs, timestamp): """ Export simulation results to CSV file with appropriate formatting. """ - filename = f'lyopronto_output_{timestamp}.csv' + filename = f"lyopronto_output_{timestamp}.csv" + + sim = inputs["sim"] - sim = config['sim'] - - - if sim['tool'] == 'Freezing Calculator': + if sim["tool"] == "Freezing Calculator": assert output_data.shape[1] == 3 header = "Time [hr], Shelf Temp [°C], Product Temp [°C]" - np.savetxt(filename, output_data, delimiter=', ', header=header) - elif sim['tool'] == 'Design-Space-Generator': + np.savetxt(filename, output_data, delimiter=", ", header=header) + elif sim["tool"] == "Design-Space-Generator": assert output_data.shape[1] == 6 header = "Chamber Pressure [mTorr], Max Product Temperature [°C], Drying Time [hr], Avg Sublimation Flux [kg/hr/m²], Max/Min Sublimation Flux [kg/hr/m²], Final Sublimation Flux [kg/hr/m²]" ds_shelf, ds_pr, ds_eq_cap = output_data - Tshelf = config['Tshelf'] - Pchamber = config['Pchamber'] + Tshelf = inputs["Tshelf"] + Pchamber = inputs["Pchamber"] # TODO: This CSV has a weird format. Consider revising, or at least redoing as a few tables. try: - csvfile = open(filename, 'w') + csvfile = open(filename, "w") writer = csv.writer(csvfile) - writer.writerow(['Chamber Pressure [mTorr]','Maximum Product Temperature [C]','Drying Time [hr]','Average Sublimation Flux [kg/hr/m^2]','Maximum/Minimum Sublimation Flux [kg/hr/m^2]','Final Sublimation Flux [kg/hr/m^2]']) - for i in range(np.size(Tshelf['setpt'])): - writer.writerow(['Shelf Temperature = ',str(Tshelf['setpt'][i])]) - for j in range(np.size(Pchamber['setpt'])): - writer.writerow([Pchamber['setpt'][j]*constant.Torr_to_mTorr,ds_shelf[0,i,j],ds_shelf[1,i,j],ds_shelf[2,i,j],ds_shelf[3,i,j],ds_shelf[4,i,j]]) - writer.writerow(['Product Temperature = ',str(config['product']['T_pr_crit'])]) - writer.writerow([Pchamber['setpt'][0]*constant.Torr_to_mTorr,ds_pr[0,0],ds_pr[1,0],ds_pr[2,0],ds_pr[3,0],ds_pr[4,0]]) - writer.writerow([Pchamber['setpt'][-1]*constant.Torr_to_mTorr,ds_pr[0,1],ds_pr[1,1],ds_pr[2,1],ds_pr[3,1],ds_pr[4,1]]) - writer.writerow(['Equipment Capability']) - for k in range(np.size(Pchamber['setpt'])): - writer.writerow([Pchamber['setpt'][k]*constant.Torr_to_mTorr,ds_eq_cap[0,k],ds_eq_cap[1,k],ds_eq_cap[2,k],ds_eq_cap[2,k],ds_eq_cap[2,k]]) + writer.writerow( + [ + "Chamber Pressure [mTorr]", + "Maximum Product Temperature [C]", + "Drying Time [hr]", + "Average Sublimation Flux [kg/hr/m^2]", + "Maximum/Minimum Sublimation Flux [kg/hr/m^2]", + "Final Sublimation Flux [kg/hr/m^2]", + ] + ) + for i in range(np.size(Tshelf["setpt"])): + writer.writerow(["Shelf Temperature = ", str(Tshelf["setpt"][i])]) + for j in range(np.size(Pchamber["setpt"])): + writer.writerow( + [ + Pchamber["setpt"][j] * constant.Torr_to_mTorr, + ds_shelf[0, i, j], + ds_shelf[1, i, j], + ds_shelf[2, i, j], + ds_shelf[3, i, j], + ds_shelf[4, i, j], + ] + ) + writer.writerow( + ["Product Temperature = ", str(inputs["product"]["T_pr_crit"])] + ) + writer.writerow( + [ + Pchamber["setpt"][0] * constant.Torr_to_mTorr, + ds_pr[0, 0], + ds_pr[1, 0], + ds_pr[2, 0], + ds_pr[3, 0], + ds_pr[4, 0], + ] + ) + writer.writerow( + [ + Pchamber["setpt"][-1] * constant.Torr_to_mTorr, + ds_pr[0, 1], + ds_pr[1, 1], + ds_pr[2, 1], + ds_pr[3, 1], + ds_pr[4, 1], + ] + ) + writer.writerow(["Equipment Capability"]) + for k in range(np.size(Pchamber["setpt"])): + writer.writerow( + [ + Pchamber["setpt"][k] * constant.Torr_to_mTorr, + ds_eq_cap[0, k], + ds_eq_cap[1, k], + ds_eq_cap[2, k], + ds_eq_cap[2, k], + ds_eq_cap[2, k], + ] + ) finally: csvfile.close() else: - header =",".join([ - 'Time [hr]', - 'Sublimation Front Temp [°C]', - 'Vial Bottom Temperature [°C]', - 'Shelf Temp [°C]', - 'Chamber Pressure [mTorr]', - 'Sublimation Flux [kg/hr/m²]', - 'Percent Dried' - ]) - np.savetxt(filename, output_data, delimiter=', ', header=header) - -#TODO: add more kwargs, proper documentation, possibly refactor to make + header = ",".join( + [ + "Time [hr]", + "Sublimation Front Temp [°C]", + "Vial Bottom Temperature [°C]", + "Shelf Temp [°C]", + "Chamber Pressure [mTorr]", + "Sublimation Flux [kg/hr/m²]", + "Percent Dried", + ] + ) + np.savetxt(filename, output_data, delimiter=", ", header=header) + + +# TODO: add more kwargs, proper documentation, possibly refactor to make # each subfunction part of the API -def generate_visualizations(output_data, config, timestamp): +def generate_visualizations(output_data, inputs, timestamp): """ Create and save publication-quality plots based on simulation results. """ - #TODO: move these to kwargs for the function + # TODO: move these to kwargs for the function figure_props = { - 'figwidth': 30, - 'figheight': 20, - 'linewidth': 5, - 'marker_size': 20, + "figwidth": 30, + "figheight": 20, + "linewidth": 5, + "marker_size": 20, } - matplotlibrc('text.latex', preamble=r'\usepackage{color}') - matplotlibrc('text',usetex=False) - plt.rcParams['font.family'] = 'Arial' + matplotlibrc("text.latex", preamble=r"\usepackage{color}") + matplotlibrc("text", usetex=False) + plt.rcParams["font.family"] = "Arial" - if config['sim']['tool'] == 'Freezing Calculator': + if inputs["sim"]["tool"] == "Freezing Calculator": _plot_freezing_results(output_data, figure_props, timestamp) - elif config['sim']['tool'] in ['Primary Drying Calculator', 'Optimizer']: + elif inputs["sim"]["tool"] in ["Primary Drying Calculator", "Optimizer"]: _plot_drying_results(output_data, figure_props, timestamp) - elif config['sim']['tool'] == 'Design-Space-Generator': - _plot_design_space(output_data, config, figure_props, timestamp) + elif inputs["sim"]["tool"] == "Design-Space-Generator": + _plot_design_space(output_data, inputs, figure_props, timestamp) def _plot_freezing_results(data, props, timestamp): """Generate freezing process visualization.""" - fig, ax = plt.subplots(figsize=(props['figwidth'], props['figheight'])) - ax.plot(data[:, 0], data[:, 1], '-k', linewidth=props['linewidth'], label='Shelf Temperature') - ax.plot(data[:, 0], data[:, 2], '-b', linewidth=props['linewidth'], label='Product Temperature') - ax.set_xlabel('Time [hr]', fontsize=props['axis_fontsize'], fontweight='bold') - ax.set_ylabel('Temperature [°C]', fontsize=props['axis_fontsize'], fontweight='bold') - ax.legend(prop={'size': 40}) + fig, ax = plt.subplots(figsize=(props["figwidth"], props["figheight"])) + ax.plot( + data[:, 0], + data[:, 1], + "-k", + linewidth=props["linewidth"], + label="Shelf Temperature", + ) + ax.plot( + data[:, 0], + data[:, 2], + "-b", + linewidth=props["linewidth"], + label="Product Temperature", + ) + ax.set_xlabel("Time [hr]", fontsize=props["axis_fontsize"], fontweight="bold") + ax.set_ylabel( + "Temperature [°C]", fontsize=props["axis_fontsize"], fontweight="bold" + ) + ax.legend(prop={"size": 40}) plt.tight_layout() - plt.savefig(f'Temperatures_{timestamp}.pdf') + plt.savefig(f"Temperatures_{timestamp}.pdf") plt.close() def _plot_drying_results(data, props, timestamp): """Generate primary drying process visualizations.""" - figwidth = props['figwidth'] - figheight = props['figheight'] - linewidth = props['linewidth'] - marker_size = props['marker_size'] + figwidth = props["figwidth"] + figheight = props["figheight"] + linewidth = props["linewidth"] + marker_size = props["marker_size"] # Pressure and sublimation flux - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax1 = fig.add_subplot(1,1,1) + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax1 = fig.add_subplot(1, 1, 1) ax2 = ax1.twinx() - ax1.plot(data[:,0],data[:,4],'-o',color='b',markevery=5,linewidth=linewidth, markersize=marker_size, label = "Chamber Pressure") - ax2.plot(data[:,0],data[:,5],'-',color=[0,0.7,0.3],linewidth=linewidth, label = "Sublimation Flux") + ax1.plot( + data[:, 0], + data[:, 4], + "-o", + color="b", + markevery=5, + linewidth=linewidth, + markersize=marker_size, + label="Chamber Pressure", + ) + ax2.plot( + data[:, 0], + data[:, 5], + "-", + color=[0, 0.7, 0.3], + linewidth=linewidth, + label="Sublimation Flux", + ) plot_styling.axis_style_pressure(ax1) plot_styling.axis_style_subflux(ax2) plt.tight_layout() - plt.savefig(f'lyo_Pressure_SublimationFlux_{timestamp}.pdf') + plt.savefig(f"lyo_Pressure_SublimationFlux_{timestamp}.pdf") plt.close() - + # Drying progress - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) plot_styling.axis_style_percdried(ax) - ax.plot(data[:,0],data[:,-1],'-k',linewidth=linewidth, label = "Percent Dried") + ax.plot(data[:, 0], data[:, -1], "-k", linewidth=linewidth, label="Percent Dried") plt.tight_layout() - plt.savefig(f'lyo_DryingProgress_{timestamp}.pdf') + plt.savefig(f"lyo_DryingProgress_{timestamp}.pdf") plt.close() # Temperatures - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) plot_styling.axis_style_temperature(ax) - ax.plot(data[:,0],data[:,1],'-b',linewidth=linewidth, label = "Sublimation Front Temperature") - ax.plot(data[:,0],data[:,2],'-r',linewidth=linewidth, label = "Maximum Product Temperature") - ax.plot(data[:,0],data[:,3],'-o',color='k',markevery=5,linewidth=linewidth, markersize=marker_size, label = "Shelf Temperature") - plt.legend(fontsize=40,loc='best') - ll,ul = ax.get_ylim() - ax.set_ylim([ll,ul+5.0]) + ax.plot( + data[:, 0], + data[:, 1], + "-b", + linewidth=linewidth, + label="Sublimation Front Temperature", + ) + ax.plot( + data[:, 0], + data[:, 2], + "-r", + linewidth=linewidth, + label="Maximum Product Temperature", + ) + ax.plot( + data[:, 0], + data[:, 3], + "-o", + color="k", + markevery=5, + linewidth=linewidth, + markersize=marker_size, + label="Shelf Temperature", + ) + plt.legend(fontsize=40, loc="best") + ll, ul = ax.get_ylim() + ax.set_ylim([ll, ul + 5.0]) plt.tight_layout() plt.savefig(f"lyo_Temperatures_{timestamp}.pdf") plt.close() -#TODO: work through this logic and see how much can be refactored out -def _plot_design_space(data, config, props, timestamp): + +# TODO: work through this logic and see how much can be refactored out +def _plot_design_space(data, inputs, props, timestamp): """Generate design space boundary visualization.""" # Implementation for design space plotting ds_shelf, ds_pr, ds_eq_cap = data - Tshelf = config['Tshelf'] - Pchamber = config['Pchamber'] - figwidth = props['figwidth'] - figheight = props['figheight'] - lineWidth = props['linewidth'] - color_list = ['b','m','g','c','r','y','k'] # Line colors + Tshelf = inputs["Tshelf"] + Pchamber = inputs["Pchamber"] + figwidth = props["figwidth"] + figheight = props["figheight"] + lineWidth = props["linewidth"] + color_list = ["b", "m", "g", "c", "r", "y", "k"] # Line colors # Design space: sublimation flux vs pressures - x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr - y1 = ((ds_eq_cap[2,-1]-ds_eq_cap[2,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_eq_cap[2,0] # equipment capability sublimation flux in kg/hr/m^2 - y2 = ((ds_pr[3,-1]-ds_pr[3,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_pr[3,0] # product temperature limited sublimation flux in kg/hr/m^2 - x = x*constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1>=y2)[0][0] - y = np.append(y1[:i],y2[i:]) - x1 = np.append(x,x[::-1]) - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) + x = np.linspace( + np.min(Pchamber["setpt"]), np.max(Pchamber["setpt"]), 1000 + ) # pressure range in Torr + y1 = ( + (ds_eq_cap[2, -1] - ds_eq_cap[2, 0]) + / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) + ) * (x - Pchamber["setpt"][0]) + ds_eq_cap[ + 2, 0 + ] # equipment capability sublimation flux in kg/hr/m^2 + y2 = ( + (ds_pr[3, -1] - ds_pr[3, 0]) / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) + ) * (x - Pchamber["setpt"][0]) + ds_pr[ + 3, 0 + ] # product temperature limited sublimation flux in kg/hr/m^2 + x = x * constant.Torr_to_mTorr # pressure range in mTorr + i = np.where(y1 >= y2)[0][0] + y = np.append(y1[:i], y2[i:]) + x1 = np.append(x, x[::-1]) + + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) plt.axes(ax) - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_eq_cap[2,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") - ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[3,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(config['product']['T_pr_crit'])+"°C")) - for i in range(np.size(Tshelf['setpt'])): - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_shelf[3,i,:],'--',color=str(color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) + ax.plot( + [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + ds_eq_cap[2, :], + "-o", + color="k", + linewidth=lineWidth, + label="Equipment Capability", + ) + ax.plot( + [ + Pchamber["setpt"][0] * constant.Torr_to_mTorr, + Pchamber["setpt"][-1] * constant.Torr_to_mTorr, + ], + ds_pr[3, :], + "-o", + color="r", + linewidth=lineWidth, + label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + "°C"), + ) + for i in range(np.size(Tshelf["setpt"])): + ax.plot( + [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + ds_shelf[3, i, :], + "--", + color=str(color_list[i]), + linewidth=lineWidth, + label=("T$_{sh}$ = " + str(Tshelf["setpt"][i]) + " C"), + ) plot_styling.axis_style_designspace(ax) - plt.legend(prop={'size':40}) - ll,ul = ax.get_ylim() - if np.min(ds_eq_cap[2,:])>np.max(ds_pr[3,:]): - ul = (ds_eq_cap[2,0]+ds_eq_cap[2,1])/3 - elif np.min(ds_pr[3,:])>np.max(ds_eq_cap[2,:]): - ul = (ds_pr[3,0]+ds_pr[3,1])/4 - ax.set_ylim([ll,ul]) - x2 = np.append(y,ll*x/x) - ax.fill(x1,x2,color=[1.,1.,0.6]) + plt.legend(prop={"size": 40}) + ll, ul = ax.get_ylim() + if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): + ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 + elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): + ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + ax.set_ylim([ll, ul]) + x2 = np.append(y, ll * x / x) + ax.fill(x1, x2, color=[1.0, 1.0, 0.6]) plt.tight_layout() figure_name = f"lyo_DesignSpace_SublimationFlux_{timestamp}.pdf" plt.savefig(figure_name) - plt.close() + plt.close() # Drying progress vs pressures - - x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr - y1 = ((ds_eq_cap[1,-1]-ds_eq_cap[1,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_eq_cap[1,0] # equipment capability drying time in hr - y2 = ((ds_pr[1,-1]-ds_pr[1,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_pr[1,0] # product temperature limited drying time in hr - x = x*constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1np.max(ds_pr[3,:]): - ul = (ds_eq_cap[2,0]+ds_eq_cap[2,1])/3 - elif np.min(ds_pr[3,:])>np.max(ds_eq_cap[2,:]): - ul = (ds_pr[3,0]+ds_pr[3,1])/4 - ax.set_ylim([ll,ul]) - x2 = np.append(y,ul*x/x) - ax.fill(x1,x2,color=[1.,1.,0.6]) + ll, ul = ax.get_ylim() + if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): + ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 + elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): + ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + ax.set_ylim([ll, ul]) + x2 = np.append(y, ul * x / x) + ax.fill(x1, x2, color=[1.0, 1.0, 0.6]) figure_name = f"lyo_DesignSpace_DryingTime_{timestamp}.pdf" plt.tight_layout() plt.savefig(figure_name) - plt.close() + plt.close() # Product temperature vs pressures - x = np.linspace(np.min(Pchamber['setpt']),np.max(Pchamber['setpt']),1000) # pressure range in Torr - y1 = ((ds_eq_cap[0,-1]-ds_eq_cap[0,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_eq_cap[0,0] # equipment capability limiting product temperature in degC - y2 = ((ds_pr[0,-1]-ds_pr[0,0])/(Pchamber['setpt'][-1]-Pchamber['setpt'][0]))*(x-Pchamber['setpt'][0]) + ds_pr[0,0] # product temperature limit in deg C - x = x*constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1>=y2)[0][0] - y = np.append(y1[:i],y2[i:]) - x1 = np.append(x,x[::-1]) - - fig = plt.figure(0,figsize=(figwidth,figheight)) - ax = fig.add_subplot(1,1,1) + x = np.linspace( + np.min(Pchamber["setpt"]), np.max(Pchamber["setpt"]), 1000 + ) # pressure range in Torr + y1 = ( + (ds_eq_cap[0, -1] - ds_eq_cap[0, 0]) + / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) + ) * (x - Pchamber["setpt"][0]) + ds_eq_cap[ + 0, 0 + ] # equipment capability limiting product temperature in degC + y2 = ( + (ds_pr[0, -1] - ds_pr[0, 0]) / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) + ) * (x - Pchamber["setpt"][0]) + ds_pr[0, 0] # product temperature limit in deg C + x = x * constant.Torr_to_mTorr # pressure range in mTorr + i = np.where(y1 >= y2)[0][0] + y = np.append(y1[:i], y2[i:]) + x1 = np.append(x, x[::-1]) + + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) plt.axes(ax) - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_eq_cap[0,:],'-o',color='k',linewidth=lineWidth, label = "Equipment Capability") - ax.plot([Pchamber['setpt'][0]*constant.Torr_to_mTorr,Pchamber['setpt'][-1]*constant.Torr_to_mTorr],ds_pr[0,:],'-o',color='r',linewidth=lineWidth, label = ("T$_{pr}$ = "+str(config['product']['T_pr_crit'])+" C")) - for i in range(np.size(Tshelf['setpt'])): - ax.plot([P*constant.Torr_to_mTorr for P in Pchamber['setpt']],ds_shelf[0,i,:],'--',color=str(color_list[i]),linewidth=lineWidth, label = ("T$_{sh}$ = "+str(Tshelf['setpt'][i])+" C")) + ax.plot( + [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + ds_eq_cap[0, :], + "-o", + color="k", + linewidth=lineWidth, + label="Equipment Capability", + ) + ax.plot( + [ + Pchamber["setpt"][0] * constant.Torr_to_mTorr, + Pchamber["setpt"][-1] * constant.Torr_to_mTorr, + ], + ds_pr[0, :], + "-o", + color="r", + linewidth=lineWidth, + label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), + ) + for i in range(np.size(Tshelf["setpt"])): + ax.plot( + [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + ds_shelf[0, i, :], + "--", + color=str(color_list[i]), + linewidth=lineWidth, + label=("T$_{sh}$ = " + str(Tshelf["setpt"][i]) + " C"), + ) plot_styling.axis_style_ds_temperature(ax) - plt.legend(prop={'size':40}) + plt.legend(prop={"size": 40}) # The following seems incorrect: done for all three y axes, regardless of units - ll,ul = ax.get_ylim() - if np.min(ds_eq_cap[2,:])>np.max(ds_pr[3,:]): - ul = (ds_eq_cap[2,0]+ds_eq_cap[2,1])/3 - elif np.min(ds_pr[3,:])>np.max(ds_eq_cap[2,:]): - ul = (ds_pr[3,0]+ds_pr[3,1])/4 - ax.set_ylim([ll,ul]) - x2 = np.append(y,ll*x/x) - ax.fill(x1,x2,color=[1.,1.,0.6]) + ll, ul = ax.get_ylim() + if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): + ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 + elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): + ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + ax.set_ylim([ll, ul]) + x2 = np.append(y, ll * x / x) + ax.fill(x1, x2, color=[1.0, 1.0, 0.6]) figure_name = f"lyo_DesignSpace_ProductTemperature_{timestamp}.pdf" plt.tight_layout() plt.savefig(figure_name) - plt.close() \ No newline at end of file + plt.close() diff --git a/main.py b/main.py index f23b235..3da45d2 100644 --- a/main.py +++ b/main.py @@ -7,18 +7,19 @@ # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. - + # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. - + # You should have received a copy of the GNU General Public License # along with this program. If not, see . import sys import numpy as np + from lyopronto import * # from . import constant # from . import freezing @@ -30,57 +31,55 @@ # from . import opt_Tsh # from . import functions -import matplotlib.pyplot as plt -from matplotlib import rc as matplotlibrc import time -current_time = time.strftime("%y%m%d_%H%M",time.localtime()) +current_time = time.strftime("%y%m%d_%H%M", time.localtime()) ################################################################ ######################## Inputs ######################## # Simulation type -# 4 Tools available: 'Freezing Calculator', 'Primary Drying Calculator', 'Design-Space-Generator', 'Optimizer' +# 4 Tools available: 'Freezing Calculator', 'Primary Drying Calculator', 'Design Space Generator', 'Optimizer' # For 'Freezing Calculator': h_freezeing, Tpr0, Tf and Tn must be provided # No Variable Tsh - set point must be specified # For 'Primary Drying Calculator': If Kv and Rp are known, drying time can be determined # If drying time and Rp are known, Kv can be determined # If Kv and product temperature are known, Rp can be determined # No Variable Pch and Tsh - set points must be specified -# For 'Design-Space-Generator': Kv and Rp must be known, Tpr_crit must be provided +# For 'Design Space Generator': Kv and Rp must be known, Tpr_crit must be provided # No Variable Pch and Tsh - set points must be specified # For 'Optimizer': Kv and Rp must be known, Tpr_crit must be provided # Can use variable Pch and/or Tsh sim = { - 'tool': 'Primary Drying Calculator', - 'Kv_known': True, - 'Rp_known': True, - 'Variable_Pch': False, - 'Variable_Tsh': False + "tool": "Design Space Generator", + "Kv_known": True, + "Rp_known": True, + "Variable_Pch": False, + "Variable_Tsh": False, } # Vial and fill properties # Av = Vial area in cm^2 # Ap = Product Area in cm^2 # Vfill = Fill volume in mL -vial = {'Av': 3.80, 'Ap': 3.14, 'Vfill': 2.0} +vial = {"Av": 3.80, "Ap": 3.14, "Vfill": 2.0} -#Product properties +# Product properties # cSolid = Fractional concentration of solute in the frozen solution # Tpr0 = Initial product temperature for freezing in degC # Tf = Freezing temperature in degC # Tn = Nucleation temperature in degC # Product Resistance Parameters # R0 in cm^2-hr-Torr/g, A1 in cm-hr-Torr/g, A2 in 1/cm -if sim['tool'] == 'Freezing Calculator': - product = {'cSolid': 0.0, 'Tpr0': 15.8, 'Tf': -1.54, 'Tn': -5.84} -elif not(sim['tool'] == 'Primary Drying Calculator' and sim['Rp_known'] == 'N'): - product = {'cSolid': 0.05, 'R0': 1.4, 'A1': 16.0, 'A2': 0.0} +if sim["tool"] == "Freezing Calculator": + product = {"cSolid": 0.0, "Tpr0": 15.8, "Tf": -1.54, "Tn": -5.84} +elif not (sim["tool"] == "Primary Drying Calculator" and not sim["Rp_known"]): + product = {"cSolid": 0.05, "R0": 1.4, "A1": 16.0, "A2": 0.0} else: - product = {'cSolid': 0.05} + product = {"cSolid": 0.05} - product_temp_filename = './temperature.dat' + product_temp_filename = "./temperature.dat" exp_data = np.loadtxt(product_temp_filename) # Assumed: time in first column, temperature in second column # Change as necessary to match data file, but keep these names @@ -88,95 +87,113 @@ temp_data = exp_data[:, 1] # Critical product temperature # At least 2 to 3 deg C below collapse or glass transition temperature -product['T_pr_crit'] = -5 # in degC +product["T_pr_crit"] = -5 # in degC # Vial Heat Transfer Parameters -if sim['tool'] == 'Freezing Calculator': +if sim["tool"] == "Freezing Calculator": # Heat transfer coefficient between product and surroundings - h_freezing = 38.0 # in W/m^2/K -elif sim['Kv_known']: - # Kv = KC + KP*Pch/(1+KD*Pch) + h_freezing = 38.0 # in W/m^2/K +elif sim["Kv_known"]: + # Kv = KC + KP*Pch/(1+KD*Pch) # KC in cal/s/K/cm^2, KP in cal/s/K/cm^2/Torr, KD in 1/Torr - ht = {'KC': 2.75e-4, 'KP': 8.93e-4, 'KD': 0.46} -elif not sim['Kv_known']: - Kv_range = np.arange(10.6,10.8,0.01)*1e-4; # cal/s/K/cm^2 + ht = {"KC": 2.75e-4, "KP": 8.93e-4, "KD": 0.46} +elif not sim["Kv_known"]: + Kv_range = np.array([5.0, 20.0]) * 1e-4 # cal/s/K/cm^2, lower & upper bounds # Primary drying time - t_dry_exp = 12.62 # in hr + t_dry_exp = 12.62 # in hr else: print("Kv_known: Input not recognized") sys.exit(1) # Chamber Pressure -if sim['tool'] == 'Freezing Calculator': +if sim["tool"] == "Freezing Calculator": 0 -elif sim['tool'] == 'Design-Space-Generator': +elif sim["tool"] == "Design Space Generator": # Array of chamber pressure set points in Torr - Pchamber = {'setpt':[0.1,0.4,0.7,1.5]} -elif not(sim['tool'] == 'Optimizer' and sim['Variable_Pch']): + Pchamber = {"setpt": [0.1, 0.4, 0.7, 1.5]} +elif not (sim["tool"] == "Optimizer" and sim["Variable_Pch"]): # setpt = Chamber pressure set points in Torr # dt_setpt = Time for which chamber pressure set points are held in min # ramp_rate = Chamber pressure ramping rate in Torr/min - Pchamber = {'setpt':[0.15],'dt_setpt':[1800.0],'ramp_rate':0.5} + Pchamber = {"setpt": [0.15], "dt_setpt": [1800.0], "ramp_rate": 0.5} else: # Chamber pressure limits in Torr - Pchamber = {'min':0.05,'max':1000} + Pchamber = {"min": 0.05, "max": 1000} # Shelf Temperature -if sim['tool'] == 'Design-Space-Generator': +if sim["tool"] == "Design Space Generator": # Array of shelf temperature set points in C # ramp_rate = Shelf temperature ramping rate in C/min - Tshelf = {'init': -5.0, 'setpt': [-5, 0, 2, 5], 'ramp_rate': 1.0} -elif not (sim['tool'] == 'Optimizer' and sim['Variable_Tsh']): + Tshelf = {"init": -5.0, "setpt": [-5, 0, 2, 5], "ramp_rate": 1.0} +elif not (sim["tool"] == "Optimizer" and sim["Variable_Tsh"]): # init = Intial shelf temperature in C # setpt = Shelf temperature set points in C # dt_setpt = Time for which shelf temperature set points are held in min # ramp_rate = Shelf temperature ramping rate in C/min - Tshelf = {'init': -35.0, 'setpt': [20.0], 'dt_setpt': [1800.0], 'ramp_rate': 1.0} + Tshelf = {"init": -35.0, "setpt": [20.0], "dt_setpt": [1800.0], "ramp_rate": 1.0} else: # Shelf temperature limits in C - Tshelf = {'min': -45, 'max': 120} + Tshelf = {"min": -45, "max": 120} # Time step -dt = 0.01 # hr +dt = 0.01 # hr # Lyophilizer equipment capability # Form: dm/dt [kg/hr] = a + b * Pch [Torr] -# a in kg/hr, b in kg/hr/Torr -eq_cap = {'a': -0.182, 'b': 0.0117e3} +# a in kg/hr, b in kg/hr/Torr +eq_cap = {"a": -0.182, "b": 0.0117e3} # Equipment load -nVial = 398 # Number of vials +nVial = 398 # Number of vials -# Get all the inputs that are defined into a config dictionary -config = {} +############################################## +# Collect parameters into input dictionary + +# Get all the inputs that are defined into a input dictionary +inputs = {} loc = locals() -for key in ['sim', 'vial', 'product', 'ht', 'Pchamber', 'Tshelf', 'dt', 'eq_cap', 'nVial', - 'h_freezing', 't_dry_exp', 'Kv_range', 'time_data', 'temp_data']: +for key in [ + "sim", + "vial", + "product", + "ht", + "Pchamber", + "Tshelf", + "dt", + "eq_cap", + "nVial", + "h_freezing", + "t_dry_exp", + "Kv_range", + "time_data", + "temp_data", +]: if key in loc: - config[key] = loc[key] - -######################################################## + inputs[key] = loc[key] #################### Input file saved ################## # Write data to files -#save input_saved.csv -save_configuration_legacy(config, current_time) - +# Save to a .csv, old style +# save_inputs_legacy(inputs, current_time) + +# Save to a .yaml, new style +save_inputs(inputs, current_time) + ######################################################## ################### Execute ########################## -output_data = execute_simulation(config) +output_data = execute_simulation(inputs) ###################################################### - + ####################### Outputs ####################### # Write data to files -save_csv(output_data, config, current_time) +save_csv(output_data, inputs, current_time) # Plot data and save figures -generate_visualizations(output_data, config, current_time) \ No newline at end of file +generate_visualizations(output_data, inputs, current_time) From 33b2f7cb670cc9e10fbb078b081a7f51b43beba8 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Tue, 3 Feb 2026 14:45:44 -0500 Subject: [PATCH 09/31] Rename "config" to "inputs" --- lyopronto/calc_knownRp.py | 4 ++-- lyopronto/functions.py | 14 +++++++------- 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/lyopronto/calc_knownRp.py b/lyopronto/calc_knownRp.py index bdeba25..1e0e61e 100644 --- a/lyopronto/calc_knownRp.py +++ b/lyopronto/calc_knownRp.py @@ -65,7 +65,7 @@ def dry(vial,product,ht,Pchamber,Tshelf,dt): "setpoint(s). Drying cannot proceed.") return np.array([[0.0, Tsh_t(0), Tsh_t(0), Tsh_t(0), Pch_t(0), 0.0, 0.0]]) - config = (vial, product, ht, Pch_t, Tsh_t, dt, Lpr0) + inputs = (vial, product, ht, Pch_t, Tsh_t, dt, Lpr0) Lck0 = [0.0] T0 = Tsh_t(0) @@ -104,7 +104,7 @@ def finish(t, L): if sol.t[-1] == max_t:# and Lpr0 > sol.y[0, -1]: warn("Maximum simulation time (specified by Pchamber and Tshelf) reached before drying completion.") - output = functions.fill_output(sol, config) + output = functions.fill_output(sol, inputs) return output diff --git a/lyopronto/functions.py b/lyopronto/functions.py index d2fedfe..1b4a250 100644 --- a/lyopronto/functions.py +++ b/lyopronto/functions.py @@ -343,13 +343,13 @@ def resid(t): ################################################################ -def calc_step(t, Lck, config): +def calc_step(t, Lck, inputs): """Calculate the full set of system states at a given time step from ODE solution states. Args: t (float): The current time in hours. Lck (float): The cake thickness in cm. - config (tuple): A tuple containing the configuration parameters. + inputs (tuple): A tuple containing the inputs parameters. Returns: (np.ndarray): The full set of system states at the given time step: @@ -361,7 +361,7 @@ def calc_step(t, Lck, config): 5. Sublimation flux [kg/hr/m²], 6. Drying percent [%] """ - vial, product, ht, Pch_t, Tsh_t, dt, Lpr0 = config + vial, product, ht, Pch_t, Tsh_t, dt, Lpr0 = inputs Tsh = Tsh_t(t) Pch = Pch_t(t) Kv = Kv_FUN(ht['KC'],ht['KP'],ht['KD'],Pch) # Vial heat transfer coefficient in cal/s/K/cm^2 @@ -379,12 +379,12 @@ def calc_step(t, Lck, config): col = np.array([t, Tsub, Tbot, Tsh, Pch*constant.Torr_to_mTorr, dmdt/(vial['Ap']*constant.cm_To_m**2), dry_percent]) return col -def fill_output(sol, config): +def fill_output(sol, inputs): """Fill the output array with the results from the ODE solver. Args: sol (ODESolution): The solution object returned by the ODE solver. - config (tuple): A tuple containing the configuration parameters. + inputs (tuple): A tuple containing the input parameters. Returns: (np.ndarray): The output array filled with the results from the ODE solver. @@ -393,11 +393,11 @@ def fill_output(sol, config): of points is impractical. Instead, we calculate at the the ODE solver points, and interpolate elsewhere. """ - dt = config[5] + dt = inputs[5] interp_points = np.zeros((len(sol.t), 7)) for i,(t, y) in enumerate(zip(sol.t, sol.y[0])): - interp_points[i,:] = calc_step(t, y, config) + interp_points[i,:] = calc_step(t, y, inputs) # out_t = np.arange(0, sol.t[-1], dt) if dt is None: return interp_points From d0d0ded249e19f4f3c878c7aad46c825af348c73 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Tue, 3 Feb 2026 14:45:56 -0500 Subject: [PATCH 10/31] Make ruamel.yaml an outright dependency --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 171fde3..569bd9a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,6 +22,7 @@ dependencies = [ "numpy>=1.24.0", "scipy>=1.10.0", "matplotlib>=3.7.0", + "ruamel.yaml>=0.18.0", ] classifiers = [ "Development Status :: 4 - Beta", @@ -49,7 +50,6 @@ dev = [ "pandas>=2.0", "papermill>=2.6.0", "ipykernel>=6.15.0", - "ruamel.yaml>=0.18.0", ] docs = [ "mkdocstrings-python>=2", From 68a1cc2b8b3dd10a9cdbec8904b14276792db8cd Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Wed, 4 Feb 2026 16:48:21 -0500 Subject: [PATCH 11/31] Change some defaults --- main.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/main.py b/main.py index 3da45d2..25c19f7 100644 --- a/main.py +++ b/main.py @@ -101,16 +101,14 @@ Kv_range = np.array([5.0, 20.0]) * 1e-4 # cal/s/K/cm^2, lower & upper bounds # Primary drying time t_dry_exp = 12.62 # in hr -else: - print("Kv_known: Input not recognized") - sys.exit(1) # Chamber Pressure if sim["tool"] == "Freezing Calculator": 0 elif sim["tool"] == "Design Space Generator": # Array of chamber pressure set points in Torr - Pchamber = {"setpt": [0.1, 0.4, 0.7, 1.5]} + Pchamber = {"setpt": [0.02, 0.05, 0.1, 0.15]} + # Pchamber = {"setpt": [0.02, 0.03]} elif not (sim["tool"] == "Optimizer" and sim["Variable_Pch"]): # setpt = Chamber pressure set points in Torr # dt_setpt = Time for which chamber pressure set points are held in min @@ -124,7 +122,7 @@ if sim["tool"] == "Design Space Generator": # Array of shelf temperature set points in C # ramp_rate = Shelf temperature ramping rate in C/min - Tshelf = {"init": -5.0, "setpt": [-5, 0, 2, 5], "ramp_rate": 1.0} + Tshelf = {"init": -5.0, "setpt": [-15, 0, 30, 90], "ramp_rate": 1.0} elif not (sim["tool"] == "Optimizer" and sim["Variable_Tsh"]): # init = Intial shelf temperature in C # setpt = Shelf temperature set points in C From 3fdcc1dfe57cb4d8031c5f7d06e7ab8a86030380 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Wed, 4 Feb 2026 16:50:03 -0500 Subject: [PATCH 12/31] Improve clarity of tests, add docs stub for design space --- lyopronto/design_space.py | 31 +++++++++++++++++++++++++++++++ tests/test_design_space.py | 16 ++++------------ 2 files changed, 35 insertions(+), 12 deletions(-) diff --git a/lyopronto/design_space.py b/lyopronto/design_space.py index 55b546c..46d71e3 100644 --- a/lyopronto/design_space.py +++ b/lyopronto/design_space.py @@ -22,7 +22,38 @@ ################# Primary drying at fixed set points ############### +# TODO: docuemnt this properly def dry(vial,product,ht,Pchamber,Tshelf,dt,eq_cap,nVial): + """Compute quantities necessary for constructing a graphical design space. + + Args: + vial (dict): _description_ + product (dict): _description_ + ht (dict): _description_ + Pchamber (dict): _description_ + Tshelf (dict): _description_ + dt (float): _description_ + eq_cap (dict): _description_ + nVial (int): _description_ + + Returns: + ndarray: table of results for shelf isotherms + ndarray: table of results for product isotherms + ndarray: table of results for equipment capability curve + + Each of the returns has 5 rows corresponding to: + - Maximum product temperature in degC + - Primary drying time in hr + - Average sublimation flux in kg/hr/m^2 + - Maximum/minimum sublimation flux in kg/hr/m^2 + - Sublimation flux at the end of primary drying in kg/hr/m^2 + (noting that for equipment capability, average, maximum, and end sublimation fluxes are identical) + With nT setpoints in Tshelf['setpt'] and nP setpoints in Pchamber['setpt'], the returned arrays have the following shapes: + - Shelf isotherms: (5, nT, nP) array + - Product isotherms: (5, 2) array (for the lowest and highest Pchamber setpoints) + - Equipment capability curve: (3, nP) array + + """ T_max = np.zeros([np.size(Tshelf['setpt']),np.size(Pchamber['setpt'])]) drying_time = np.zeros([np.size(Tshelf['setpt']),np.size(Pchamber['setpt'])]) diff --git a/tests/test_design_space.py b/tests/test_design_space.py index fbf2d53..b73a60b 100644 --- a/tests/test_design_space.py +++ b/tests/test_design_space.py @@ -67,25 +67,17 @@ def check_shape(output, Pchamber, Tshelf): n_Tsh = len(Tshelf["setpt"]) n_Pch = len(Pchamber["setpt"]) - # Shelf results: 5 components, each with shape (n_Tsh, n_Pch) - assert len(shelf_results) == 5 # for each of (Tmax, drying_time, avg_flux, max_flux, end_flux), # there should be a value for each combination (n_Tsh x n_Pch) - for component in shelf_results: - assert component.shape == (n_Tsh, n_Pch) + assert shelf_results.shape == (5, n_Tsh, n_Pch) - # Product results: 2 values for each Pchamber - assert len(product_results) == 5 + # Product results: 2 values, for min and max Pchamber # for each of (T_product, drying_time, avg_flux, min_flux, end_flux), - # 2 values - for component in product_results: - assert component.shape == (2,) # 2 T_product values x n_Pch + assert product_results.shape == (5, 2) # Equipment capability results: 1 value per Pchamber - assert len(eq_cap_results) == 3 # for each of (Tmax, drying_time, flux), 1 value per Pch - for component in eq_cap_results: - assert component.shape == (n_Pch,) # n_Pch + assert eq_cap_results.shape == (3, n_Pch) class TestDesignSpaceBasic: From f1c84d590e322a671d62ae7b98927dd67694f3a1 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Wed, 4 Feb 2026 16:50:38 -0500 Subject: [PATCH 13/31] Overhaul the design space plots, including fixing some correctness bugs --- lyopronto/__init__.py | 325 ++++++++++++++++++-------------------- lyopronto/plot_styling.py | 20 +-- 2 files changed, 160 insertions(+), 185 deletions(-) diff --git a/lyopronto/__init__.py b/lyopronto/__init__.py index 7215e1a..882daa4 100644 --- a/lyopronto/__init__.py +++ b/lyopronto/__init__.py @@ -77,7 +77,7 @@ def execute_simulation(inputs): "With the current implementation, either Kv or Rp must be specified." ) - elif sim_type == "Design-Space-Generator": + elif sim_type == "Design Space Generator": output_data = design_space.dry( inputs["vial"], inputs["product"], @@ -230,7 +230,7 @@ def save_inputs_legacy(inputs, timestamp): if sim["tool"] == "Freezing Calculator": 0 - elif sim["tool"] == "Design-Space-Generator": + elif sim["tool"] == "Design Space Generator": writer.writerow( ["Chamber pressure set points [Torr]:", inputs["Pchamber"]["setpt"][:]] ) @@ -259,7 +259,7 @@ def save_inputs_legacy(inputs, timestamp): ) writer.writerow([""]) - if sim["tool"] == "Design-Space-Generator": + if sim["tool"] == "Design Space Generator": writer.writerow(["Intial shelf temperature [C]:", inputs["Tshelf"]["init"]]) writer.writerow( ["Shelf temperature set points [C]:", inputs["Tshelf"]["setpt"][:]] @@ -327,78 +327,8 @@ def save_csv(output_data, inputs, timestamp): assert output_data.shape[1] == 3 header = "Time [hr], Shelf Temp [°C], Product Temp [°C]" np.savetxt(filename, output_data, delimiter=", ", header=header) - elif sim["tool"] == "Design-Space-Generator": - assert output_data.shape[1] == 6 - header = "Chamber Pressure [mTorr], Max Product Temperature [°C], Drying Time [hr], Avg Sublimation Flux [kg/hr/m²], Max/Min Sublimation Flux [kg/hr/m²], Final Sublimation Flux [kg/hr/m²]" - ds_shelf, ds_pr, ds_eq_cap = output_data - Tshelf = inputs["Tshelf"] - Pchamber = inputs["Pchamber"] - - # TODO: This CSV has a weird format. Consider revising, or at least redoing as a few tables. - try: - csvfile = open(filename, "w") - writer = csv.writer(csvfile) - writer.writerow( - [ - "Chamber Pressure [mTorr]", - "Maximum Product Temperature [C]", - "Drying Time [hr]", - "Average Sublimation Flux [kg/hr/m^2]", - "Maximum/Minimum Sublimation Flux [kg/hr/m^2]", - "Final Sublimation Flux [kg/hr/m^2]", - ] - ) - for i in range(np.size(Tshelf["setpt"])): - writer.writerow(["Shelf Temperature = ", str(Tshelf["setpt"][i])]) - for j in range(np.size(Pchamber["setpt"])): - writer.writerow( - [ - Pchamber["setpt"][j] * constant.Torr_to_mTorr, - ds_shelf[0, i, j], - ds_shelf[1, i, j], - ds_shelf[2, i, j], - ds_shelf[3, i, j], - ds_shelf[4, i, j], - ] - ) - writer.writerow( - ["Product Temperature = ", str(inputs["product"]["T_pr_crit"])] - ) - writer.writerow( - [ - Pchamber["setpt"][0] * constant.Torr_to_mTorr, - ds_pr[0, 0], - ds_pr[1, 0], - ds_pr[2, 0], - ds_pr[3, 0], - ds_pr[4, 0], - ] - ) - writer.writerow( - [ - Pchamber["setpt"][-1] * constant.Torr_to_mTorr, - ds_pr[0, 1], - ds_pr[1, 1], - ds_pr[2, 1], - ds_pr[3, 1], - ds_pr[4, 1], - ] - ) - writer.writerow(["Equipment Capability"]) - for k in range(np.size(Pchamber["setpt"])): - writer.writerow( - [ - Pchamber["setpt"][k] * constant.Torr_to_mTorr, - ds_eq_cap[0, k], - ds_eq_cap[1, k], - ds_eq_cap[2, k], - ds_eq_cap[2, k], - ds_eq_cap[2, k], - ] - ) - finally: - csvfile.close() - + elif sim["tool"] == "Design Space Generator": + _write_design_space_csv(output_data, inputs, filename) else: header = ",".join( [ @@ -414,6 +344,67 @@ def save_csv(output_data, inputs, timestamp): np.savetxt(filename, output_data, delimiter=", ", header=header) +def _write_design_space_csv(data, inputs, filename): + ds_shelf, ds_pr, ds_eq_cap = data + Tshelf = inputs["Tshelf"] + Pchamber = inputs["Pchamber"] + + try: + csvfile = open(filename, "w", newline="") + writer = csv.writer(csvfile) + writer.writerow( + [ + "Chamber Pressure [mTorr]", + "Maximum Product Temperature [C]", + "Drying Time [hr]", + "Average Sublimation Flux [kg/hr/m^2]", + "Maximum/Minimum Sublimation Flux [kg/hr/m^2]", + "Final Sublimation Flux [kg/hr/m^2]", + ] + ) + for i in range(np.size(Tshelf["setpt"])): + writer.writerow(["Shelf Temperature = ", str(Tshelf["setpt"][i])]) + for j in range(np.size(Pchamber["setpt"])): + writer.writerow( + [ + Pchamber["setpt"][j] * constant.Torr_to_mTorr, + *ds_shelf[:, i, j], + ] + ) + writer.writerow( + ["Product Temperature = ", str(inputs["product"]["T_pr_crit"])] + ) + writer.writerow( + [Pchamber["setpt"][0] * constant.Torr_to_mTorr, *ds_pr[:, 0]] + ) + writer.writerow( + [Pchamber["setpt"][-1] * constant.Torr_to_mTorr, *ds_pr[:, 1]] + ) + writer.writerow(["Equipment Capability"]) + for k in range(np.size(Pchamber["setpt"])): + writer.writerow( + [ + Pchamber["setpt"][k] * constant.Torr_to_mTorr, + *ds_eq_cap[:, k], + ds_eq_cap[-1, k], + ds_eq_cap[-1, k], + ] + ) + finally: + csvfile.close() + + +# TODO: implement this after redesigning design space output API +# def _write_design_space_yaml(data, inputs, filename): +# ds_shelf, ds_pr, ds_eq_cap = data +# # ds_shelf: 5 x nTsh x nPch +# # ds_pr: 5 x 2 +# # ds_eq_cap: 3 x nPch + +# def _read_design_space_yaml(filename): +# """Read design space data from a YAML file.""" + + # TODO: add more kwargs, proper documentation, possibly refactor to make # each subfunction part of the API def generate_visualizations(output_data, inputs, timestamp): @@ -435,7 +426,7 @@ def generate_visualizations(output_data, inputs, timestamp): _plot_freezing_results(output_data, figure_props, timestamp) elif inputs["sim"]["tool"] in ["Primary Drying Calculator", "Optimizer"]: _plot_drying_results(output_data, figure_props, timestamp) - elif inputs["sim"]["tool"] == "Design-Space-Generator": + elif inputs["sim"]["tool"] == "Design Space Generator": _plot_design_space(output_data, inputs, figure_props, timestamp) @@ -554,106 +545,125 @@ def _plot_design_space(data, inputs, props, timestamp): # Implementation for design space plotting ds_shelf, ds_pr, ds_eq_cap = data - Tshelf = inputs["Tshelf"] - Pchamber = inputs["Pchamber"] + Tshelf = np.array(inputs["Tshelf"]["setpt"]) + Pchamber = np.array(inputs["Pchamber"]["setpt"]) + T_pr_crit = inputs["product"]["T_pr_crit"] figwidth = props["figwidth"] figheight = props["figheight"] lineWidth = props["linewidth"] color_list = ["b", "m", "g", "c", "r", "y", "k"] # Line colors + assert np.all(np.diff(Pchamber) >= 0), "Plotting assumes Pchamber set points are sorted." # Design space: sublimation flux vs pressures - x = np.linspace( - np.min(Pchamber["setpt"]), np.max(Pchamber["setpt"]), 1000 - ) # pressure range in Torr + # Range in pressure space, min to max, Torr + x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) + # Line 1: equipment capability sub flux, kg/hr/m^2 + # Indices (2,-1) is average sub flux at last Pch setpt, + # (2,0) is average sub flux at first Pch setpt + # Slope: (delta sub flux)/(delta pressure) + # Intercept: sub flux at first pressure y1 = ( (ds_eq_cap[2, -1] - ds_eq_cap[2, 0]) - / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) - ) * (x - Pchamber["setpt"][0]) + ds_eq_cap[ - 2, 0 - ] # equipment capability sublimation flux in kg/hr/m^2 + / (Pchamber[-1] - Pchamber[0]) + ) * (x - Pchamber[0]) + ds_eq_cap[2, 0] + # Line 2: product temperature limited sub flux, kg/hr/m^2 + # Indices (3, -1) is minimum sub flux at last setpt, + # (3,0) is minimum sub flux at first setpt + # Slope: (delta sub flux)/(delta pressure) + # Intercept: sub flux at first pressure y2 = ( - (ds_pr[3, -1] - ds_pr[3, 0]) / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) - ) * (x - Pchamber["setpt"][0]) + ds_pr[ - 3, 0 - ] # product temperature limited sublimation flux in kg/hr/m^2 - x = x * constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1 >= y2)[0][0] - y = np.append(y1[:i], y2[i:]) - x1 = np.append(x, x[::-1]) + (ds_pr[3, -1] - ds_pr[3, 0]) / (Pchamber[-1] - Pchamber[0]) + ) * (x - Pchamber[0]) + ds_pr[3, 0] + # Convert to mTorr for plotting + x = x * constant.Torr_to_mTorr + # Get whichever sub flux is lower at each x value + y = np.minimum(y1, y2) fig = plt.figure(0, figsize=(figwidth, figheight)) ax = fig.add_subplot(1, 1, 1) plt.axes(ax) + # Plot boundary lines + # Equipment capability line + # Fill the feasible region + ax.fill_between(x, y, color=[1.0, 1.0, 0.6]) + ax.plot( - [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + # x: pressure in mTorr + Pchamber * constant.Torr_to_mTorr, + # y: equipment capability average sub flux, for all Pch ds_eq_cap[2, :], "-o", color="k", linewidth=lineWidth, label="Equipment Capability", ) + # Product temperature isotherm + # Straight line: endpoints only enough ax.plot( - [ - Pchamber["setpt"][0] * constant.Torr_to_mTorr, - Pchamber["setpt"][-1] * constant.Torr_to_mTorr, - ], + # x: pressure in mTorr + Pchamber[[0, -1]] * constant.Torr_to_mTorr, + # y: product temperature limited minimum sub flux, for all first and last Pch ds_pr[3, :], "-o", color="r", linewidth=lineWidth, label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + "°C"), ) - for i in range(np.size(Tshelf["setpt"])): + # Shelf temperature isotherms + for i in range(Tshelf.size): ax.plot( - [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + # x: pressure in mTorr + Pchamber * constant.Torr_to_mTorr, + # y: 3 for maximum sub flux, i shelf temp , for all Pch ds_shelf[3, i, :], "--", color=str(color_list[i]), linewidth=lineWidth, - label=("T$_{sh}$ = " + str(Tshelf["setpt"][i]) + " C"), + label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), ) - plot_styling.axis_style_designspace(ax) + plot_styling.axis_style_designspace(ax, ylabel="Sublimation Flux [kg/hr/m$^2$]") plt.legend(prop={"size": 40}) ll, ul = ax.get_ylim() + # Adjust axis limits + # TODO: this logic seems questionable. What does it achieve? + # If minimum of eq cap average flux > maximum of pr limited min flux if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): + # Adjust upper limit to be 1/3 of first two eq cap average flux values ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 + # If instead minimum of pr limited min flux > maximum of eq cap average flux elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): + # Adjust upper limit to be 1/4 of first two pr limited min flux values ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + ll = max(0, ll) + # ul = np.max(y) * 1.2 # Consider: focus on feasible region ax.set_ylim([ll, ul]) - x2 = np.append(y, ll * x / x) - ax.fill(x1, x2, color=[1.0, 1.0, 0.6]) + # y part of bounding box: top of feasible region, then lower limit + # Use lower limit for lower box bound plt.tight_layout() figure_name = f"lyo_DesignSpace_SublimationFlux_{timestamp}.pdf" plt.savefig(figure_name) plt.close() - # Drying progress vs pressures + # Drying time vs pressures - x = np.linspace( - np.min(Pchamber["setpt"]), np.max(Pchamber["setpt"]), 1000 - ) # pressure range in Torr - y1 = ( - (ds_eq_cap[1, -1] - ds_eq_cap[1, 0]) - / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) - ) * (x - Pchamber["setpt"][0]) + ds_eq_cap[ - 1, 0 - ] # equipment capability drying time in hr - y2 = ( - (ds_pr[1, -1] - ds_pr[1, 0]) / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) - ) * (x - Pchamber["setpt"][0]) + ds_pr[ - 1, 0 - ] # product temperature limited drying time in hr - x = x * constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1 < y2)[0][0] - y = np.append(y1[:i], y2[i:]) - x1 = np.append(x, x[::-1]) + #### First, filled area above constraints + # TODO: this is wrong: doesn't actually match constraints + # Pressure range in Torr + x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) + # Line 1: drying time limited by equipment capability + y1 = np.interp(x, Pchamber, ds_eq_cap[1, :]) + # Line 2: drying time limited by product temperature + y2 = np.interp(x, Pchamber[[0, -1]], ds_pr[1, :]) + x = x * constant.Torr_to_mTorr # convert pressure range to mTorr + # get pointwise maximum of y1 and y2 + y = np.maximum(y1, y2) fig = plt.figure(0, figsize=(figwidth, figheight)) ax = fig.add_subplot(1, 1, 1) plt.axes(ax) ax.plot( - [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + Pchamber * constant.Torr_to_mTorr, ds_eq_cap[1, :], "-o", color="k", @@ -661,36 +671,29 @@ def _plot_design_space(data, inputs, props, timestamp): label="Equipment Capability", ) ax.plot( - [ - Pchamber["setpt"][0] * constant.Torr_to_mTorr, - Pchamber["setpt"][-1] * constant.Torr_to_mTorr, - ], + Pchamber[[0, -1]] * constant.Torr_to_mTorr, ds_pr[1, :], "-o", color="r", linewidth=lineWidth, label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), ) - for i in range(np.size(Tshelf["setpt"])): + for i in range(Tshelf.size): ax.plot( - [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + Pchamber * constant.Torr_to_mTorr, ds_shelf[1, i, :], "--", color=str(color_list[i]), linewidth=lineWidth, - label=("T$_{sh}$ = " + str(Tshelf["setpt"][i]) + " C"), + label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), ) - plot_styling.axis_style_ds_percdried(ax) + plot_styling.axis_style_designspace(ax, ylabel="Drying Time [hr]") plt.legend(prop={"size": 40}) # The following seems incorrect: done for all three y axes, regardless of units ll, ul = ax.get_ylim() - if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): - ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 - elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): - ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + ll = max(0, ll) ax.set_ylim([ll, ul]) - x2 = np.append(y, ul * x / x) - ax.fill(x1, x2, color=[1.0, 1.0, 0.6]) + ax.fill_between(x, y, ul, color=[1.0, 1.0, 0.6]) figure_name = f"lyo_DesignSpace_DryingTime_{timestamp}.pdf" plt.tight_layout() plt.savefig(figure_name) @@ -699,27 +702,21 @@ def _plot_design_space(data, inputs, props, timestamp): # Product temperature vs pressures x = np.linspace( - np.min(Pchamber["setpt"]), np.max(Pchamber["setpt"]), 1000 + np.min(Pchamber), np.max(Pchamber), 1000 ) # pressure range in Torr - y1 = ( - (ds_eq_cap[0, -1] - ds_eq_cap[0, 0]) - / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) - ) * (x - Pchamber["setpt"][0]) + ds_eq_cap[ - 0, 0 - ] # equipment capability limiting product temperature in degC - y2 = ( - (ds_pr[0, -1] - ds_pr[0, 0]) / (Pchamber["setpt"][-1] - Pchamber["setpt"][0]) - ) * (x - Pchamber["setpt"][0]) + ds_pr[0, 0] # product temperature limit in deg C - x = x * constant.Torr_to_mTorr # pressure range in mTorr - i = np.where(y1 >= y2)[0][0] - y = np.append(y1[:i], y2[i:]) - x1 = np.append(x, x[::-1]) + # Curve 1: equipment capability limited product temperature + y1 = np.interp(x, Pchamber, ds_eq_cap[0, :]) # equipment capability limiting product temperature in degC + # Curve 2: horizontal line at product temperature limit + y2 = np.full_like(y1, T_pr_crit) # horizontal line at product temperature limit + x = x * constant.Torr_to_mTorr # Convert pressure range to mTorr + # Pointwise minimum of y1 and y2 + y = np.minimum(y1, y2) fig = plt.figure(0, figsize=(figwidth, figheight)) ax = fig.add_subplot(1, 1, 1) plt.axes(ax) ax.plot( - [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + Pchamber * constant.Torr_to_mTorr, ds_eq_cap[0, :], "-o", color="k", @@ -727,36 +724,28 @@ def _plot_design_space(data, inputs, props, timestamp): label="Equipment Capability", ) ax.plot( - [ - Pchamber["setpt"][0] * constant.Torr_to_mTorr, - Pchamber["setpt"][-1] * constant.Torr_to_mTorr, - ], + Pchamber[[0, -1]] * constant.Torr_to_mTorr, ds_pr[0, :], "-o", color="r", linewidth=lineWidth, label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), ) - for i in range(np.size(Tshelf["setpt"])): + for i in range(np.size(Tshelf)): ax.plot( - [P * constant.Torr_to_mTorr for P in Pchamber["setpt"]], + Pchamber * constant.Torr_to_mTorr, ds_shelf[0, i, :], "--", color=str(color_list[i]), linewidth=lineWidth, - label=("T$_{sh}$ = " + str(Tshelf["setpt"][i]) + " C"), + label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), ) - plot_styling.axis_style_ds_temperature(ax) + plot_styling.axis_style_designspace(ax, ylabel="Product Temperature [°C]") plt.legend(prop={"size": 40}) - # The following seems incorrect: done for all three y axes, regardless of units ll, ul = ax.get_ylim() - if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): - ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 - elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): - ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + # TODO: Possibly tinker with ll and ul ax.set_ylim([ll, ul]) - x2 = np.append(y, ll * x / x) - ax.fill(x1, x2, color=[1.0, 1.0, 0.6]) + ax.fill_between(x, y, ll, color=[1.0, 1.0, 0.6]) figure_name = f"lyo_DesignSpace_ProductTemperature_{timestamp}.pdf" plt.tight_layout() plt.savefig(figure_name) diff --git a/lyopronto/plot_styling.py b/lyopronto/plot_styling.py index 10c0698..16953d2 100644 --- a/lyopronto/plot_styling.py +++ b/lyopronto/plot_styling.py @@ -70,25 +70,11 @@ def axis_style_temperature(ax, **kwargs): ax.set_ylabel("Product Temperature [°C]",fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) -def axis_style_designspace(ax,**kwargs): +def axis_style_designspace(ax, ylabel, **kwargs): """ Function to set styling for axes, with pressure on x and sublimation flux on y """ gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,**default_font_spec) - ax.set_ylabel("Sublimation Flux [kg/hr/m$^2$]",fontsize=gcafontSize,**default_font_spec) - axis_tick_styling(ax, **kwargs) - -def axis_style_ds_percdried(ax,**kwargs): - """ Function to set styling for axes, with chamber pressure on x and fraction dried on y """ - gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,**default_font_spec) - ax.set_ylabel("Fraction Dried",fontsize=gcafontSize,**default_font_spec) - axis_tick_styling(ax, **kwargs) - -def axis_style_ds_temperature(ax,**kwargs): - """ Function to set styling for axes, with chamber pressure on x and product temperature on y """ - gcafontSize = kwargs.get('gcafontSize',60) - ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,**default_font_spec) - ax.set_ylabel("Product Temperature [°C]",fontsize=gcafontSize,**default_font_spec) + ax.set_ylabel(ylabel,fontsize=gcafontSize,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_rp(ax, **kwargs): @@ -96,7 +82,7 @@ def axis_style_rp(ax, **kwargs): color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Dry Layer Height [cm]",fontsize=gcafontSize,**default_font_spec) - ax.set_ylabel('Product Resistance [cm$^2$ hr Torr/g]',fontsize=gcafontSize,color=color,**default_font_spec) + ax.set_ylabel("Product Resistance [cm$^2$ hr Torr/g]",fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) From 5ae0e7fcec45b3aa708b8563a2c398b2f119088b Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Wed, 4 Feb 2026 16:53:48 -0500 Subject: [PATCH 14/31] Minor cleanup --- lyopronto/__init__.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/lyopronto/__init__.py b/lyopronto/__init__.py index 882daa4..aa23eb9 100644 --- a/lyopronto/__init__.py +++ b/lyopronto/__init__.py @@ -585,8 +585,6 @@ def _plot_design_space(data, inputs, props, timestamp): plt.axes(ax) # Plot boundary lines # Equipment capability line - # Fill the feasible region - ax.fill_between(x, y, color=[1.0, 1.0, 0.6]) ax.plot( # x: pressure in mTorr @@ -636,10 +634,10 @@ def _plot_design_space(data, inputs, props, timestamp): # Adjust upper limit to be 1/4 of first two pr limited min flux values ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 ll = max(0, ll) + # Fill the feasible region + ax.fill_between(x, y, ll, color=[1.0, 1.0, 0.6]) # ul = np.max(y) * 1.2 # Consider: focus on feasible region ax.set_ylim([ll, ul]) - # y part of bounding box: top of feasible region, then lower limit - # Use lower limit for lower box bound plt.tight_layout() figure_name = f"lyo_DesignSpace_SublimationFlux_{timestamp}.pdf" plt.savefig(figure_name) @@ -655,13 +653,14 @@ def _plot_design_space(data, inputs, props, timestamp): y1 = np.interp(x, Pchamber, ds_eq_cap[1, :]) # Line 2: drying time limited by product temperature y2 = np.interp(x, Pchamber[[0, -1]], ds_pr[1, :]) - x = x * constant.Torr_to_mTorr # convert pressure range to mTorr # get pointwise maximum of y1 and y2 y = np.maximum(y1, y2) + x = x * constant.Torr_to_mTorr # convert pressure range to mTorr fig = plt.figure(0, figsize=(figwidth, figheight)) ax = fig.add_subplot(1, 1, 1) plt.axes(ax) + # Drying time boundary for eq cap ax.plot( Pchamber * constant.Torr_to_mTorr, ds_eq_cap[1, :], @@ -670,6 +669,7 @@ def _plot_design_space(data, inputs, props, timestamp): linewidth=lineWidth, label="Equipment Capability", ) + # Drying time boundary for product temperature ax.plot( Pchamber[[0, -1]] * constant.Torr_to_mTorr, ds_pr[1, :], @@ -678,6 +678,7 @@ def _plot_design_space(data, inputs, props, timestamp): linewidth=lineWidth, label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), ) + # Shelf temperature isotherms for i in range(Tshelf.size): ax.plot( Pchamber * constant.Torr_to_mTorr, @@ -689,7 +690,6 @@ def _plot_design_space(data, inputs, props, timestamp): ) plot_styling.axis_style_designspace(ax, ylabel="Drying Time [hr]") plt.legend(prop={"size": 40}) - # The following seems incorrect: done for all three y axes, regardless of units ll, ul = ax.get_ylim() ll = max(0, ll) ax.set_ylim([ll, ul]) @@ -708,9 +708,10 @@ def _plot_design_space(data, inputs, props, timestamp): y1 = np.interp(x, Pchamber, ds_eq_cap[0, :]) # equipment capability limiting product temperature in degC # Curve 2: horizontal line at product temperature limit y2 = np.full_like(y1, T_pr_crit) # horizontal line at product temperature limit + y = np.minimum(y1, y2) + x = x * constant.Torr_to_mTorr # Convert pressure range to mTorr # Pointwise minimum of y1 and y2 - y = np.minimum(y1, y2) fig = plt.figure(0, figsize=(figwidth, figheight)) ax = fig.add_subplot(1, 1, 1) From 0a620de14d20687ad36cd52baba2495abaab3659 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 6 Feb 2026 13:22:22 -0500 Subject: [PATCH 15/31] Move high-level API from __init__ to its own module, make available from wildcard import --- lyopronto/__init__.py | 750 ++-------------------------------------- lyopronto/high_level.py | 724 ++++++++++++++++++++++++++++++++++++++ 2 files changed, 751 insertions(+), 723 deletions(-) create mode 100644 lyopronto/high_level.py diff --git a/lyopronto/__init__.py b/lyopronto/__init__.py index aa23eb9..a5fe48a 100644 --- a/lyopronto/__init__.py +++ b/lyopronto/__init__.py @@ -28,726 +28,30 @@ from . import functions from . import plot_styling -# ---------------------- -# Provide functionality for running LyoPRONTO as a module -from warnings import warn -import numpy as np -import csv -import matplotlib.pyplot as plt -from matplotlib import rc as matplotlibrc -from scipy.optimize import curve_fit, brentq -from ruamel.yaml import YAML - -yaml = YAML() - - -def execute_simulation(inputs): - """ - Run the selected simulation tool with the provided inputs. - Returns output data based on the chosen simulation mode. - """ - sim_type = inputs["sim"]["tool"] - output_data = None - - if sim_type == "Freezing Calculator": - output_data = freezing.freeze( - inputs["vial"], - inputs["product"], - inputs["h_freezing"], - inputs["Tshelf"], - inputs["dt"], - ) - - elif sim_type == "Primary Drying Calculator": - if inputs["sim"]["Kv_known"] and inputs["sim"]["Rp_known"]: - output_data = calc_knownRp.dry( - inputs["vial"], - inputs["product"], - inputs["ht"], - inputs["Pchamber"], - inputs["Tshelf"], - inputs["dt"], - ) - elif not inputs["sim"]["Kv_known"] and inputs["sim"]["Rp_known"]: - output_data = _optimize_kv_parameter(inputs) - elif inputs["sim"]["Kv_known"] and not inputs["sim"]["Rp_known"]: - output_data = _optimize_rp_parameter(inputs) - else: - raise ValueError( - "With the current implementation, either Kv or Rp must be specified." - ) - - elif sim_type == "Design Space Generator": - output_data = design_space.dry( - inputs["vial"], - inputs["product"], - inputs["ht"], - inputs["Pchamber"], - inputs["Tshelf"], - inputs["dt"], - inputs["eq_cap"], - inputs["nVial"], - ) - - elif sim_type == "Optimizer": - output_data = _run_optimizer(inputs) - - return output_data - - -def _optimize_kv_parameter(inputs): - """Helper to determine Kv based on experimental drying time.""" - Kv_range = inputs.get("Kv_range", (1e-6, 1e-2)) - - def obj(Kc): - output = calc_knownRp.dry( - inputs["vial"], - inputs["product"], - {"KC": Kc, "KP": 0.0, "KD": 0.0}, - inputs["Pchamber"], - inputs["Tshelf"], - inputs["dt"], - ) - simulated_time = output[-1, 0] - return simulated_time - inputs["t_dry_exp"] - - if obj(Kv_range[0]) * obj(Kv_range[-1]) > 0: - warn( - "Given Kv bounds do not bracket the most likely value. Choosing either min or max." - ) - if abs(obj(Kv_range[0])) < abs(obj(Kv_range[-1])): - best_Kv = Kv_range[0] - else: - best_Kv = Kv_range[-1] - else: - best_Kv = brentq(obj, Kv_range[0], Kv_range[-1]) - - deviation = obj(best_Kv) - output = calc_knownRp.dry( - inputs["vial"], - inputs["product"], - {"KC": best_Kv, "KP": 0.0, "KD": 0.0}, - inputs["Pchamber"], - inputs["Tshelf"], - inputs["dt"], - ) - - print(f"Optimal Kv: {best_Kv}, Deviation: {deviation}%") - return output - - -def _optimize_rp_parameter(inputs): - """Helper to determine Rp from experimental product temperature.""" - - output, product_res = calc_unknownRp.dry( - inputs["vial"], - inputs["product"], - inputs["ht"], - inputs["Pchamber"], - inputs["Tshelf"], - inputs["time_data"], - inputs["temp_data"], - ) - - params, _ = curve_fit( - functions.Rp_FUN, product_res[:, 1], product_res[:, 2], p0=[1.0, 0.0, 0.0] - ) - - print(f"R0: {params[0]}, A1: {params[1]}, A2: {params[2]}") - return output - - -def _run_optimizer(inputs): - """Helper to run optimization with variable parameters.""" - args = ( - inputs["vial"], - inputs["product"], - inputs["ht"], - inputs["Pchamber"], - inputs["Tshelf"], - inputs["dt"], - inputs["eq_cap"], - inputs["nVial"], - ) - if inputs["sim"]["Variable_Pch"] and inputs["sim"]["Variable_Tsh"]: - return opt_Pch_Tsh.dry(*args) - elif inputs["sim"]["Variable_Pch"]: - return opt_Pch.dry(*args) - elif inputs["sim"]["Variable_Tsh"]: - return opt_Tsh.dry(*args) - - -def save_inputs_legacy(inputs, timestamp): - """ - Save inputs to a CSV file with timestamped filename. - """ - filename = f"lyopronto_input_{timestamp}.csv" - sim = inputs["sim"] - vial = inputs["vial"] - product = inputs["product"] - - with open(filename, "w", newline="") as csvfile: - writer = csv.writer(csvfile) - - writer.writerow(["Simulation Tool", sim["tool"]]) - writer.writerow(["Kv Known", sim["Kv_known"]]) - writer.writerow(["Rp Known", sim["Rp_known"]]) - writer.writerow(["Variable Chamber Pressure", sim["Variable_Pch"]]) - writer.writerow(["Variable Shelf Temperature", sim["Variable_Tsh"]]) - writer.writerow([]) - - writer.writerow(["Vial Cross-Section [cm²]", vial["Av"]]) - writer.writerow(["Product Area [cm²]", vial["Ap"]]) - writer.writerow(["Fill Volume [mL]", vial["Vfill"]]) - writer.writerow([]) - - writer.writerow(["Fractional solute concentration:", product["cSolid"]]) - if sim["tool"] == "Freezing Calculator": - writer.writerow(["Intial product temperature [C]:", product["Tpr0"]]) - writer.writerow(["Freezing temperature [C]:", product["Tf"]]) - writer.writerow(["Nucleation temperature [C]:", product["Tn"]]) - elif not ( - sim["tool"] == "Primary Drying Calculator" and sim["Rp_known"] == "N" - ): - writer.writerow(["R0 [cm^2-hr-Torr/g]:", product["R0"]]) - writer.writerow(["A1 [cm-hr-Torr/g]:", product["A1"]]) - writer.writerow(["A2 [1/cm]:", product["A2"]]) - if not ( - sim["tool"] == "Freezing Calculator" - and sim["tool"] == "Primary Drying Calculator" - ): - writer.writerow(["Critical product temperature [C]:", product["T_pr_crit"]]) - - if sim["tool"] == "Freezing Calculator": - writer.writerow(["h_freezing [W/m^2/K]:", inputs["h_freezing"]]) - elif sim["Kv_known"]: - writer.writerow(["KC [cal/s/K/cm^2]:", inputs["ht"]["KC"]]) - writer.writerow(["KP [cal/s/K/cm^2/Torr]:", inputs["ht"]["KP"]]) - writer.writerow(["KD [1/Torr]:", inputs["ht"]["KD"]]) - elif not sim["Kv_known"]: - writer.writerow(["Kv range [cal/s/K/cm^2]:", inputs["Kv_range"][:]]) - writer.writerow(["Experimental drying time [hr]:", inputs["t_dry_exp"]]) - - if sim["tool"] == "Freezing Calculator": - 0 - elif sim["tool"] == "Design Space Generator": - writer.writerow( - ["Chamber pressure set points [Torr]:", inputs["Pchamber"]["setpt"][:]] - ) - elif not (sim["tool"] == "Optimizer" and sim["Variable_Pch"] == "Y"): - for i in range(len(inputs["Pchamber"]["setpt"])): - writer.writerow( - [ - "Chamber pressure setpoint [Torr]:", - inputs["Pchamber"]["setpt"][i], - "Duration [min]:", - inputs["Pchamber"]["dt_setpt"][i], - ] - ) - writer.writerow( - [ - "Chamber pressure ramping rate [Torr/min]:", - inputs["Pchamber"]["ramp_rate"], - ] - ) - else: - writer.writerow( - ["Minimum chamber pressure [Torr]:", inputs["Pchamber"]["min"]] - ) - writer.writerow( - ["Maximum chamber pressure [Torr]:", inputs["Pchamber"]["max"]] - ) - writer.writerow([""]) - - if sim["tool"] == "Design Space Generator": - writer.writerow(["Intial shelf temperature [C]:", inputs["Tshelf"]["init"]]) - writer.writerow( - ["Shelf temperature set points [C]:", inputs["Tshelf"]["setpt"][:]] - ) - writer.writerow( - [ - "Shelf temperature ramping rate [C/min]:", - inputs["Tshelf"]["ramp_rate"], - ] - ) - elif not (sim["tool"] == "Optimizer" and sim["Variable_Tsh"] == "Y"): - for i in range(len(inputs["Tshelf"]["setpt"])): - writer.writerow( - [ - "Shelf temperature setpoint [C]:", - inputs["Tshelf"]["setpt"][i], - "Duration [min]:", - inputs["Tshelf"]["dt_setpt"][i], - ] - ) - writer.writerow( - [ - "Shelf temperature ramping rate [C/min]:", - inputs["Tshelf"]["ramp_rate"], - ] - ) - else: - writer.writerow(["Minimum shelf temperature [C]:", inputs["Tshelf"]["min"]]) - writer.writerow(["Maximum shelf temperature [C]:", inputs["Tshelf"]["max"]]) - - writer.writerow(["Time Step [hr]", inputs["dt"]]) - writer.writerow(["Equipment Parameter a [kg/hr]", inputs["eq_cap"]["a"]]) - writer.writerow(["Equipment Parameter b [kg/hr/Torr]", inputs["eq_cap"]["b"]]) - writer.writerow(["Number of Vials", inputs["nVial"]]) - - -def save_inputs(inputs, timestamp): - "Save inputs to a YAML file with timestamped filename." - try: - yamlfile = open("lyopronto_input_" + timestamp + ".yaml", "w") - yaml.dump(inputs, yamlfile) - finally: - yamlfile.close() - - -def read_inputs(filename): - "Read inputs from a YAML file." - try: - yamlfile = open(filename, "r") - inputs = yaml.load(yamlfile) - return inputs - finally: - yamlfile.close() - - -def save_csv(output_data, inputs, timestamp): - """ - Export simulation results to CSV file with appropriate formatting. - """ - filename = f"lyopronto_output_{timestamp}.csv" - - sim = inputs["sim"] - - if sim["tool"] == "Freezing Calculator": - assert output_data.shape[1] == 3 - header = "Time [hr], Shelf Temp [°C], Product Temp [°C]" - np.savetxt(filename, output_data, delimiter=", ", header=header) - elif sim["tool"] == "Design Space Generator": - _write_design_space_csv(output_data, inputs, filename) - else: - header = ",".join( - [ - "Time [hr]", - "Sublimation Front Temp [°C]", - "Vial Bottom Temperature [°C]", - "Shelf Temp [°C]", - "Chamber Pressure [mTorr]", - "Sublimation Flux [kg/hr/m²]", - "Percent Dried", - ] - ) - np.savetxt(filename, output_data, delimiter=", ", header=header) - - -def _write_design_space_csv(data, inputs, filename): - ds_shelf, ds_pr, ds_eq_cap = data - Tshelf = inputs["Tshelf"] - Pchamber = inputs["Pchamber"] - - try: - csvfile = open(filename, "w", newline="") - writer = csv.writer(csvfile) - writer.writerow( - [ - "Chamber Pressure [mTorr]", - "Maximum Product Temperature [C]", - "Drying Time [hr]", - "Average Sublimation Flux [kg/hr/m^2]", - "Maximum/Minimum Sublimation Flux [kg/hr/m^2]", - "Final Sublimation Flux [kg/hr/m^2]", - ] - ) - for i in range(np.size(Tshelf["setpt"])): - writer.writerow(["Shelf Temperature = ", str(Tshelf["setpt"][i])]) - for j in range(np.size(Pchamber["setpt"])): - writer.writerow( - [ - Pchamber["setpt"][j] * constant.Torr_to_mTorr, - *ds_shelf[:, i, j], - ] - ) - writer.writerow( - ["Product Temperature = ", str(inputs["product"]["T_pr_crit"])] - ) - writer.writerow( - [Pchamber["setpt"][0] * constant.Torr_to_mTorr, *ds_pr[:, 0]] - ) - writer.writerow( - [Pchamber["setpt"][-1] * constant.Torr_to_mTorr, *ds_pr[:, 1]] - ) - writer.writerow(["Equipment Capability"]) - for k in range(np.size(Pchamber["setpt"])): - writer.writerow( - [ - Pchamber["setpt"][k] * constant.Torr_to_mTorr, - *ds_eq_cap[:, k], - ds_eq_cap[-1, k], - ds_eq_cap[-1, k], - ] - ) - finally: - csvfile.close() - - -# TODO: implement this after redesigning design space output API -# def _write_design_space_yaml(data, inputs, filename): -# ds_shelf, ds_pr, ds_eq_cap = data -# # ds_shelf: 5 x nTsh x nPch -# # ds_pr: 5 x 2 -# # ds_eq_cap: 3 x nPch - -# def _read_design_space_yaml(filename): -# """Read design space data from a YAML file.""" - - -# TODO: add more kwargs, proper documentation, possibly refactor to make -# each subfunction part of the API -def generate_visualizations(output_data, inputs, timestamp): - """ - Create and save publication-quality plots based on simulation results. - """ - # TODO: move these to kwargs for the function - figure_props = { - "figwidth": 30, - "figheight": 20, - "linewidth": 5, - "marker_size": 20, - } - matplotlibrc("text.latex", preamble=r"\usepackage{color}") - matplotlibrc("text", usetex=False) - plt.rcParams["font.family"] = "Arial" - - if inputs["sim"]["tool"] == "Freezing Calculator": - _plot_freezing_results(output_data, figure_props, timestamp) - elif inputs["sim"]["tool"] in ["Primary Drying Calculator", "Optimizer"]: - _plot_drying_results(output_data, figure_props, timestamp) - elif inputs["sim"]["tool"] == "Design Space Generator": - _plot_design_space(output_data, inputs, figure_props, timestamp) - - -def _plot_freezing_results(data, props, timestamp): - """Generate freezing process visualization.""" - fig, ax = plt.subplots(figsize=(props["figwidth"], props["figheight"])) - ax.plot( - data[:, 0], - data[:, 1], - "-k", - linewidth=props["linewidth"], - label="Shelf Temperature", - ) - ax.plot( - data[:, 0], - data[:, 2], - "-b", - linewidth=props["linewidth"], - label="Product Temperature", - ) - ax.set_xlabel("Time [hr]", fontsize=props["axis_fontsize"], fontweight="bold") - ax.set_ylabel( - "Temperature [°C]", fontsize=props["axis_fontsize"], fontweight="bold" - ) - ax.legend(prop={"size": 40}) - plt.tight_layout() - plt.savefig(f"Temperatures_{timestamp}.pdf") - plt.close() - - -def _plot_drying_results(data, props, timestamp): - """Generate primary drying process visualizations.""" - - figwidth = props["figwidth"] - figheight = props["figheight"] - linewidth = props["linewidth"] - marker_size = props["marker_size"] - # Pressure and sublimation flux - fig = plt.figure(0, figsize=(figwidth, figheight)) - ax1 = fig.add_subplot(1, 1, 1) - ax2 = ax1.twinx() - ax1.plot( - data[:, 0], - data[:, 4], - "-o", - color="b", - markevery=5, - linewidth=linewidth, - markersize=marker_size, - label="Chamber Pressure", - ) - ax2.plot( - data[:, 0], - data[:, 5], - "-", - color=[0, 0.7, 0.3], - linewidth=linewidth, - label="Sublimation Flux", - ) - - plot_styling.axis_style_pressure(ax1) - plot_styling.axis_style_subflux(ax2) - - plt.tight_layout() - plt.savefig(f"lyo_Pressure_SublimationFlux_{timestamp}.pdf") - plt.close() - - # Drying progress - fig = plt.figure(0, figsize=(figwidth, figheight)) - ax = fig.add_subplot(1, 1, 1) - plot_styling.axis_style_percdried(ax) - ax.plot(data[:, 0], data[:, -1], "-k", linewidth=linewidth, label="Percent Dried") - plt.tight_layout() - plt.savefig(f"lyo_DryingProgress_{timestamp}.pdf") - plt.close() - - # Temperatures - fig = plt.figure(0, figsize=(figwidth, figheight)) - ax = fig.add_subplot(1, 1, 1) - plot_styling.axis_style_temperature(ax) - ax.plot( - data[:, 0], - data[:, 1], - "-b", - linewidth=linewidth, - label="Sublimation Front Temperature", - ) - ax.plot( - data[:, 0], - data[:, 2], - "-r", - linewidth=linewidth, - label="Maximum Product Temperature", - ) - ax.plot( - data[:, 0], - data[:, 3], - "-o", - color="k", - markevery=5, - linewidth=linewidth, - markersize=marker_size, - label="Shelf Temperature", - ) - plt.legend(fontsize=40, loc="best") - ll, ul = ax.get_ylim() - ax.set_ylim([ll, ul + 5.0]) - plt.tight_layout() - plt.savefig(f"lyo_Temperatures_{timestamp}.pdf") - plt.close() - - -# TODO: work through this logic and see how much can be refactored out -def _plot_design_space(data, inputs, props, timestamp): - """Generate design space boundary visualization.""" - # Implementation for design space plotting - - ds_shelf, ds_pr, ds_eq_cap = data - Tshelf = np.array(inputs["Tshelf"]["setpt"]) - Pchamber = np.array(inputs["Pchamber"]["setpt"]) - T_pr_crit = inputs["product"]["T_pr_crit"] - figwidth = props["figwidth"] - figheight = props["figheight"] - lineWidth = props["linewidth"] - color_list = ["b", "m", "g", "c", "r", "y", "k"] # Line colors - - assert np.all(np.diff(Pchamber) >= 0), "Plotting assumes Pchamber set points are sorted." - # Design space: sublimation flux vs pressures - - # Range in pressure space, min to max, Torr - x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) - # Line 1: equipment capability sub flux, kg/hr/m^2 - # Indices (2,-1) is average sub flux at last Pch setpt, - # (2,0) is average sub flux at first Pch setpt - # Slope: (delta sub flux)/(delta pressure) - # Intercept: sub flux at first pressure - y1 = ( - (ds_eq_cap[2, -1] - ds_eq_cap[2, 0]) - / (Pchamber[-1] - Pchamber[0]) - ) * (x - Pchamber[0]) + ds_eq_cap[2, 0] - # Line 2: product temperature limited sub flux, kg/hr/m^2 - # Indices (3, -1) is minimum sub flux at last setpt, - # (3,0) is minimum sub flux at first setpt - # Slope: (delta sub flux)/(delta pressure) - # Intercept: sub flux at first pressure - y2 = ( - (ds_pr[3, -1] - ds_pr[3, 0]) / (Pchamber[-1] - Pchamber[0]) - ) * (x - Pchamber[0]) + ds_pr[3, 0] - # Convert to mTorr for plotting - x = x * constant.Torr_to_mTorr - # Get whichever sub flux is lower at each x value - y = np.minimum(y1, y2) - - fig = plt.figure(0, figsize=(figwidth, figheight)) - ax = fig.add_subplot(1, 1, 1) - plt.axes(ax) - # Plot boundary lines - # Equipment capability line - - ax.plot( - # x: pressure in mTorr - Pchamber * constant.Torr_to_mTorr, - # y: equipment capability average sub flux, for all Pch - ds_eq_cap[2, :], - "-o", - color="k", - linewidth=lineWidth, - label="Equipment Capability", - ) - # Product temperature isotherm - # Straight line: endpoints only enough - ax.plot( - # x: pressure in mTorr - Pchamber[[0, -1]] * constant.Torr_to_mTorr, - # y: product temperature limited minimum sub flux, for all first and last Pch - ds_pr[3, :], - "-o", - color="r", - linewidth=lineWidth, - label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + "°C"), - ) - # Shelf temperature isotherms - for i in range(Tshelf.size): - ax.plot( - # x: pressure in mTorr - Pchamber * constant.Torr_to_mTorr, - # y: 3 for maximum sub flux, i shelf temp , for all Pch - ds_shelf[3, i, :], - "--", - color=str(color_list[i]), - linewidth=lineWidth, - label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), - ) - plot_styling.axis_style_designspace(ax, ylabel="Sublimation Flux [kg/hr/m$^2$]") - plt.legend(prop={"size": 40}) - ll, ul = ax.get_ylim() - # Adjust axis limits - # TODO: this logic seems questionable. What does it achieve? - # If minimum of eq cap average flux > maximum of pr limited min flux - if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): - # Adjust upper limit to be 1/3 of first two eq cap average flux values - ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 - # If instead minimum of pr limited min flux > maximum of eq cap average flux - elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): - # Adjust upper limit to be 1/4 of first two pr limited min flux values - ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 - ll = max(0, ll) - # Fill the feasible region - ax.fill_between(x, y, ll, color=[1.0, 1.0, 0.6]) - # ul = np.max(y) * 1.2 # Consider: focus on feasible region - ax.set_ylim([ll, ul]) - plt.tight_layout() - figure_name = f"lyo_DesignSpace_SublimationFlux_{timestamp}.pdf" - plt.savefig(figure_name) - plt.close() - - # Drying time vs pressures - - #### First, filled area above constraints - # TODO: this is wrong: doesn't actually match constraints - # Pressure range in Torr - x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) - # Line 1: drying time limited by equipment capability - y1 = np.interp(x, Pchamber, ds_eq_cap[1, :]) - # Line 2: drying time limited by product temperature - y2 = np.interp(x, Pchamber[[0, -1]], ds_pr[1, :]) - # get pointwise maximum of y1 and y2 - y = np.maximum(y1, y2) - x = x * constant.Torr_to_mTorr # convert pressure range to mTorr - - fig = plt.figure(0, figsize=(figwidth, figheight)) - ax = fig.add_subplot(1, 1, 1) - plt.axes(ax) - # Drying time boundary for eq cap - ax.plot( - Pchamber * constant.Torr_to_mTorr, - ds_eq_cap[1, :], - "-o", - color="k", - linewidth=lineWidth, - label="Equipment Capability", - ) - # Drying time boundary for product temperature - ax.plot( - Pchamber[[0, -1]] * constant.Torr_to_mTorr, - ds_pr[1, :], - "-o", - color="r", - linewidth=lineWidth, - label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), - ) - # Shelf temperature isotherms - for i in range(Tshelf.size): - ax.plot( - Pchamber * constant.Torr_to_mTorr, - ds_shelf[1, i, :], - "--", - color=str(color_list[i]), - linewidth=lineWidth, - label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), - ) - plot_styling.axis_style_designspace(ax, ylabel="Drying Time [hr]") - plt.legend(prop={"size": 40}) - ll, ul = ax.get_ylim() - ll = max(0, ll) - ax.set_ylim([ll, ul]) - ax.fill_between(x, y, ul, color=[1.0, 1.0, 0.6]) - figure_name = f"lyo_DesignSpace_DryingTime_{timestamp}.pdf" - plt.tight_layout() - plt.savefig(figure_name) - plt.close() - - # Product temperature vs pressures - - x = np.linspace( - np.min(Pchamber), np.max(Pchamber), 1000 - ) # pressure range in Torr - # Curve 1: equipment capability limited product temperature - y1 = np.interp(x, Pchamber, ds_eq_cap[0, :]) # equipment capability limiting product temperature in degC - # Curve 2: horizontal line at product temperature limit - y2 = np.full_like(y1, T_pr_crit) # horizontal line at product temperature limit - y = np.minimum(y1, y2) - - x = x * constant.Torr_to_mTorr # Convert pressure range to mTorr - # Pointwise minimum of y1 and y2 - - fig = plt.figure(0, figsize=(figwidth, figheight)) - ax = fig.add_subplot(1, 1, 1) - plt.axes(ax) - ax.plot( - Pchamber * constant.Torr_to_mTorr, - ds_eq_cap[0, :], - "-o", - color="k", - linewidth=lineWidth, - label="Equipment Capability", - ) - ax.plot( - Pchamber[[0, -1]] * constant.Torr_to_mTorr, - ds_pr[0, :], - "-o", - color="r", - linewidth=lineWidth, - label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), - ) - for i in range(np.size(Tshelf)): - ax.plot( - Pchamber * constant.Torr_to_mTorr, - ds_shelf[0, i, :], - "--", - color=str(color_list[i]), - linewidth=lineWidth, - label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), - ) - plot_styling.axis_style_designspace(ax, ylabel="Product Temperature [°C]") - plt.legend(prop={"size": 40}) - ll, ul = ax.get_ylim() - # TODO: Possibly tinker with ll and ul - ax.set_ylim([ll, ul]) - ax.fill_between(x, y, ll, color=[1.0, 1.0, 0.6]) - figure_name = f"lyo_DesignSpace_ProductTemperature_{timestamp}.pdf" - plt.tight_layout() - plt.savefig(figure_name) - plt.close() +from .high_level import ( + execute_simulation, + save_inputs_legacy, + save_inputs, + read_inputs, + save_csv, + generate_visualizations, +) + +__all__ = [ + "constant", + "freezing", + "calc_knownRp", + "calc_unknownRp", + "design_space", + "opt_Pch_Tsh", + "opt_Pch", + "opt_Tsh", + "functions", + "plot_styling", + "execute_simulation", + "save_inputs_legacy", + "save_inputs", + "read_inputs", + "save_csv", + "generate_visualizations", +] \ No newline at end of file diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py new file mode 100644 index 0000000..1945bfa --- /dev/null +++ b/lyopronto/high_level.py @@ -0,0 +1,724 @@ +from . import freezing, calc_knownRp, calc_unknownRp, design_space, opt_Pch_Tsh, opt_Pch, opt_Tsh +from . import functions, constant, plot_styling + +from warnings import warn +import numpy as np +import csv +import matplotlib.pyplot as plt +from matplotlib import rc as matplotlibrc +from scipy.optimize import curve_fit, brentq +from ruamel.yaml import YAML + +yaml = YAML() + + +def execute_simulation(inputs): + """ + Run the selected simulation tool with the provided inputs. + Returns output data based on the chosen simulation mode. + """ + sim_type = inputs["sim"]["tool"] + output_data = None + + if sim_type == "Freezing Calculator": + output_data = freezing.freeze( + inputs["vial"], + inputs["product"], + inputs["h_freezing"], + inputs["Tshelf"], + inputs["dt"], + ) + + elif sim_type == "Primary Drying Calculator": + if inputs["sim"]["Kv_known"] and inputs["sim"]["Rp_known"]: + output_data = calc_knownRp.dry( + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + ) + elif not inputs["sim"]["Kv_known"] and inputs["sim"]["Rp_known"]: + output_data = _optimize_kv_parameter(inputs) + elif inputs["sim"]["Kv_known"] and not inputs["sim"]["Rp_known"]: + output_data = _optimize_rp_parameter(inputs) + else: + raise ValueError( + "With the current implementation, either Kv or Rp must be specified." + ) + + elif sim_type == "Design Space Generator": + output_data = design_space.dry( + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + inputs["eq_cap"], + inputs["nVial"], + ) + + elif sim_type == "Optimizer": + output_data = _run_optimizer(inputs) + + return output_data + + +def _optimize_kv_parameter(inputs): + """Helper to determine Kv based on experimental drying time.""" + Kv_range = inputs.get("Kv_range", (1e-6, 1e-2)) + + def obj(Kc): + output = calc_knownRp.dry( + inputs["vial"], + inputs["product"], + {"KC": Kc, "KP": 0.0, "KD": 0.0}, + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + ) + simulated_time = output[-1, 0] + return simulated_time - inputs["t_dry_exp"] + + if obj(Kv_range[0]) * obj(Kv_range[-1]) > 0: + warn( + "Given Kv bounds do not bracket the most likely value. Choosing either min or max." + ) + if abs(obj(Kv_range[0])) < abs(obj(Kv_range[-1])): + best_Kv = Kv_range[0] + else: + best_Kv = Kv_range[-1] + else: + best_Kv = brentq(obj, Kv_range[0], Kv_range[-1]) + + deviation = obj(best_Kv) + output = calc_knownRp.dry( + inputs["vial"], + inputs["product"], + {"KC": best_Kv, "KP": 0.0, "KD": 0.0}, + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + ) + + print(f"Optimal Kv: {best_Kv}, Deviation: {deviation}%") + return output + + +def _optimize_rp_parameter(inputs): + """Helper to determine Rp from experimental product temperature.""" + + output, product_res = calc_unknownRp.dry( + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["time_data"], + inputs["temp_data"], + ) + + params, _ = curve_fit( + functions.Rp_FUN, product_res[:, 1], product_res[:, 2], p0=[1.0, 0.0, 0.0] + ) + + print(f"R0: {params[0]}, A1: {params[1]}, A2: {params[2]}") + return output + + +def _run_optimizer(inputs): + """Helper to run optimization with variable parameters.""" + args = ( + inputs["vial"], + inputs["product"], + inputs["ht"], + inputs["Pchamber"], + inputs["Tshelf"], + inputs["dt"], + inputs["eq_cap"], + inputs["nVial"], + ) + if inputs["sim"]["Variable_Pch"] and inputs["sim"]["Variable_Tsh"]: + return opt_Pch_Tsh.dry(*args) + elif inputs["sim"]["Variable_Pch"]: + return opt_Pch.dry(*args) + elif inputs["sim"]["Variable_Tsh"]: + return opt_Tsh.dry(*args) + + +def save_inputs_legacy(inputs, timestamp): + """ + Save inputs to a CSV file with timestamped filename. + """ + filename = f"lyopronto_input_{timestamp}.csv" + sim = inputs["sim"] + vial = inputs["vial"] + product = inputs["product"] + + with open(filename, "w", newline="") as csvfile: + writer = csv.writer(csvfile) + + writer.writerow(["Simulation Tool", sim["tool"]]) + writer.writerow(["Kv Known", sim["Kv_known"]]) + writer.writerow(["Rp Known", sim["Rp_known"]]) + writer.writerow(["Variable Chamber Pressure", sim["Variable_Pch"]]) + writer.writerow(["Variable Shelf Temperature", sim["Variable_Tsh"]]) + writer.writerow([]) + + writer.writerow(["Vial Cross-Section [cm²]", vial["Av"]]) + writer.writerow(["Product Area [cm²]", vial["Ap"]]) + writer.writerow(["Fill Volume [mL]", vial["Vfill"]]) + writer.writerow([]) + + writer.writerow(["Fractional solute concentration:", product["cSolid"]]) + if sim["tool"] == "Freezing Calculator": + writer.writerow(["Intial product temperature [C]:", product["Tpr0"]]) + writer.writerow(["Freezing temperature [C]:", product["Tf"]]) + writer.writerow(["Nucleation temperature [C]:", product["Tn"]]) + elif not ( + sim["tool"] == "Primary Drying Calculator" and sim["Rp_known"] == "N" + ): + writer.writerow(["R0 [cm^2-hr-Torr/g]:", product["R0"]]) + writer.writerow(["A1 [cm-hr-Torr/g]:", product["A1"]]) + writer.writerow(["A2 [1/cm]:", product["A2"]]) + if not ( + sim["tool"] == "Freezing Calculator" + and sim["tool"] == "Primary Drying Calculator" + ): + writer.writerow(["Critical product temperature [C]:", product["T_pr_crit"]]) + + if sim["tool"] == "Freezing Calculator": + writer.writerow(["h_freezing [W/m^2/K]:", inputs["h_freezing"]]) + elif sim["Kv_known"]: + writer.writerow(["KC [cal/s/K/cm^2]:", inputs["ht"]["KC"]]) + writer.writerow(["KP [cal/s/K/cm^2/Torr]:", inputs["ht"]["KP"]]) + writer.writerow(["KD [1/Torr]:", inputs["ht"]["KD"]]) + elif not sim["Kv_known"]: + writer.writerow(["Kv range [cal/s/K/cm^2]:", inputs["Kv_range"][:]]) + writer.writerow(["Experimental drying time [hr]:", inputs["t_dry_exp"]]) + + if sim["tool"] == "Freezing Calculator": + 0 + elif sim["tool"] == "Design Space Generator": + writer.writerow( + ["Chamber pressure set points [Torr]:", inputs["Pchamber"]["setpt"][:]] + ) + elif not (sim["tool"] == "Optimizer" and sim["Variable_Pch"] == "Y"): + for i in range(len(inputs["Pchamber"]["setpt"])): + writer.writerow( + [ + "Chamber pressure setpoint [Torr]:", + inputs["Pchamber"]["setpt"][i], + "Duration [min]:", + inputs["Pchamber"]["dt_setpt"][i], + ] + ) + writer.writerow( + [ + "Chamber pressure ramping rate [Torr/min]:", + inputs["Pchamber"]["ramp_rate"], + ] + ) + else: + writer.writerow( + ["Minimum chamber pressure [Torr]:", inputs["Pchamber"]["min"]] + ) + writer.writerow( + ["Maximum chamber pressure [Torr]:", inputs["Pchamber"]["max"]] + ) + writer.writerow([""]) + + if sim["tool"] == "Design Space Generator": + writer.writerow(["Intial shelf temperature [C]:", inputs["Tshelf"]["init"]]) + writer.writerow( + ["Shelf temperature set points [C]:", inputs["Tshelf"]["setpt"][:]] + ) + writer.writerow( + [ + "Shelf temperature ramping rate [C/min]:", + inputs["Tshelf"]["ramp_rate"], + ] + ) + elif not (sim["tool"] == "Optimizer" and sim["Variable_Tsh"] == "Y"): + for i in range(len(inputs["Tshelf"]["setpt"])): + writer.writerow( + [ + "Shelf temperature setpoint [C]:", + inputs["Tshelf"]["setpt"][i], + "Duration [min]:", + inputs["Tshelf"]["dt_setpt"][i], + ] + ) + writer.writerow( + [ + "Shelf temperature ramping rate [C/min]:", + inputs["Tshelf"]["ramp_rate"], + ] + ) + else: + writer.writerow(["Minimum shelf temperature [C]:", inputs["Tshelf"]["min"]]) + writer.writerow(["Maximum shelf temperature [C]:", inputs["Tshelf"]["max"]]) + + writer.writerow(["Time Step [hr]", inputs["dt"]]) + writer.writerow(["Equipment Parameter a [kg/hr]", inputs["eq_cap"]["a"]]) + writer.writerow(["Equipment Parameter b [kg/hr/Torr]", inputs["eq_cap"]["b"]]) + writer.writerow(["Number of Vials", inputs["nVial"]]) + + +def save_inputs(inputs, timestamp): + "Save inputs to a YAML file with timestamped filename." + try: + yamlfile = open("lyopronto_input_" + timestamp + ".yaml", "w") + yaml.dump(inputs, yamlfile) + finally: + yamlfile.close() + + +def read_inputs(filename): + "Read inputs from a YAML file." + try: + yamlfile = open(filename, "r") + inputs = yaml.load(yamlfile) + return inputs + finally: + yamlfile.close() + + +def save_csv(output_data, inputs, timestamp): + """ + Export simulation results to CSV file with appropriate formatting. + """ + filename = f"lyopronto_output_{timestamp}.csv" + + sim = inputs["sim"] + + if sim["tool"] == "Freezing Calculator": + assert output_data.shape[1] == 3 + header = "Time [hr], Shelf Temp [°C], Product Temp [°C]" + np.savetxt(filename, output_data, delimiter=", ", header=header) + elif sim["tool"] == "Design Space Generator": + _write_design_space_csv(output_data, inputs, filename) + else: + header = ",".join( + [ + "Time [hr]", + "Sublimation Front Temp [°C]", + "Vial Bottom Temperature [°C]", + "Shelf Temp [°C]", + "Chamber Pressure [mTorr]", + "Sublimation Flux [kg/hr/m²]", + "Percent Dried", + ] + ) + np.savetxt(filename, output_data, delimiter=", ", header=header) + + +def _write_design_space_csv(data, inputs, filename): + ds_shelf, ds_pr, ds_eq_cap = data + Tshelf = inputs["Tshelf"] + Pchamber = inputs["Pchamber"] + + try: + csvfile = open(filename, "w", newline="") + writer = csv.writer(csvfile) + writer.writerow( + [ + "Chamber Pressure [mTorr]", + "Maximum Product Temperature [C]", + "Drying Time [hr]", + "Average Sublimation Flux [kg/hr/m^2]", + "Maximum/Minimum Sublimation Flux [kg/hr/m^2]", + "Final Sublimation Flux [kg/hr/m^2]", + ] + ) + for i in range(np.size(Tshelf["setpt"])): + writer.writerow(["Shelf Temperature = ", str(Tshelf["setpt"][i])]) + for j in range(np.size(Pchamber["setpt"])): + writer.writerow( + [ + Pchamber["setpt"][j] * constant.Torr_to_mTorr, + *ds_shelf[:, i, j], + ] + ) + writer.writerow( + ["Product Temperature = ", str(inputs["product"]["T_pr_crit"])] + ) + writer.writerow( + [Pchamber["setpt"][0] * constant.Torr_to_mTorr, *ds_pr[:, 0]] + ) + writer.writerow( + [Pchamber["setpt"][-1] * constant.Torr_to_mTorr, *ds_pr[:, 1]] + ) + writer.writerow(["Equipment Capability"]) + for k in range(np.size(Pchamber["setpt"])): + writer.writerow( + [ + Pchamber["setpt"][k] * constant.Torr_to_mTorr, + *ds_eq_cap[:, k], + ds_eq_cap[-1, k], + ds_eq_cap[-1, k], + ] + ) + finally: + csvfile.close() + + +# TODO: implement this after redesigning design space output API +# def _write_design_space_yaml(data, inputs, filename): +# ds_shelf, ds_pr, ds_eq_cap = data +# # ds_shelf: 5 x nTsh x nPch +# # ds_pr: 5 x 2 +# # ds_eq_cap: 3 x nPch + +# def _read_design_space_yaml(filename): +# """Read design space data from a YAML file.""" + + +# TODO: add more kwargs, proper documentation, possibly refactor to make +# each subfunction part of the API +def generate_visualizations(output_data, inputs, timestamp): + """ + Create and save publication-quality plots based on simulation results. + """ + # TODO: move these to kwargs for the function + figure_props = { + "figwidth": 30, + "figheight": 20, + "linewidth": 5, + "marker_size": 20, + } + matplotlibrc("text.latex", preamble=r"\usepackage{color}") + matplotlibrc("text", usetex=False) + plt.rcParams["font.family"] = "Arial" + + if inputs["sim"]["tool"] == "Freezing Calculator": + _plot_freezing_results(output_data, figure_props, timestamp) + elif inputs["sim"]["tool"] in ["Primary Drying Calculator", "Optimizer"]: + _plot_drying_results(output_data, figure_props, timestamp) + elif inputs["sim"]["tool"] == "Design Space Generator": + _plot_design_space(output_data, inputs, figure_props, timestamp) + + +def _plot_freezing_results(data, props, timestamp): + """Generate freezing process visualization.""" + fig, ax = plt.subplots(figsize=(props["figwidth"], props["figheight"])) + ax.plot( + data[:, 0], + data[:, 1], + "-k", + linewidth=props["linewidth"], + label="Shelf Temperature", + ) + ax.plot( + data[:, 0], + data[:, 2], + "-b", + linewidth=props["linewidth"], + label="Product Temperature", + ) + ax.set_xlabel("Time [hr]", fontsize=props["axis_fontsize"], fontweight="bold") + ax.set_ylabel( + "Temperature [°C]", fontsize=props["axis_fontsize"], fontweight="bold" + ) + ax.legend(prop={"size": 40}) + plt.tight_layout() + plt.savefig(f"Temperatures_{timestamp}.pdf") + plt.close() + + +def _plot_drying_results(data, props, timestamp): + """Generate primary drying process visualizations.""" + + figwidth = props["figwidth"] + figheight = props["figheight"] + linewidth = props["linewidth"] + marker_size = props["marker_size"] + # Pressure and sublimation flux + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax1 = fig.add_subplot(1, 1, 1) + ax2 = ax1.twinx() + ax1.plot( + data[:, 0], + data[:, 4], + "-o", + color="b", + markevery=5, + linewidth=linewidth, + markersize=marker_size, + label="Chamber Pressure", + ) + ax2.plot( + data[:, 0], + data[:, 5], + "-", + color=[0, 0.7, 0.3], + linewidth=linewidth, + label="Sublimation Flux", + ) + + plot_styling.axis_style_pressure(ax1) + plot_styling.axis_style_subflux(ax2) + + plt.tight_layout() + plt.savefig(f"lyo_Pressure_SublimationFlux_{timestamp}.pdf") + plt.close() + + # Drying progress + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) + plot_styling.axis_style_percdried(ax) + ax.plot(data[:, 0], data[:, -1], "-k", linewidth=linewidth, label="Percent Dried") + plt.tight_layout() + plt.savefig(f"lyo_DryingProgress_{timestamp}.pdf") + plt.close() + + # Temperatures + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) + plot_styling.axis_style_temperature(ax) + ax.plot( + data[:, 0], + data[:, 1], + "-b", + linewidth=linewidth, + label="Sublimation Front Temperature", + ) + ax.plot( + data[:, 0], + data[:, 2], + "-r", + linewidth=linewidth, + label="Maximum Product Temperature", + ) + ax.plot( + data[:, 0], + data[:, 3], + "-o", + color="k", + markevery=5, + linewidth=linewidth, + markersize=marker_size, + label="Shelf Temperature", + ) + plt.legend(fontsize=40, loc="best") + ll, ul = ax.get_ylim() + ax.set_ylim([ll, ul + 5.0]) + plt.tight_layout() + plt.savefig(f"lyo_Temperatures_{timestamp}.pdf") + plt.close() + + +# TODO: work through this logic and see how much can be refactored out +def _plot_design_space(data, inputs, props, timestamp): + """Generate design space boundary visualization.""" + # Implementation for design space plotting + + ds_shelf, ds_pr, ds_eq_cap = data + Tshelf = np.array(inputs["Tshelf"]["setpt"]) + Pchamber = np.array(inputs["Pchamber"]["setpt"]) + T_pr_crit = inputs["product"]["T_pr_crit"] + figwidth = props["figwidth"] + figheight = props["figheight"] + lineWidth = props["linewidth"] + color_list = ["b", "m", "g", "c", "r", "y", "k"] # Line colors + + assert np.all(np.diff(Pchamber) >= 0), "Plotting assumes Pchamber set points are sorted." + # Design space: sublimation flux vs pressures + + # Range in pressure space, min to max, Torr + x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) + # Line 1: equipment capability sub flux, kg/hr/m^2 + # Indices (2,-1) is average sub flux at last Pch setpt, + # (2,0) is average sub flux at first Pch setpt + # Slope: (delta sub flux)/(delta pressure) + # Intercept: sub flux at first pressure + y1 = ( + (ds_eq_cap[2, -1] - ds_eq_cap[2, 0]) + / (Pchamber[-1] - Pchamber[0]) + ) * (x - Pchamber[0]) + ds_eq_cap[2, 0] + # Line 2: product temperature limited sub flux, kg/hr/m^2 + # Indices (3, -1) is minimum sub flux at last setpt, + # (3,0) is minimum sub flux at first setpt + # Slope: (delta sub flux)/(delta pressure) + # Intercept: sub flux at first pressure + y2 = ( + (ds_pr[3, -1] - ds_pr[3, 0]) / (Pchamber[-1] - Pchamber[0]) + ) * (x - Pchamber[0]) + ds_pr[3, 0] + # Convert to mTorr for plotting + x = x * constant.Torr_to_mTorr + # Get whichever sub flux is lower at each x value + y = np.minimum(y1, y2) + + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) + plt.axes(ax) + # Plot boundary lines + # Equipment capability line + + ax.plot( + # x: pressure in mTorr + Pchamber * constant.Torr_to_mTorr, + # y: equipment capability average sub flux, for all Pch + ds_eq_cap[2, :], + "-o", + color="k", + linewidth=lineWidth, + label="Equipment Capability", + ) + # Product temperature isotherm + # Straight line: endpoints only enough + ax.plot( + # x: pressure in mTorr + Pchamber[[0, -1]] * constant.Torr_to_mTorr, + # y: product temperature limited minimum sub flux, for all first and last Pch + ds_pr[3, :], + "-o", + color="r", + linewidth=lineWidth, + label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + "°C"), + ) + # Shelf temperature isotherms + for i in range(Tshelf.size): + ax.plot( + # x: pressure in mTorr + Pchamber * constant.Torr_to_mTorr, + # y: 3 for maximum sub flux, i shelf temp , for all Pch + ds_shelf[3, i, :], + "--", + color=str(color_list[i]), + linewidth=lineWidth, + label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), + ) + plot_styling.axis_style_designspace(ax, ylabel="Sublimation Flux [kg/hr/m$^2$]") + plt.legend(prop={"size": 40}) + ll, ul = ax.get_ylim() + # Adjust axis limits + # TODO: this logic seems questionable. What does it achieve? + # If minimum of eq cap average flux > maximum of pr limited min flux + if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): + # Adjust upper limit to be 1/3 of first two eq cap average flux values + ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 + # If instead minimum of pr limited min flux > maximum of eq cap average flux + elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): + # Adjust upper limit to be 1/4 of first two pr limited min flux values + ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + ll = max(0, ll) + # Fill the feasible region + ax.fill_between(x, y, ll, color=[1.0, 1.0, 0.6]) + # ul = np.max(y) * 1.2 # Consider: focus on feasible region + ax.set_ylim([ll, ul]) + plt.tight_layout() + figure_name = f"lyo_DesignSpace_SublimationFlux_{timestamp}.pdf" + plt.savefig(figure_name) + plt.close() + + # Drying time vs pressures + + #### First, filled area above constraints + # TODO: this is wrong: doesn't actually match constraints + # Pressure range in Torr + x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) + # Line 1: drying time limited by equipment capability + y1 = np.interp(x, Pchamber, ds_eq_cap[1, :]) + # Line 2: drying time limited by product temperature + y2 = np.interp(x, Pchamber[[0, -1]], ds_pr[1, :]) + # get pointwise maximum of y1 and y2 + y = np.maximum(y1, y2) + x = x * constant.Torr_to_mTorr # convert pressure range to mTorr + + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) + plt.axes(ax) + # Drying time boundary for eq cap + ax.plot( + Pchamber * constant.Torr_to_mTorr, + ds_eq_cap[1, :], + "-o", + color="k", + linewidth=lineWidth, + label="Equipment Capability", + ) + # Drying time boundary for product temperature + ax.plot( + Pchamber[[0, -1]] * constant.Torr_to_mTorr, + ds_pr[1, :], + "-o", + color="r", + linewidth=lineWidth, + label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), + ) + # Shelf temperature isotherms + for i in range(Tshelf.size): + ax.plot( + Pchamber * constant.Torr_to_mTorr, + ds_shelf[1, i, :], + "--", + color=str(color_list[i]), + linewidth=lineWidth, + label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), + ) + plot_styling.axis_style_designspace(ax, ylabel="Drying Time [hr]") + plt.legend(prop={"size": 40}) + ll, ul = ax.get_ylim() + ll = max(0, ll) + ax.set_ylim([ll, ul]) + ax.fill_between(x, y, ul, color=[1.0, 1.0, 0.6]) + figure_name = f"lyo_DesignSpace_DryingTime_{timestamp}.pdf" + plt.tight_layout() + plt.savefig(figure_name) + plt.close() + + # Product temperature vs pressures + + x = np.linspace( + np.min(Pchamber), np.max(Pchamber), 1000 + ) # pressure range in Torr + # Curve 1: equipment capability limited product temperature + y1 = np.interp(x, Pchamber, ds_eq_cap[0, :]) # equipment capability limiting product temperature in degC + # Curve 2: horizontal line at product temperature limit + y2 = np.full_like(y1, T_pr_crit) # horizontal line at product temperature limit + y = np.minimum(y1, y2) + + x = x * constant.Torr_to_mTorr # Convert pressure range to mTorr + # Pointwise minimum of y1 and y2 + + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(1, 1, 1) + plt.axes(ax) + ax.plot( + Pchamber * constant.Torr_to_mTorr, + ds_eq_cap[0, :], + "-o", + color="k", + linewidth=lineWidth, + label="Equipment Capability", + ) + ax.plot( + Pchamber[[0, -1]] * constant.Torr_to_mTorr, + ds_pr[0, :], + "-o", + color="r", + linewidth=lineWidth, + label=("T$_{pr}$ = " + str(inputs["product"]["T_pr_crit"]) + " C"), + ) + for i in range(np.size(Tshelf)): + ax.plot( + Pchamber * constant.Torr_to_mTorr, + ds_shelf[0, i, :], + "--", + color=str(color_list[i]), + linewidth=lineWidth, + label=("T$_{sh}$ = " + str(Tshelf[i]) + " C"), + ) + plot_styling.axis_style_designspace(ax, ylabel="Product Temperature [°C]") + plt.legend(prop={"size": 40}) + ll, ul = ax.get_ylim() + # TODO: Possibly tinker with ll and ul + ax.set_ylim([ll, ul]) + ax.fill_between(x, y, ll, color=[1.0, 1.0, 0.6]) + figure_name = f"lyo_DesignSpace_ProductTemperature_{timestamp}.pdf" + plt.tight_layout() + plt.savefig(figure_name) + plt.close() \ No newline at end of file From e628a6ad79d7a8f3f0d2fb68d91abae3ce630162 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 6 Feb 2026 13:38:34 -0500 Subject: [PATCH 16/31] Record temp data filename in inputs, but not the full arrays --- lyopronto/high_level.py | 11 ++++++++++- main.py | 5 +++++ 2 files changed, 15 insertions(+), 1 deletion(-) diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index 1945bfa..8e453a0 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -269,9 +269,14 @@ def save_inputs_legacy(inputs, timestamp): def save_inputs(inputs, timestamp): "Save inputs to a YAML file with timestamped filename." + copied = inputs.copy() + # If the inputs include large arrays of data, strip those out + copied.pop("time_data", None) + copied.pop("temp_data", None) + # Then save try: yamlfile = open("lyopronto_input_" + timestamp + ".yaml", "w") - yaml.dump(inputs, yamlfile) + yaml.dump(copied, yamlfile) finally: yamlfile.close() @@ -281,6 +286,10 @@ def read_inputs(filename): try: yamlfile = open(filename, "r") inputs = yaml.load(yamlfile) + if "product_temp_filename" in inputs: + print("Note: input specifies a product temperature data file." + + "This data should be loaded separately and added to the inputs dictionary" + + "as `time_data` and `temp_data`.") return inputs finally: yamlfile.close() diff --git a/main.py b/main.py index 25c19f7..e573d6e 100644 --- a/main.py +++ b/main.py @@ -79,7 +79,11 @@ else: product = {"cSolid": 0.05} + # Keep this variable's name, so that it can be recorded with inputs, but adjust the + # filename as necessary to get your local data. + # The times and temperatures will not be recorded directly with the inputs, for sake of space product_temp_filename = "./temperature.dat" + # Load that file. As necessary, add keywords to np.loadtxt to get the correct data exp_data = np.loadtxt(product_temp_filename) # Assumed: time in first column, temperature in second column # Change as necessary to match data file, but keep these names @@ -163,6 +167,7 @@ "h_freezing", "t_dry_exp", "Kv_range", + "product_temp_filename", "time_data", "temp_data", ]: From 553c27f16e58548a1ac04a412992b7cccf4d0944 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 6 Feb 2026 15:40:32 -0500 Subject: [PATCH 17/31] Add some tests that run YAML inputs through the full main script --- lyopronto/high_level.py | 7 +- main.py | 2 +- pyproject.toml | 2 + test_data/example_design_space.yaml | 39 ++++++++++ test_data/example_freezing.yaml | 29 ++++++++ test_data/example_knownrp.yaml | 38 ++++++++++ test_data/example_unknownkv.yaml | 38 ++++++++++ tests/test_calc_knownRp.py | 47 ++++++++++++ tests/test_calc_unknownRp.py | 24 +++++++ tests/test_main.py | 108 ++++++++++++++++++++++++++++ 10 files changed, 328 insertions(+), 6 deletions(-) create mode 100644 test_data/example_design_space.yaml create mode 100644 test_data/example_freezing.yaml create mode 100644 test_data/example_knownrp.yaml create mode 100644 test_data/example_unknownkv.yaml create mode 100644 tests/test_main.py diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index 8e453a0..fb905db 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -427,13 +427,10 @@ def _plot_freezing_results(data, props, timestamp): linewidth=props["linewidth"], label="Product Temperature", ) - ax.set_xlabel("Time [hr]", fontsize=props["axis_fontsize"], fontweight="bold") - ax.set_ylabel( - "Temperature [°C]", fontsize=props["axis_fontsize"], fontweight="bold" - ) + plot_styling.axis_style_temperature(ax) ax.legend(prop={"size": 40}) plt.tight_layout() - plt.savefig(f"Temperatures_{timestamp}.pdf") + plt.savefig(f"lyo_Temperatures_{timestamp}.pdf") plt.close() diff --git a/main.py b/main.py index e573d6e..fd4c99a 100644 --- a/main.py +++ b/main.py @@ -41,7 +41,7 @@ # Simulation type # 4 Tools available: 'Freezing Calculator', 'Primary Drying Calculator', 'Design Space Generator', 'Optimizer' -# For 'Freezing Calculator': h_freezeing, Tpr0, Tf and Tn must be provided +# For 'Freezing Calculator': h_freezing, Tpr0, Tf and Tn must be provided # No Variable Tsh - set point must be specified # For 'Primary Drying Calculator': If Kv and Rp are known, drying time can be determined # If drying time and Rp are known, Kv can be determined diff --git a/pyproject.toml b/pyproject.toml index 569bd9a..7c73724 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -42,6 +42,7 @@ classifiers = [ [project.optional-dependencies] dev = [ "pytest>=7.4.0", + "pytest-mock>=3", "pytest-cov>=4.1.0", "pytest-xdist>=3.3.0", "hypothesis>=6.82.0", @@ -86,4 +87,5 @@ markers = [ "slow: Tests that take a long time to run", "fast: Quick tests that run in under 1 second", "notebook: Tests that execute Jupyter notebooks for documentation", + "main: Tests that cover functionality previously included in main.py", ] diff --git a/test_data/example_design_space.yaml b/test_data/example_design_space.yaml new file mode 100644 index 0000000..5e3cb95 --- /dev/null +++ b/test_data/example_design_space.yaml @@ -0,0 +1,39 @@ +sim: + tool: Design Space Generator + Kv_known: true + Rp_known: true + Variable_Pch: false + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +ht: + KC: 0.000275 + KP: 0.000893 + KD: 0.46 +Pchamber: + setpt: + - 0.02 + - 0.05 + - 0.1 + - 0.15 +Tshelf: + init: -5.0 + setpt: + - -15 + - 0 + - 30 + - 90 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 diff --git a/test_data/example_freezing.yaml b/test_data/example_freezing.yaml new file mode 100644 index 0000000..37f1928 --- /dev/null +++ b/test_data/example_freezing.yaml @@ -0,0 +1,29 @@ +sim: + tool: Freezing Calculator + Kv_known: true + Rp_known: true + Variable_Pch: false + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.0 + Tpr0: 15.8 + Tf: -1.54 + Tn: -5.84 + T_pr_crit: -5 +Tshelf: + init: 15.0 + setpt: + - -40.0 + dt_setpt: + - 180.0 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 +h_freezing: 38.0 diff --git a/test_data/example_knownrp.yaml b/test_data/example_knownrp.yaml new file mode 100644 index 0000000..2bd8367 --- /dev/null +++ b/test_data/example_knownrp.yaml @@ -0,0 +1,38 @@ +sim: + tool: Primary Drying Calculator + Kv_known: true + Rp_known: true + Variable_Pch: false + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +ht: + KC: 0.000275 + KP: 0.000893 + KD: 0.46 +Pchamber: + setpt: + - 0.15 + dt_setpt: + - 1800.0 + ramp_rate: 0.5 +Tshelf: + init: -35.0 + setpt: + - 20.0 + dt_setpt: + - 1800.0 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 diff --git a/test_data/example_unknownkv.yaml b/test_data/example_unknownkv.yaml new file mode 100644 index 0000000..f6b9a78 --- /dev/null +++ b/test_data/example_unknownkv.yaml @@ -0,0 +1,38 @@ +sim: + tool: Primary Drying Calculator + Kv_known: false + Rp_known: true + Variable_Pch: false + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +Pchamber: + setpt: + - 0.15 + dt_setpt: + - 1800.0 + ramp_rate: 0.5 +Tshelf: + init: -35.0 + setpt: + - 20.0 + dt_setpt: + - 1800.0 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 +t_dry_exp: 12.62 +Kv_range: +- 0.0001 +- 0.002 diff --git a/tests/test_calc_knownRp.py b/tests/test_calc_knownRp.py index 6c9fa29..0267f60 100644 --- a/tests/test_calc_knownRp.py +++ b/tests/test_calc_knownRp.py @@ -3,6 +3,7 @@ import pytest import numpy as np from lyopronto import calc_knownRp, constant +from lyopronto.high_level import execute_simulation from .utils import ( assert_physically_reasonable_output, assert_complete_drying, @@ -10,6 +11,7 @@ ) + @pytest.fixture def knownRp_standard_setup(standard_setup): """Unpack standard setup into individual components.""" @@ -150,6 +152,50 @@ def test_mass_balance_conservation(self, knownRp_standard_setup): f"(error: {abs(mass_removed - water_mass_initial) / water_mass_initial * 100:.1f}%)" ) + @pytest.mark.main + def test_main_known_kv(self, mocker, knownRp_standard_setup): + """Test that this function is called from high-level API without errors.""" + sim = {"tool": "Primary Drying Calculator", + "Kv_known": True, + "Rp_known": True,} + vial, product, ht, Pchamber, Tshelf, dt = knownRp_standard_setup + + mocked_func = mocker.patch("lyopronto.calc_knownRp.dry", wraps=calc_knownRp.dry, autospec=True) + inputs = {"sim": sim,} + loc = locals() + for key in ["vial", "product", "ht", "Pchamber", "Tshelf", "dt", ]: + inputs[key] = loc[key] + + output = execute_simulation(inputs) + + mocked_func.assert_called_once_with(vial, product, ht, Pchamber, Tshelf, dt) + + assert_physically_reasonable_output(output) + assert_complete_drying(output) + + @pytest.mark.main + def test_main_unknown_kv(self, mocker, knownRp_standard_setup): + """Test that this function is called from high-level API without errors.""" + sim = {"tool": "Primary Drying Calculator", + "Kv_known": False, + "Rp_known": True,} + vial, product, _, Pchamber, Tshelf, dt = knownRp_standard_setup + Kv_range = [1e-4, 1e-2] + t_dry_exp = 12.0 + + mocked_func = mocker.patch("lyopronto.calc_knownRp.dry", wraps=calc_knownRp.dry, autospec=True) + inputs = {"sim": sim,} + loc = locals() + for key in ["vial", "product", "Kv_range", "Pchamber", "Tshelf", "dt", "t_dry_exp"]: + inputs[key] = loc[key] + + output = execute_simulation(inputs) + + assert mocked_func.call_count > 2 # Should be called at least twice by rootfinder + + assert_physically_reasonable_output(output) + assert_complete_drying(output) + class TestEdgeCases: """Tests for edge cases and error handling.""" @@ -363,3 +409,4 @@ def test_flux_profile_non_monotonic(self, reference_case): # After peak, flux should generally decrease (late stage) late_stage = flux[int(len(flux) * 0.8) :] assert np.all(np.diff(late_stage) <= 0.0), "Flux should decrease in late stage" + diff --git a/tests/test_calc_unknownRp.py b/tests/test_calc_unknownRp.py index 7420655..d2ecb8f 100644 --- a/tests/test_calc_unknownRp.py +++ b/tests/test_calc_unknownRp.py @@ -12,6 +12,7 @@ import scipy.optimize as sp from lyopronto import calc_unknownRp +from lyopronto.high_level import execute_simulation from lyopronto.functions import Lpr0_FUN, Rp_FUN from .utils import assert_physically_reasonable_output, assert_incomplete_drying @@ -146,6 +147,29 @@ def test_calc_unknownRp_basics(self, standard_inputs_nodt, temperature_data): assert final_Lck > 0, "Cake length should have progressed" assert final_Lck <= Lpr0 * 1.01, "Cake length should not exceed initial height" + @pytest.mark.main + def test_main_unknown_rp(self, mocker, standard_inputs_nodt, temperature_data): + """Test that this function is called from high-level API without errors.""" + sim = {"tool": "Primary Drying Calculator", + "Kv_known": True, + "Rp_known": False,} + vial, product, ht, Pchamber, Tshelf = standard_inputs_nodt + time_data, temp_data = temperature_data + print(time_data[-1]) + + mocked_func = mocker.patch("lyopronto.calc_unknownRp.dry", wraps=calc_unknownRp.dry) + inputs = {"sim": sim,} + loc = locals() + for key in ["vial", "product", "ht", "Pchamber", "Tshelf", "time_data", "temp_data"]: + inputs[key] = loc[key] + + output = execute_simulation(inputs) + + mocked_func.assert_called_once_with(vial, product, ht, Pchamber, Tshelf, time_data, temp_data) + + assert_physically_reasonable_output(output) + assert_incomplete_drying(output) + class TestCalcUnknownRpEdgeCases: """Test edge cases and different input scenarios.""" diff --git a/tests/test_main.py b/tests/test_main.py new file mode 100644 index 0000000..8b63ab0 --- /dev/null +++ b/tests/test_main.py @@ -0,0 +1,108 @@ +"""Tests for the high-level API (formerly main.py).""" + +from contextlib import chdir +import pytest +import numpy as np +from lyopronto import * +from .utils import ( + assert_physically_reasonable_output, + assert_complete_drying, + assert_incomplete_drying, +) + +class TestHighLevelAPI: + """Tests for the high-level API functions in lyopronto.high_level.""" + + @pytest.mark.main + def test_freezing_fullstack(self, mocker, repo_root, tmp_path): + input_file = repo_root / "test_data" / "example_freezing.yaml" + mocked_func = mocker.patch("lyopronto.freezing.freeze", wraps=freezing.freeze, autospec=True) + with chdir(tmp_path): + inputs = read_inputs(input_file) + + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + output = execute_simulation(inputs) + assert mocked_func.call_count == 1 + + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() + + + @pytest.mark.main + def test_knownRp_fullstack(self, mocker, repo_root, tmp_path): + input_file = repo_root / "test_data" / "example_knownRp.yaml" + mocked_func = mocker.patch("lyopronto.calc_knownRp.dry", wraps=calc_knownRp.dry, autospec=True) + with chdir(tmp_path): + inputs = read_inputs(input_file) + + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + output = execute_simulation(inputs) + assert mocked_func.call_count == 1 + + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() + assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() + assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + + @pytest.mark.main + def test_unknownKv_fullstack(self, mocker, repo_root, tmp_path, capsys): + input_file = repo_root / "test_data" / "example_unknownKv.yaml" + mocked_func = mocker.patch("lyopronto.calc_knownRp.dry", wraps=calc_knownRp.dry, autospec=True) + with chdir(tmp_path): + inputs = read_inputs(input_file) + + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + output = execute_simulation(inputs) + captured = capsys.readouterr() + assert "Optimal Kv: " in captured.out + assert mocked_func.call_count > 2 # Should be called multiple times by rootfinder + + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() + assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() + assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + + @pytest.mark.main + def test_design_space_fullstack(self, repo_root, tmp_path): + input_file = repo_root / "test_data" / "example_design_space.yaml" + with chdir(tmp_path): + inputs = read_inputs(input_file) + + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + output = execute_simulation(inputs) + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_DesignSpace_ProductTemperature_testtime.pdf").exists() + assert (tmp_path / "lyo_DesignSpace_SublimationFlux_testtime.pdf").exists() + assert (tmp_path / "lyo_DesignSpace_DryingTime_testtime.pdf").exists() + + + + From f80c0123fb3d6fac9ed4313f5a0c73927bf83042 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Fri, 6 Feb 2026 15:42:15 -0500 Subject: [PATCH 18/31] Fix possible bug due to unclear code in crystallization time bracketing --- lyopronto/functions.py | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/lyopronto/functions.py b/lyopronto/functions.py index 1b4a250..59b9622 100644 --- a/lyopronto/functions.py +++ b/lyopronto/functions.py @@ -328,15 +328,13 @@ def crystallization_time_FUN(V,h,Av,Tf,Tn,Tsh_func,t0): hA = h*constant.hr_To_s * Av*constant.cm_To_m**2 # heat transfer coefficient in J/K/hr # t = rhoV*(Hf-Cp*(Tf-Tn))/hA/(Tf-Tsh) # time: g*(J/g- J/g/K*K)/(J/m^2/K/hr*m^2*K) = hr lhs = rhoV*(Hf-Cp*(Tf-Tn))/hA - def integrand(t): - return Tf - Tsh_func(t+t0) - def resid(t): - integral, _ = quad(integrand, 0, t) + def integrand(dt): + return Tf - Tsh_func(t0+dt) + def resid(delta_t): + integral, _ = quad(integrand, 0, delta_t) return integral - lhs - t = brentq(resid, t0, t0+100.0) - - - return t + delta_t = brentq(resid, 0, 100.0) + return delta_t ## From d316da416d81cec2b31433e6b9763bf030d3aaa3 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 09:29:55 -0500 Subject: [PATCH 19/31] fix filename casing so tests find them --- tests/test_main.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_main.py b/tests/test_main.py index 8b63ab0..b24df72 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -37,7 +37,7 @@ def test_freezing_fullstack(self, mocker, repo_root, tmp_path): @pytest.mark.main def test_knownRp_fullstack(self, mocker, repo_root, tmp_path): - input_file = repo_root / "test_data" / "example_knownRp.yaml" + input_file = repo_root / "test_data" / "example_knownrp.yaml" mocked_func = mocker.patch("lyopronto.calc_knownRp.dry", wraps=calc_knownRp.dry, autospec=True) with chdir(tmp_path): inputs = read_inputs(input_file) @@ -60,7 +60,7 @@ def test_knownRp_fullstack(self, mocker, repo_root, tmp_path): @pytest.mark.main def test_unknownKv_fullstack(self, mocker, repo_root, tmp_path, capsys): - input_file = repo_root / "test_data" / "example_unknownKv.yaml" + input_file = repo_root / "test_data" / "example_unknownkv.yaml" mocked_func = mocker.patch("lyopronto.calc_knownRp.dry", wraps=calc_knownRp.dry, autospec=True) with chdir(tmp_path): inputs = read_inputs(input_file) From 3239f3f8ff6149ec3a7cf59b1fae9b71da2cac42 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 13:16:14 -0500 Subject: [PATCH 20/31] Cleanup in design space plots --- lyopronto/high_level.py | 48 +++++++++++++++++++++-------------------- 1 file changed, 25 insertions(+), 23 deletions(-) diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index fb905db..8e2652b 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -530,7 +530,9 @@ def _plot_design_space(data, inputs, props, timestamp): lineWidth = props["linewidth"] color_list = ["b", "m", "g", "c", "r", "y", "k"] # Line colors - assert np.all(np.diff(Pchamber) >= 0), "Plotting assumes Pchamber set points are sorted." + assert np.all(np.diff(Pchamber) >= 0), ( + "Plotting assumes Pchamber set points are sorted." + ) # Design space: sublimation flux vs pressures # Range in pressure space, min to max, Torr @@ -540,18 +542,17 @@ def _plot_design_space(data, inputs, props, timestamp): # (2,0) is average sub flux at first Pch setpt # Slope: (delta sub flux)/(delta pressure) # Intercept: sub flux at first pressure - y1 = ( - (ds_eq_cap[2, -1] - ds_eq_cap[2, 0]) - / (Pchamber[-1] - Pchamber[0]) - ) * (x - Pchamber[0]) + ds_eq_cap[2, 0] + y1 = ((ds_eq_cap[2, -1] - ds_eq_cap[2, 0]) / (Pchamber[-1] - Pchamber[0])) * ( + x - Pchamber[0] + ) + ds_eq_cap[2, 0] # Line 2: product temperature limited sub flux, kg/hr/m^2 # Indices (3, -1) is minimum sub flux at last setpt, # (3,0) is minimum sub flux at first setpt # Slope: (delta sub flux)/(delta pressure) # Intercept: sub flux at first pressure - y2 = ( - (ds_pr[3, -1] - ds_pr[3, 0]) / (Pchamber[-1] - Pchamber[0]) - ) * (x - Pchamber[0]) + ds_pr[3, 0] + y2 = ((ds_pr[3, -1] - ds_pr[3, 0]) / (Pchamber[-1] - Pchamber[0])) * ( + x - Pchamber[0] + ) + ds_pr[3, 0] # Convert to mTorr for plotting x = x * constant.Torr_to_mTorr # Get whichever sub flux is lower at each x value @@ -601,15 +602,17 @@ def _plot_design_space(data, inputs, props, timestamp): plt.legend(prop={"size": 40}) ll, ul = ax.get_ylim() # Adjust axis limits - # TODO: this logic seems questionable. What does it achieve? - # If minimum of eq cap average flux > maximum of pr limited min flux - if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): - # Adjust upper limit to be 1/3 of first two eq cap average flux values - ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 - # If instead minimum of pr limited min flux > maximum of eq cap average flux - elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): - # Adjust upper limit to be 1/4 of first two pr limited min flux values - ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 + # TODO: consider under what conditions y limits should be adjusted + # Particularly: if eq cap is much higher than product, or vice versa + # Former logic follows + # # If minimum of eq cap average flux > maximum of pr limited min flux + # if np.min(ds_eq_cap[2, :]) > np.max(ds_pr[3, :]): + # # Adjust upper limit to be 1/3 of first two eq cap average flux values + # ul = (ds_eq_cap[2, 0] + ds_eq_cap[2, 1]) / 3 + # # If instead minimum of pr limited min flux > maximum of eq cap average flux + # elif np.min(ds_pr[3, :]) > np.max(ds_eq_cap[2, :]): + # # Adjust upper limit to be 1/4 of the two pr limited min flux values + # ul = (ds_pr[3, 0] + ds_pr[3, 1]) / 4 ll = max(0, ll) # Fill the feasible region ax.fill_between(x, y, ll, color=[1.0, 1.0, 0.6]) @@ -623,9 +626,8 @@ def _plot_design_space(data, inputs, props, timestamp): # Drying time vs pressures #### First, filled area above constraints - # TODO: this is wrong: doesn't actually match constraints # Pressure range in Torr - x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) + x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) # Line 1: drying time limited by equipment capability y1 = np.interp(x, Pchamber, ds_eq_cap[1, :]) # Line 2: drying time limited by product temperature @@ -678,11 +680,11 @@ def _plot_design_space(data, inputs, props, timestamp): # Product temperature vs pressures - x = np.linspace( - np.min(Pchamber), np.max(Pchamber), 1000 - ) # pressure range in Torr + x = np.linspace(np.min(Pchamber), np.max(Pchamber), 1000) # pressure range in Torr # Curve 1: equipment capability limited product temperature - y1 = np.interp(x, Pchamber, ds_eq_cap[0, :]) # equipment capability limiting product temperature in degC + y1 = np.interp( + x, Pchamber, ds_eq_cap[0, :] + ) # equipment capability limiting product temperature in degC # Curve 2: horizontal line at product temperature limit y2 = np.full_like(y1, T_pr_crit) # horizontal line at product temperature limit y = np.minimum(y1, y2) From 009d241fa4d4857e9edaa1d1fe60068aa54fdbad Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 13:17:02 -0500 Subject: [PATCH 21/31] Test high-level functionality for all modes --- lyopronto/high_level.py | 97 +++++++++++++--- test_data/badexample_optimizer_noopt.yaml | 38 +++++++ test_data/badexample_unknownkvrp.yaml | 38 +++++++ test_data/example_opt_pch.yaml | 35 ++++++ test_data/example_opt_pch_tsh.yaml | 31 ++++++ test_data/example_opt_tsh.yaml | 34 ++++++ test_data/example_unknownrp.yaml | 36 ++++++ tests/test_main.py | 130 +++++++++++++++++++++- 8 files changed, 420 insertions(+), 19 deletions(-) create mode 100644 test_data/badexample_optimizer_noopt.yaml create mode 100644 test_data/badexample_unknownkvrp.yaml create mode 100644 test_data/example_opt_pch.yaml create mode 100644 test_data/example_opt_pch_tsh.yaml create mode 100644 test_data/example_opt_tsh.yaml create mode 100644 test_data/example_unknownrp.yaml diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index 8e2652b..7d2d7bc 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -1,4 +1,12 @@ -from . import freezing, calc_knownRp, calc_unknownRp, design_space, opt_Pch_Tsh, opt_Pch, opt_Tsh +from . import ( + freezing, + calc_knownRp, + calc_unknownRp, + design_space, + opt_Pch_Tsh, + opt_Pch, + opt_Tsh, +) from . import functions, constant, plot_styling from warnings import warn @@ -125,7 +133,7 @@ def _optimize_rp_parameter(inputs): ) print(f"R0: {params[0]}, A1: {params[1]}, A2: {params[2]}") - return output + return output, product_res, params def _run_optimizer(inputs): @@ -146,6 +154,8 @@ def _run_optimizer(inputs): return opt_Pch.dry(*args) elif inputs["sim"]["Variable_Tsh"]: return opt_Tsh.dry(*args) + else: + raise ValueError("Either Tsh or Pch needs to be variable to optimize.") def save_inputs_legacy(inputs, timestamp): @@ -177,15 +187,13 @@ def save_inputs_legacy(inputs, timestamp): writer.writerow(["Intial product temperature [C]:", product["Tpr0"]]) writer.writerow(["Freezing temperature [C]:", product["Tf"]]) writer.writerow(["Nucleation temperature [C]:", product["Tn"]]) - elif not ( - sim["tool"] == "Primary Drying Calculator" and sim["Rp_known"] == "N" - ): + elif not (sim["tool"] == "Primary Drying Calculator" and not sim["Rp_known"]): writer.writerow(["R0 [cm^2-hr-Torr/g]:", product["R0"]]) writer.writerow(["A1 [cm-hr-Torr/g]:", product["A1"]]) writer.writerow(["A2 [1/cm]:", product["A2"]]) if not ( sim["tool"] == "Freezing Calculator" - and sim["tool"] == "Primary Drying Calculator" + or sim["tool"] == "Primary Drying Calculator" ): writer.writerow(["Critical product temperature [C]:", product["T_pr_crit"]]) @@ -205,7 +213,7 @@ def save_inputs_legacy(inputs, timestamp): writer.writerow( ["Chamber pressure set points [Torr]:", inputs["Pchamber"]["setpt"][:]] ) - elif not (sim["tool"] == "Optimizer" and sim["Variable_Pch"] == "Y"): + elif not (sim["tool"] == "Optimizer" and sim["Variable_Pch"]): for i in range(len(inputs["Pchamber"]["setpt"])): writer.writerow( [ @@ -241,7 +249,7 @@ def save_inputs_legacy(inputs, timestamp): inputs["Tshelf"]["ramp_rate"], ] ) - elif not (sim["tool"] == "Optimizer" and sim["Variable_Tsh"] == "Y"): + elif not (sim["tool"] == "Optimizer" and sim["Variable_Tsh"]): for i in range(len(inputs["Tshelf"]["setpt"])): writer.writerow( [ @@ -287,9 +295,11 @@ def read_inputs(filename): yamlfile = open(filename, "r") inputs = yaml.load(yamlfile) if "product_temp_filename" in inputs: - print("Note: input specifies a product temperature data file." - + "This data should be loaded separately and added to the inputs dictionary" - + "as `time_data` and `temp_data`.") + print( + "Note: input specifies a product temperature data file." + + "This data should be loaded separately and added to the inputs dictionary" + + "as `time_data` and `temp_data`." + ) return inputs finally: yamlfile.close() @@ -310,6 +320,21 @@ def save_csv(output_data, inputs, timestamp): elif sim["tool"] == "Design Space Generator": _write_design_space_csv(output_data, inputs, filename) else: + if sim["tool"] == "Primary Drying Calculator" and not sim["Rp_known"]: + assert len(output_data) == 3 # output, product_res, params + header = ",".join( + [ + "Time [hr]", + "Cake Length [cm]", + "Product Resistance [cm^2-hr-Torr/g]", + ] + ) + rpfile = f"lyo_Rp_data_{timestamp}.csv" + np.savetxt(rpfile, output_data[1], delimiter=", ", header=header) + data = output_data[0] + else: + data = output_data # for all but unknown Rp, output_data is the only return + header = ",".join( [ "Time [hr]", @@ -321,7 +346,7 @@ def save_csv(output_data, inputs, timestamp): "Percent Dried", ] ) - np.savetxt(filename, output_data, delimiter=", ", header=header) + np.savetxt(filename, data, delimiter=", ", header=header) def _write_design_space_csv(data, inputs, filename): @@ -391,6 +416,7 @@ def generate_visualizations(output_data, inputs, timestamp): """ Create and save publication-quality plots based on simulation results. """ + # TODO: move these to kwargs for the function figure_props = { "figwidth": 30, @@ -398,15 +424,21 @@ def generate_visualizations(output_data, inputs, timestamp): "linewidth": 5, "marker_size": 20, } + tool = inputs["sim"]["tool"] matplotlibrc("text.latex", preamble=r"\usepackage{color}") matplotlibrc("text", usetex=False) plt.rcParams["font.family"] = "Arial" - if inputs["sim"]["tool"] == "Freezing Calculator": + if tool == "Freezing Calculator": _plot_freezing_results(output_data, figure_props, timestamp) - elif inputs["sim"]["tool"] in ["Primary Drying Calculator", "Optimizer"]: - _plot_drying_results(output_data, figure_props, timestamp) - elif inputs["sim"]["tool"] == "Design Space Generator": + elif tool in ["Primary Drying Calculator", "Optimizer"]: + if tool == "Primary Drying Calculator" and not inputs["sim"]["Rp_known"]: + _plot_rp_results(output_data, figure_props, timestamp) + data = output_data[0] # There are extra returns for Rp fitting + else: + data = output_data # for all but unknown Rp, output_data is the only return + _plot_drying_results(data, figure_props, timestamp) + elif tool == "Design Space Generator": _plot_design_space(output_data, inputs, figure_props, timestamp) @@ -515,8 +547,37 @@ def _plot_drying_results(data, props, timestamp): plt.savefig(f"lyo_Temperatures_{timestamp}.pdf") plt.close() +def _plot_rp_results(data, props, timestamp): + product_res = data[1] + params = data[2] + figwidth = props["figwidth"] + figheight = props["figheight"] + linewidth = props["linewidth"] + marker_size = props["marker_size"] + fig = plt.figure(0, figsize=(figwidth, figheight)) + ax = fig.add_subplot(111) + plot_styling.axis_style_rp(ax) + ax.plot( + product_res[:, 1], + product_res[:, 2], + "o", + markevery=5, + markersize=marker_size, + label="$R_p$ from Temperature Data", + ) + ax.plot( + product_res[:, 1], + params[0] + product_res[:, 1] * params[1] / (1 + product_res[:, 1] * params[2]), + "-", + linewidth=linewidth, + label="Fitted $R_p$", + ) + ll, ul = ax.get_ylim() + ax.set_ylim([max(0, ll), ul]) + plt.legend(fontsize=40, loc="best") + plt.savefig(f"lyo_Rp_Fit_{timestamp}.pdf") + plt.close() -# TODO: work through this logic and see how much can be refactored out def _plot_design_space(data, inputs, props, timestamp): """Generate design space boundary visualization.""" # Implementation for design space plotting @@ -729,4 +790,4 @@ def _plot_design_space(data, inputs, props, timestamp): figure_name = f"lyo_DesignSpace_ProductTemperature_{timestamp}.pdf" plt.tight_layout() plt.savefig(figure_name) - plt.close() \ No newline at end of file + plt.close() diff --git a/test_data/badexample_optimizer_noopt.yaml b/test_data/badexample_optimizer_noopt.yaml new file mode 100644 index 0000000..8027e44 --- /dev/null +++ b/test_data/badexample_optimizer_noopt.yaml @@ -0,0 +1,38 @@ +sim: + tool: Optimizer + Kv_known: true + Rp_known: true + Variable_Pch: false + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +ht: + KC: 0.000275 + KP: 0.000893 + KD: 0.46 +Pchamber: + setpt: + - 0.15 + dt_setpt: + - 1800.0 + ramp_rate: 0.5 +Tshelf: + init: 15.0 + setpt: + - -40.0 + dt_setpt: + - 180.0 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 diff --git a/test_data/badexample_unknownkvrp.yaml b/test_data/badexample_unknownkvrp.yaml new file mode 100644 index 0000000..d14464c --- /dev/null +++ b/test_data/badexample_unknownkvrp.yaml @@ -0,0 +1,38 @@ +sim: + tool: Primary Drying Calculator + Kv_known: false + Rp_known: false + Variable_Pch: false + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +Pchamber: + setpt: + - 0.15 + dt_setpt: + - 1800.0 + ramp_rate: 0.5 +Tshelf: + init: -35.0 + setpt: + - 20.0 + dt_setpt: + - 1800.0 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 +t_dry_exp: 12.62 +Kv_range: +- 0.0001 +- 0.002 diff --git a/test_data/example_opt_pch.yaml b/test_data/example_opt_pch.yaml new file mode 100644 index 0000000..04b0653 --- /dev/null +++ b/test_data/example_opt_pch.yaml @@ -0,0 +1,35 @@ +sim: + tool: Optimizer + Kv_known: true + Rp_known: true + Variable_Pch: true + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +ht: + KC: 0.000275 + KP: 0.000893 + KD: 0.46 +Pchamber: + min: 0.05 + max: 1000 +Tshelf: + init: -40 + setpt: + - 10.0 + dt_setpt: + - 1800.0 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 diff --git a/test_data/example_opt_pch_tsh.yaml b/test_data/example_opt_pch_tsh.yaml new file mode 100644 index 0000000..9ca0cfc --- /dev/null +++ b/test_data/example_opt_pch_tsh.yaml @@ -0,0 +1,31 @@ +sim: + tool: Optimizer + Kv_known: true + Rp_known: true + Variable_Pch: true + Variable_Tsh: true +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +ht: + KC: 0.000275 + KP: 0.000893 + KD: 0.46 +Pchamber: + min: 0.05 + max: 1000 +Tshelf: + min: -45 + max: 120 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 diff --git a/test_data/example_opt_tsh.yaml b/test_data/example_opt_tsh.yaml new file mode 100644 index 0000000..dcce169 --- /dev/null +++ b/test_data/example_opt_tsh.yaml @@ -0,0 +1,34 @@ +sim: + tool: Optimizer + Kv_known: true + Rp_known: true + Variable_Pch: false + Variable_Tsh: true +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + R0: 1.4 + A1: 16.0 + A2: 0.0 + T_pr_crit: -5 +ht: + KC: 0.000275 + KP: 0.000893 + KD: 0.46 +Pchamber: + setpt: + - 0.15 + dt_setpt: + - 1800.0 + ramp_rate: 0.5 +Tshelf: + min: -45 + max: 120 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 diff --git a/test_data/example_unknownrp.yaml b/test_data/example_unknownrp.yaml new file mode 100644 index 0000000..bf59099 --- /dev/null +++ b/test_data/example_unknownrp.yaml @@ -0,0 +1,36 @@ +sim: + tool: Primary Drying Calculator + Kv_known: true + Rp_known: false + Variable_Pch: false + Variable_Tsh: false +vial: + Av: 3.8 + Ap: 3.14 + Vfill: 2.0 +product: + cSolid: 0.05 + T_pr_crit: -5 +ht: + KC: 0.000275 + KP: 0.000893 + KD: 0.46 +Pchamber: + setpt: + - 0.15 + dt_setpt: + - 1800.0 + ramp_rate: 0.5 +Tshelf: + init: -33 + setpt: + - 10.0 + dt_setpt: + - 1800.0 + ramp_rate: 1.0 +dt: 0.01 +eq_cap: + a: -0.182 + b: 11.7 +nVial: 398 +product_temp_filename: ./test_data/temperature.txt diff --git a/tests/test_main.py b/tests/test_main.py index b24df72..1cafcaf 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -83,11 +83,69 @@ def test_unknownKv_fullstack(self, mocker, repo_root, tmp_path, capsys): assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + @pytest.mark.main + def test_unknownkv_edgecases(self, repo_root, capsys): + input_file = repo_root / "test_data" / "badexample_unknownkvrp.yaml" + inputs = read_inputs(input_file) + with pytest.raises(ValueError, match="Kv or Rp must be specified."): + execute_simulation(inputs) + + # Check that if bracket is below, returns max + inputs["sim"]["Rp_known"] = True + inputs["Kv_range"] = [1e-5, 2e-5] + with pytest.warns(UserWarning, match="bracket"): + output = execute_simulation(inputs) + assert_physically_reasonable_output(output) + captured = capsys.readouterr() + assert f"Optimal Kv: {2e-5}" in captured.out + + # Check that if bracket is above, returns min + inputs["sim"]["Rp_known"] = True + inputs["Kv_range"] = [1e-3, 2e-3] + with pytest.warns(UserWarning, match="bracket"): + output = execute_simulation(inputs) + assert_physically_reasonable_output(output) + captured = capsys.readouterr() + assert f"Optimal Kv: {1e-3}" in captured.out + + @pytest.mark.main + def test_unknown_rp_fullstack(self, mocker, repo_root, tmp_path, capsys): + """Test that this function is called from high-level API without errors.""" + input_file = repo_root / "test_data" / "example_unknownrp.yaml" + inputs = read_inputs(input_file) + data = np.loadtxt(repo_root / "test_data" / "temperature.txt") + inputs["time_data"] = data[:, 0] + inputs["temp_data"] = data[:, 1] + + mocked_func = mocker.patch("lyopronto.calc_unknownRp.dry", wraps=calc_unknownRp.dry) + + output = execute_simulation(inputs) + + assert mocked_func.call_count == 1 + + with chdir(tmp_path): + + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + assert (tmp_path / "lyo_Rp_data_testtime.csv").exists() + + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_Rp_Fit_testtime.pdf").exists() + assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() + assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() + assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + + @pytest.mark.main def test_design_space_fullstack(self, repo_root, tmp_path): input_file = repo_root / "test_data" / "example_design_space.yaml" + inputs = read_inputs(input_file) with chdir(tmp_path): - inputs = read_inputs(input_file) save_inputs(inputs, "testtime") assert (tmp_path / "lyopronto_input_testtime.yaml").exists() @@ -102,7 +160,77 @@ def test_design_space_fullstack(self, repo_root, tmp_path): assert (tmp_path / "lyo_DesignSpace_ProductTemperature_testtime.pdf").exists() assert (tmp_path / "lyo_DesignSpace_SublimationFlux_testtime.pdf").exists() assert (tmp_path / "lyo_DesignSpace_DryingTime_testtime.pdf").exists() + + def test_optimizer_novariable(self, repo_root, tmp_path): + input_file = repo_root / "test_data" / "badexample_optimizer_noopt.yaml" + with chdir(tmp_path): + inputs = read_inputs(input_file) + with pytest.raises(ValueError, match="Either Tsh or Pch needs to be variable to optimize."): + execute_simulation(inputs) + + + def test_opt_tsh_fullstack(self, mocker, repo_root, tmp_path, capsys): + input_file = repo_root / "test_data" / "example_opt_tsh.yaml" + mocked_func = mocker.patch("lyopronto.opt_Tsh.dry", wraps=opt_Tsh.dry, autospec=True) + with chdir(tmp_path): + inputs = read_inputs(input_file) + + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + output = execute_simulation(inputs) + assert mocked_func.call_count == 1 + + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() + assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() + assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + + def test_opt_pch_tsh_fullstack(self, mocker, repo_root, tmp_path, capsys): + input_file = repo_root / "test_data" / "example_opt_pch_tsh.yaml" + mocked_func = mocker.patch("lyopronto.opt_Pch_Tsh.dry", wraps=opt_Pch_Tsh.dry, autospec=True) + with chdir(tmp_path): + inputs = read_inputs(input_file) + + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + output = execute_simulation(inputs) + assert mocked_func.call_count == 1 # Should be called multiple times by rootfinder + + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() + assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() + assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + def test_opt_pch_fullstack(self, mocker, repo_root, tmp_path, capsys): + input_file = repo_root / "test_data" / "example_opt_pch.yaml" + mocked_func = mocker.patch("lyopronto.opt_Pch.dry", wraps=opt_Pch.dry, autospec=True) + with chdir(tmp_path): + inputs = read_inputs(input_file) + save_inputs(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.yaml").exists() + save_inputs_legacy(inputs, "testtime") + assert (tmp_path / "lyopronto_input_testtime.csv").exists() + + output = execute_simulation(inputs) + assert mocked_func.call_count == 1 # Should be called multiple times by rootfinder + save_csv(output, inputs, "testtime") + assert (tmp_path / "lyopronto_output_testtime.csv").exists() + + generate_visualizations(output, inputs, "testtime") + assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() + assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() + assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() \ No newline at end of file From 56a2cb642ab9433d12f63fe9917f8cb130e2b349 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 13:17:51 -0500 Subject: [PATCH 22/31] Check in most recent version of docs notebooks --- docs/examples/knownRp_PD.ipynb | 222 +++++++-------- docs/examples/unknownRp_PD.ipynb | 458 +++++++++++++++++++------------ 2 files changed, 392 insertions(+), 288 deletions(-) diff --git a/docs/examples/knownRp_PD.ipynb b/docs/examples/knownRp_PD.ipynb index 01fa9ca..8f5360e 100644 --- a/docs/examples/knownRp_PD.ipynb +++ b/docs/examples/knownRp_PD.ipynb @@ -5,10 +5,10 @@ "id": "5c17cc83", "metadata": { "papermill": { - "duration": 0.0054, - "end_time": "2026-01-26T22:17:17.475053", + "duration": 0.005311, + "end_time": "2026-02-03T17:50:58.122653", "exception": false, - "start_time": "2026-01-26T22:17:17.469653", + "start_time": "2026-02-03T17:50:58.117342", "status": "completed" }, "tags": [] @@ -22,10 +22,10 @@ "id": "f6f064bf", "metadata": { "papermill": { - "duration": 0.004984, - "end_time": "2026-01-26T22:17:17.485500", + "duration": 0.002819, + "end_time": "2026-02-03T17:50:58.130404", "exception": false, - "start_time": "2026-01-26T22:17:17.480516", + "start_time": "2026-02-03T17:50:58.127585", "status": "completed" }, "tags": [] @@ -42,16 +42,16 @@ "id": "63dabee9", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:17.503159Z", - "iopub.status.busy": "2026-01-26T22:17:17.502896Z", - "iopub.status.idle": "2026-01-26T22:17:17.507878Z", - "shell.execute_reply": "2026-01-26T22:17:17.506951Z" + "iopub.execute_input": "2026-02-03T17:50:58.138040Z", + "iopub.status.busy": "2026-02-03T17:50:58.137808Z", + "iopub.status.idle": "2026-02-03T17:50:58.141506Z", + "shell.execute_reply": "2026-02-03T17:50:58.140999Z" }, "papermill": { - "duration": 0.016044, - "end_time": "2026-01-26T22:17:17.509729", + "duration": 0.008794, + "end_time": "2026-02-03T17:50:58.142674", "exception": false, - "start_time": "2026-01-26T22:17:17.493685", + "start_time": "2026-02-03T17:50:58.133880", "status": "completed" }, "tags": [] @@ -67,10 +67,10 @@ "id": "8075c1de", "metadata": { "papermill": { - "duration": 0.005213, - "end_time": "2026-01-26T22:17:17.519514", + "duration": 0.004004, + "end_time": "2026-02-03T17:50:58.149685", "exception": false, - "start_time": "2026-01-26T22:17:17.514301", + "start_time": "2026-02-03T17:50:58.145681", "status": "completed" }, "tags": [] @@ -85,16 +85,16 @@ "id": "74b81b44", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:17.529913Z", - "iopub.status.busy": "2026-01-26T22:17:17.529633Z", - "iopub.status.idle": "2026-01-26T22:17:19.079158Z", - "shell.execute_reply": "2026-01-26T22:17:19.078648Z" + "iopub.execute_input": "2026-02-03T17:50:58.155618Z", + "iopub.status.busy": "2026-02-03T17:50:58.155363Z", + "iopub.status.idle": "2026-02-03T17:50:59.468813Z", + "shell.execute_reply": "2026-02-03T17:50:59.468214Z" }, "papermill": { - "duration": 1.557442, - "end_time": "2026-01-26T22:17:19.081467", + "duration": 1.317925, + "end_time": "2026-02-03T17:50:59.470087", "exception": false, - "start_time": "2026-01-26T22:17:17.524025", + "start_time": "2026-02-03T17:50:58.152162", "status": "completed" }, "tags": [] @@ -106,7 +106,7 @@ "from ruamel.yaml import YAML\n", "yaml = YAML()\n", "\n", - "import lyopronto as lp" + "from lyopronto import calc_knownRp, plot_styling" ] }, { @@ -114,10 +114,10 @@ "id": "eb24f0de", "metadata": { "papermill": { - "duration": 0.005147, - "end_time": "2026-01-26T22:17:19.094040", + "duration": 0.002857, + "end_time": "2026-02-03T17:50:59.476468", "exception": false, - "start_time": "2026-01-26T22:17:19.088893", + "start_time": "2026-02-03T17:50:59.473611", "status": "completed" }, "tags": [] @@ -132,16 +132,16 @@ "id": "6ce7b601", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:19.105577Z", - "iopub.status.busy": "2026-01-26T22:17:19.105260Z", - "iopub.status.idle": "2026-01-26T22:17:19.111930Z", - "shell.execute_reply": "2026-01-26T22:17:19.111419Z" + "iopub.execute_input": "2026-02-03T17:50:59.483395Z", + "iopub.status.busy": "2026-02-03T17:50:59.483038Z", + "iopub.status.idle": "2026-02-03T17:50:59.489444Z", + "shell.execute_reply": "2026-02-03T17:50:59.488954Z" }, "papermill": { - "duration": 0.014723, - "end_time": "2026-01-26T22:17:19.113954", + "duration": 0.011044, + "end_time": "2026-02-03T17:50:59.490387", "exception": false, - "start_time": "2026-01-26T22:17:19.099231", + "start_time": "2026-02-03T17:50:59.479343", "status": "completed" }, "tags": [] @@ -183,16 +183,16 @@ "id": "804ea772", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:19.126794Z", - "iopub.status.busy": "2026-01-26T22:17:19.126528Z", - "iopub.status.idle": "2026-01-26T22:17:19.129836Z", - "shell.execute_reply": "2026-01-26T22:17:19.129371Z" + "iopub.execute_input": "2026-02-03T17:50:59.497110Z", + "iopub.status.busy": "2026-02-03T17:50:59.496887Z", + "iopub.status.idle": "2026-02-03T17:50:59.500154Z", + "shell.execute_reply": "2026-02-03T17:50:59.499466Z" }, "papermill": { - "duration": 0.010293, - "end_time": "2026-01-26T22:17:19.131198", + "duration": 0.008209, + "end_time": "2026-02-03T17:50:59.501576", "exception": false, - "start_time": "2026-01-26T22:17:19.120905", + "start_time": "2026-02-03T17:50:59.493367", "status": "completed" }, "tags": [] @@ -220,16 +220,16 @@ "id": "9bf42168", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:19.144840Z", - "iopub.status.busy": "2026-01-26T22:17:19.144487Z", - "iopub.status.idle": "2026-01-26T22:17:19.149048Z", - "shell.execute_reply": "2026-01-26T22:17:19.148549Z" + "iopub.execute_input": "2026-02-03T17:50:59.509858Z", + "iopub.status.busy": "2026-02-03T17:50:59.509596Z", + "iopub.status.idle": "2026-02-03T17:50:59.513562Z", + "shell.execute_reply": "2026-02-03T17:50:59.512910Z" }, "papermill": { - "duration": 0.012617, - "end_time": "2026-01-26T22:17:19.151118", + "duration": 0.009891, + "end_time": "2026-02-03T17:50:59.514757", "exception": false, - "start_time": "2026-01-26T22:17:19.138501", + "start_time": "2026-02-03T17:50:59.504866", "status": "completed" }, "tags": [] @@ -273,10 +273,10 @@ "id": "15983737", "metadata": { "papermill": { - "duration": 0.005196, - "end_time": "2026-01-26T22:17:19.164126", + "duration": 0.002996, + "end_time": "2026-02-03T17:50:59.520692", "exception": false, - "start_time": "2026-01-26T22:17:19.158930", + "start_time": "2026-02-03T17:50:59.517696", "status": "completed" }, "tags": [] @@ -295,16 +295,16 @@ "id": "b7ea86bb", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:19.192072Z", - "iopub.status.busy": "2026-01-26T22:17:19.191631Z", - "iopub.status.idle": "2026-01-26T22:17:19.298497Z", - "shell.execute_reply": "2026-01-26T22:17:19.297844Z" + "iopub.execute_input": "2026-02-03T17:50:59.527948Z", + "iopub.status.busy": "2026-02-03T17:50:59.527702Z", + "iopub.status.idle": "2026-02-03T17:50:59.603705Z", + "shell.execute_reply": "2026-02-03T17:50:59.602688Z" }, "papermill": { - "duration": 0.116057, - "end_time": "2026-01-26T22:17:19.300480", + "duration": 0.082242, + "end_time": "2026-02-03T17:50:59.605839", "exception": false, - "start_time": "2026-01-26T22:17:19.184423", + "start_time": "2026-02-03T17:50:59.523597", "status": "completed" }, "tags": [] @@ -312,7 +312,7 @@ "outputs": [], "source": [ "\n", - "output_table = lp.calc_knownRp.dry(vial,product,ht,Pchamber,Tshelf,dt)\n" + "output_table = calc_knownRp.dry(vial,product,ht,Pchamber,Tshelf,dt)\n" ] }, { @@ -320,10 +320,10 @@ "id": "8903c791", "metadata": { "papermill": { - "duration": 0.006891, - "end_time": "2026-01-26T22:17:19.315538", + "duration": 0.005554, + "end_time": "2026-02-03T17:50:59.619446", "exception": false, - "start_time": "2026-01-26T22:17:19.308647", + "start_time": "2026-02-03T17:50:59.613892", "status": "completed" }, "tags": [] @@ -340,16 +340,16 @@ "id": "8876d895", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:19.330453Z", - "iopub.status.busy": "2026-01-26T22:17:19.330148Z", - "iopub.status.idle": "2026-01-26T22:17:19.334790Z", - "shell.execute_reply": "2026-01-26T22:17:19.333788Z" + "iopub.execute_input": "2026-02-03T17:50:59.632215Z", + "iopub.status.busy": "2026-02-03T17:50:59.631766Z", + "iopub.status.idle": "2026-02-03T17:50:59.638813Z", + "shell.execute_reply": "2026-02-03T17:50:59.637721Z" }, "papermill": { - "duration": 0.015284, - "end_time": "2026-01-26T22:17:19.337626", + "duration": 0.016571, + "end_time": "2026-02-03T17:50:59.640856", "exception": false, - "start_time": "2026-01-26T22:17:19.322342", + "start_time": "2026-02-03T17:50:59.624285", "status": "completed" }, "tags": [] @@ -391,10 +391,10 @@ "id": "950ffff3", "metadata": { "papermill": { - "duration": 0.00869, - "end_time": "2026-01-26T22:17:19.364797", + "duration": 0.004862, + "end_time": "2026-02-03T17:50:59.651043", "exception": false, - "start_time": "2026-01-26T22:17:19.356107", + "start_time": "2026-02-03T17:50:59.646181", "status": "completed" }, "tags": [] @@ -411,16 +411,16 @@ "id": "baff89b0", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:19.391035Z", - "iopub.status.busy": "2026-01-26T22:17:19.390533Z", - "iopub.status.idle": "2026-01-26T22:17:19.395772Z", - "shell.execute_reply": "2026-01-26T22:17:19.394933Z" + "iopub.execute_input": "2026-02-03T17:50:59.678688Z", + "iopub.status.busy": "2026-02-03T17:50:59.678265Z", + "iopub.status.idle": "2026-02-03T17:50:59.683311Z", + "shell.execute_reply": "2026-02-03T17:50:59.682544Z" }, "papermill": { - "duration": 0.022818, - "end_time": "2026-01-26T22:17:19.398853", + "duration": 0.029426, + "end_time": "2026-02-03T17:50:59.685356", "exception": false, - "start_time": "2026-01-26T22:17:19.376035", + "start_time": "2026-02-03T17:50:59.655930", "status": "completed" }, "tags": [] @@ -444,16 +444,16 @@ "id": "fd289577", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:19.421840Z", - "iopub.status.busy": "2026-01-26T22:17:19.421339Z", - "iopub.status.idle": "2026-01-26T22:17:20.718767Z", - "shell.execute_reply": "2026-01-26T22:17:20.718168Z" + "iopub.execute_input": "2026-02-03T17:50:59.696775Z", + "iopub.status.busy": "2026-02-03T17:50:59.696284Z", + "iopub.status.idle": "2026-02-03T17:51:01.217823Z", + "shell.execute_reply": "2026-02-03T17:51:01.216055Z" }, "papermill": { - "duration": 1.313014, - "end_time": "2026-01-26T22:17:20.722268", + "duration": 1.531547, + "end_time": "2026-02-03T17:51:01.220951", "exception": false, - "start_time": "2026-01-26T22:17:19.409254", + "start_time": "2026-02-03T17:50:59.689404", "status": "completed" }, "tags": [] @@ -461,7 +461,7 @@ "outputs": [ { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -478,8 +478,8 @@ "ax1.plot(output_table[:,0],output_table[:,4],'-o',color='b',markevery=5,linewidth=lineWidth, markersize=markerSize, label = \"Chamber Pressure\")\n", "ax2.plot(output_table[:,0],output_table[:,5],'-',color=[0,0.7,0.3],linewidth=lineWidth, label = \"Sublimation Flux\")\n", "\n", - "lp.plot_styling.axis_style_pressure(ax1)\n", - "lp.plot_styling.axis_style_subflux(ax2)\n", + "plot_styling.axis_style_pressure(ax1)\n", + "plot_styling.axis_style_subflux(ax2)\n", "\n", "plt.tight_layout()\n", "# figure_name = 'lyopronto_pressure_subflux_'+current_time+'.pdf'\n", @@ -493,16 +493,16 @@ "id": "1932f978", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:20.746128Z", - "iopub.status.busy": "2026-01-26T22:17:20.745742Z", - "iopub.status.idle": "2026-01-26T22:17:21.519399Z", - "shell.execute_reply": "2026-01-26T22:17:21.518875Z" + "iopub.execute_input": "2026-02-03T17:51:01.240180Z", + "iopub.status.busy": "2026-02-03T17:51:01.239782Z", + "iopub.status.idle": "2026-02-03T17:51:02.127708Z", + "shell.execute_reply": "2026-02-03T17:51:02.127058Z" }, "papermill": { - "duration": 0.791135, - "end_time": "2026-01-26T22:17:21.522597", + "duration": 0.899538, + "end_time": "2026-02-03T17:51:02.129469", "exception": false, - "start_time": "2026-01-26T22:17:20.731462", + "start_time": "2026-02-03T17:51:01.229931", "status": "completed" }, "tags": [] @@ -523,7 +523,7 @@ "\n", "fig = plt.figure(0,figsize=(figwidth,figheight))\n", "ax = fig.add_subplot(1,1,1)\n", - "lp.plot_styling.axis_style_percdried(ax)\n", + "plot_styling.axis_style_percdried(ax)\n", "ax.plot(output_table[:,0],output_table[:,-1],'-k',linewidth=lineWidth, label = \"Percent Dried\")\n", "plt.tight_layout()\n", "# figure_name = 'lyopronto_percentdried_'+current_time+'.pdf'\n", @@ -537,16 +537,16 @@ "id": "db6d2df5", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:21.552289Z", - "iopub.status.busy": "2026-01-26T22:17:21.552034Z", - "iopub.status.idle": "2026-01-26T22:17:22.418782Z", - "shell.execute_reply": "2026-01-26T22:17:22.417861Z" + "iopub.execute_input": "2026-02-03T17:51:02.146905Z", + "iopub.status.busy": "2026-02-03T17:51:02.146647Z", + "iopub.status.idle": "2026-02-03T17:51:03.124635Z", + "shell.execute_reply": "2026-02-03T17:51:03.123979Z" }, "papermill": { - "duration": 0.887179, - "end_time": "2026-01-26T22:17:22.421504", + "duration": 0.989718, + "end_time": "2026-02-03T17:51:03.127613", "exception": false, - "start_time": "2026-01-26T22:17:21.534325", + "start_time": "2026-02-03T17:51:02.137895", "status": "completed" }, "tags": [] @@ -567,7 +567,7 @@ "\n", "fig = plt.figure(0,figsize=(figwidth,figheight))\n", "ax = fig.add_subplot(1,1,1)\n", - "lp.plot_styling.axis_style_temperature(ax)\n", + "plot_styling.axis_style_temperature(ax)\n", "ax.plot(output_table[:,0],output_table[:,1],'-b',linewidth=lineWidth, label = \"Sublimation Front Temperature\")\n", "ax.plot(output_table[:,0],output_table[:,2],'-r',linewidth=lineWidth, label = \"Maximum Product Temperature\")\n", "ax.plot(output_table[:,0],output_table[:,3],'-o',color='k',markevery=5,linewidth=lineWidth, markersize=markerSize, label = \"Shelf Temperature\")\n", @@ -585,7 +585,7 @@ "kernelspec": { "display_name": "lyopronto", "language": "python", - "name": "python" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -601,14 +601,14 @@ }, "papermill": { "default_parameters": {}, - "duration": 8.583172, - "end_time": "2026-01-26T22:17:22.897204", + "duration": 8.756554, + "end_time": "2026-02-03T17:51:03.925209", "environment_variables": {}, "exception": null, - "input_path": "C:\\Users\\iwheeler\\OneDrive - purdue.edu\\Documents\\01_Projects\\LyoPronto_dev\\docs\\examples\\knownRp_PD.ipynb", - "output_path": "C:\\Users\\iwheeler\\OneDrive - purdue.edu\\Documents\\01_Projects\\LyoPronto_dev\\docs\\examples\\knownRp_PD.ipynb", + "input_path": ".\\docs\\examples\\knownRp_PD.ipynb", + "output_path": ".\\docs\\examples\\knownRp_PD.ipynb", "parameters": {}, - "start_time": "2026-01-26T22:17:14.314032", + "start_time": "2026-02-03T17:50:55.168655", "version": "2.6.0" } }, diff --git a/docs/examples/unknownRp_PD.ipynb b/docs/examples/unknownRp_PD.ipynb index 24b09db..2726aeb 100644 --- a/docs/examples/unknownRp_PD.ipynb +++ b/docs/examples/unknownRp_PD.ipynb @@ -1,26 +1,14 @@ { "cells": [ - { - "cell_type": "markdown", - "id": "873006c1", - "metadata": { - "tags": [ - "papermill-error-cell-tag" - ] - }, - "source": [ - "An Exception was encountered at 'In [4]'." - ] - }, { "cell_type": "markdown", "id": "a9a4ea4e", "metadata": { "papermill": { - "duration": 0.006262, - "end_time": "2026-01-26T22:17:24.778535", + "duration": 0.00303, + "end_time": "2026-02-03T17:46:45.398519", "exception": false, - "start_time": "2026-01-26T22:17:24.772273", + "start_time": "2026-02-03T17:46:45.395489", "status": "completed" }, "tags": [] @@ -35,16 +23,16 @@ "id": "df3ebedc", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:24.791798Z", - "iopub.status.busy": "2026-01-26T22:17:24.791502Z", - "iopub.status.idle": "2026-01-26T22:17:24.796453Z", - "shell.execute_reply": "2026-01-26T22:17:24.795408Z" + "iopub.execute_input": "2026-02-03T17:46:45.405870Z", + "iopub.status.busy": "2026-02-03T17:46:45.405657Z", + "iopub.status.idle": "2026-02-03T17:46:45.410316Z", + "shell.execute_reply": "2026-02-03T17:46:45.409485Z" }, "papermill": { - "duration": 0.014568, - "end_time": "2026-01-26T22:17:24.798348", + "duration": 0.00988, + "end_time": "2026-02-03T17:46:45.411484", "exception": false, - "start_time": "2026-01-26T22:17:24.783780", + "start_time": "2026-02-03T17:46:45.401604", "status": "completed" }, "tags": [] @@ -66,16 +54,16 @@ "id": "1c0e2019", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:24.809892Z", - "iopub.status.busy": "2026-01-26T22:17:24.809625Z", - "iopub.status.idle": "2026-01-26T22:17:26.158243Z", - "shell.execute_reply": "2026-01-26T22:17:26.157370Z" + "iopub.execute_input": "2026-02-03T17:46:45.417966Z", + "iopub.status.busy": "2026-02-03T17:46:45.417745Z", + "iopub.status.idle": "2026-02-03T17:46:46.716075Z", + "shell.execute_reply": "2026-02-03T17:46:46.715457Z" }, "papermill": { - "duration": 1.357261, - "end_time": "2026-01-26T22:17:26.160325", + "duration": 1.302929, + "end_time": "2026-02-03T17:46:46.717294", "exception": false, - "start_time": "2026-01-26T22:17:24.803064", + "start_time": "2026-02-03T17:46:45.414365", "status": "completed" }, "tags": [] @@ -84,14 +72,10 @@ "source": [ "from scipy.optimize import curve_fit\n", "import numpy as np\n", - "import csv\n", "import matplotlib.pyplot as plt\n", "from matplotlib import rc as matplotlibrc\n", - "import time\n", "\n", - "# from lyopronto.calc_unknownRp import dry\n", - "\n", - "from lyopronto import *" + "from lyopronto import calc_unknownRp, plot_styling" ] }, { @@ -100,16 +84,16 @@ "id": "3b2f6e09", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:26.174445Z", - "iopub.status.busy": "2026-01-26T22:17:26.174096Z", - "iopub.status.idle": "2026-01-26T22:17:26.181160Z", - "shell.execute_reply": "2026-01-26T22:17:26.180560Z" + "iopub.execute_input": "2026-02-03T17:46:46.724398Z", + "iopub.status.busy": "2026-02-03T17:46:46.724095Z", + "iopub.status.idle": "2026-02-03T17:46:46.729016Z", + "shell.execute_reply": "2026-02-03T17:46:46.728417Z" }, "papermill": { - "duration": 0.016198, - "end_time": "2026-01-26T22:17:26.182803", + "duration": 0.009515, + "end_time": "2026-02-03T17:46:46.730088", "exception": false, - "start_time": "2026-01-26T22:17:26.166605", + "start_time": "2026-02-03T17:46:46.720573", "status": "completed" }, "tags": [] @@ -122,8 +106,6 @@ "\n", "######################## Inputs ########################\n", "\n", - "sim = dict([('tool','Primary Drying Calculator'),('Kv_known','Y'),('Rp_known','N'),('Variable_Pch','N'),('Variable_Tsh','N')])\n", - "\n", "# Vial and fill properties\n", "# Av = Vial area in cm^2\n", "# Ap = Product Area in cm^2\n", @@ -131,43 +113,28 @@ "vial = dict([('Av',3.80),('Ap',3.14),('Vfill',2.0)])\n", "\n", "#Product properties\n", - "# cSolid = Fractional concentration of solute in the frozen solution\n", - "# Tpr0 = Initial product temperature for freezing in degC\n", - "# Tf = Freezing temperature in degC\n", - "# Tn = Nucleation temperature in degC\n", - "# Product Resistance Parameters\n", - "# R0 in cm^2-hr-Torr/g, A1 in cm-hr-Torr/g, A2 in 1/cm\n", - "product = dict([('cSolid',0.05)])\n", - "# Critical product temperature\n", - "# At least 2 to 3 deg C below collapse or glass transition temperature\n", - "product['T_pr_crit'] = -5 # in degC\n", + "product = {\n", + " 'cSolid':0.05, # Concentration of solute in the frozen solution\n", + " 'T_pr_crit':-5.0, # Critical product temperature in degC\n", + " }\n", "\n", "# Vial Heat Transfer Parameters\n", "# Kv = KC + KP*Pch/(1+KD*Pch) \n", "# KC in cal/s/K/cm^2, KP in cal/s/K/cm^2/Torr, KD in 1/Torr\n", - "ht = dict([('KC',2.75e-4),('KP',8.93e-4),('KD',0.46)])\n", + "ht = {'KC': 2.75e-4, 'KP': 8.93e-4, 'KD': 0.46}\n", "\n", "# Chamber Pressure\n", - "Pchamber = dict([('setpt',[0.15]),('dt_setpt',[1800.0]),('ramp_rate',0.5)])\n", + "# setpt = Chamber pressure set points in Torr\n", + "# dt_setpt = Time for which chamber pressure set points are held in min, including ramp time\n", + "# ramp_rate = Chamber pressure ramping rate in Torr/min\n", + "Pchamber = {'setpt':[0.15],'dt_setpt':[1800.0],'ramp_rate':0.5}\n", "\n", "# Shelf Temperature\n", "# init = Intial shelf temperature in C\n", "# setpt = Shelf temperature set points in C\n", - "# dt_setpt = Time for which shelf temperature set points are held in min\n", + "# dt_setpt = Time for which shelf temperature set points are held in min, including ramp time\n", "# ramp_rate = Shelf temperature ramping rate in C/min\n", - "Tshelf = dict([('init',-35.0),('setpt',[20.0]),('dt_setpt',[1800.0]),('ramp_rate',1.0)])\n", - "\n", - "# Time step\n", - "dt = 0.01 # hr\n", - "\n", - "# Lyophilizer equipment capability\n", - "# Form: dm/dt [kg/hr] = a + b * Pch [Torr]\n", - "# a in kg/hr, b in kg/hr/Torr \n", - "eq_cap = dict([('a',-0.182),('b',0.0117e3)])\n", - "\n", - "# Equipment load\n", - "nVial = 398 # Number of vials\n", - "\n" + "Tshelf = {'init': -35.0, 'setpt': [20.0], 'dt_setpt': [1800.0], 'ramp_rate': 1.0}" ] }, { @@ -175,10 +142,10 @@ "id": "e67797f0", "metadata": { "papermill": { - "duration": 0.00521, - "end_time": "2026-01-26T22:17:26.193023", + "duration": 0.003079, + "end_time": "2026-02-03T17:46:46.736227", "exception": false, - "start_time": "2026-01-26T22:17:26.187813", + "start_time": "2026-02-03T17:46:46.733148", "status": "completed" }, "tags": [] @@ -191,41 +158,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "7679c0d6", "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T22:17:26.209894Z", - "iopub.status.busy": "2026-01-26T22:17:26.209604Z", - "iopub.status.idle": "2026-01-26T22:17:26.959761Z", - "shell.execute_reply": "2026-01-26T22:17:26.958611Z" + "iopub.execute_input": "2026-02-03T17:46:46.742830Z", + "iopub.status.busy": "2026-02-03T17:46:46.742608Z", + "iopub.status.idle": "2026-02-03T17:46:46.745359Z", + "shell.execute_reply": "2026-02-03T17:46:46.744771Z" }, "papermill": { - "duration": 0.75913, - "end_time": "2026-01-26T22:17:26.961559", - "exception": true, - "start_time": "2026-01-26T22:17:26.202429", - "status": "failed" + "duration": 0.007601, + "end_time": "2026-02-03T17:46:46.746684", + "exception": false, + "start_time": "2026-02-03T17:46:46.739083", + "status": "completed" }, - "tags": ["parameters"] + "tags": [ + "parameters" + ] }, - "outputs": [ - { - "ename": "FileNotFoundError", - "evalue": "./temperature.txt not found.", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mFileNotFoundError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m product_temp_filename = \u001b[33m'\u001b[39m\u001b[33m./temperature.txt\u001b[39m\u001b[33m'\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m dat = \u001b[43mnp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mloadtxt\u001b[49m\u001b[43m(\u001b[49m\u001b[43mproduct_temp_filename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 3\u001b[39m time = dat[:,\u001b[32m0\u001b[39m]\n\u001b[32m 4\u001b[39m Tbot_exp = dat[:,\u001b[32m1\u001b[39m]\n", - "\u001b[36mFile \u001b[39m\u001b[32m~\\Miniconda3\\envs\\lyopronto\\Lib\\site-packages\\numpy\\lib\\_npyio_impl.py:1397\u001b[39m, in \u001b[36mloadtxt\u001b[39m\u001b[34m(fname, dtype, comments, delimiter, converters, skiprows, usecols, unpack, ndmin, encoding, max_rows, quotechar, like)\u001b[39m\n\u001b[32m 1394\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(delimiter, \u001b[38;5;28mbytes\u001b[39m):\n\u001b[32m 1395\u001b[39m delimiter = delimiter.decode(\u001b[33m'\u001b[39m\u001b[33mlatin1\u001b[39m\u001b[33m'\u001b[39m)\n\u001b[32m-> \u001b[39m\u001b[32m1397\u001b[39m arr = \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcomment\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcomment\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdelimiter\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdelimiter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1398\u001b[39m \u001b[43m \u001b[49m\u001b[43mconverters\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconverters\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mskiplines\u001b[49m\u001b[43m=\u001b[49m\u001b[43mskiprows\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43musecols\u001b[49m\u001b[43m=\u001b[49m\u001b[43musecols\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1399\u001b[39m \u001b[43m \u001b[49m\u001b[43munpack\u001b[49m\u001b[43m=\u001b[49m\u001b[43munpack\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mndmin\u001b[49m\u001b[43m=\u001b[49m\u001b[43mndmin\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1400\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_rows\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_rows\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquote\u001b[49m\u001b[43m=\u001b[49m\u001b[43mquotechar\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1402\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m arr\n", - "\u001b[36mFile \u001b[39m\u001b[32m~\\Miniconda3\\envs\\lyopronto\\Lib\\site-packages\\numpy\\lib\\_npyio_impl.py:1024\u001b[39m, in \u001b[36m_read\u001b[39m\u001b[34m(fname, delimiter, comment, quote, imaginary_unit, usecols, skiplines, max_rows, converters, ndmin, unpack, dtype, encoding)\u001b[39m\n\u001b[32m 1022\u001b[39m fname = os.fspath(fname)\n\u001b[32m 1023\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(fname, \u001b[38;5;28mstr\u001b[39m):\n\u001b[32m-> \u001b[39m\u001b[32m1024\u001b[39m fh = \u001b[43mnp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mlib\u001b[49m\u001b[43m.\u001b[49m\u001b[43m_datasource\u001b[49m\u001b[43m.\u001b[49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mrt\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencoding\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1025\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m encoding \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m 1026\u001b[39m encoding = \u001b[38;5;28mgetattr\u001b[39m(fh, \u001b[33m'\u001b[39m\u001b[33mencoding\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33mlatin1\u001b[39m\u001b[33m'\u001b[39m)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~\\Miniconda3\\envs\\lyopronto\\Lib\\site-packages\\numpy\\lib\\_datasource.py:192\u001b[39m, in \u001b[36mopen\u001b[39m\u001b[34m(path, mode, destpath, encoding, newline)\u001b[39m\n\u001b[32m 155\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 156\u001b[39m \u001b[33;03mOpen `path` with `mode` and return the file object.\u001b[39;00m\n\u001b[32m 157\u001b[39m \n\u001b[32m (...)\u001b[39m\u001b[32m 188\u001b[39m \n\u001b[32m 189\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 191\u001b[39m ds = DataSource(destpath)\n\u001b[32m--> \u001b[39m\u001b[32m192\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mds\u001b[49m\u001b[43m.\u001b[49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[43m=\u001b[49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnewline\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnewline\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~\\Miniconda3\\envs\\lyopronto\\Lib\\site-packages\\numpy\\lib\\_datasource.py:529\u001b[39m, in \u001b[36mDataSource.open\u001b[39m\u001b[34m(self, path, mode, encoding, newline)\u001b[39m\n\u001b[32m 526\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m _file_openers[ext](found, mode=mode,\n\u001b[32m 527\u001b[39m encoding=encoding, newline=newline)\n\u001b[32m 528\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m529\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m not found.\u001b[39m\u001b[33m\"\u001b[39m)\n", - "\u001b[31mFileNotFoundError\u001b[39m: ./temperature.txt not found." - ] - } - ], + "outputs": [], "source": [ "data_path = Path('.')\n", "product_temp_filename = 'temperature.txt'" @@ -233,9 +186,52 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, + "id": "2adc2b3a", + "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:46.754877Z", + "iopub.status.busy": "2026-02-03T17:46:46.754651Z", + "iopub.status.idle": "2026-02-03T17:46:46.757347Z", + "shell.execute_reply": "2026-02-03T17:46:46.756840Z" + }, + "papermill": { + "duration": 0.007672, + "end_time": "2026-02-03T17:46:46.758643", + "exception": false, + "start_time": "2026-02-03T17:46:46.750971", + "status": "completed" + }, + "tags": [ + "injected-parameters" + ] + }, + "outputs": [], + "source": [ + "# Parameters\n", + "data_path = \"./docs/examples/\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, "id": "86d98194", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:46.766199Z", + "iopub.status.busy": "2026-02-03T17:46:46.765984Z", + "iopub.status.idle": "2026-02-03T17:46:46.770101Z", + "shell.execute_reply": "2026-02-03T17:46:46.769598Z" + }, + "papermill": { + "duration": 0.008723, + "end_time": "2026-02-03T17:46:46.771442", + "exception": false, + "start_time": "2026-02-03T17:46:46.762719", + "status": "completed" + }, + "tags": [] + }, "outputs": [], "source": [ "dat = np.loadtxt(data_path + product_temp_filename)\n", @@ -248,11 +244,11 @@ "id": "81f6f69e", "metadata": { "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 0.002758, + "end_time": "2026-02-03T17:46:46.778355", + "exception": false, + "start_time": "2026-02-03T17:46:46.775597", + "status": "completed" }, "tags": [] }, @@ -262,15 +258,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "0a712084", "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:46.785766Z", + "iopub.status.busy": "2026-02-03T17:46:46.785552Z", + "iopub.status.idle": "2026-02-03T17:46:46.830386Z", + "shell.execute_reply": "2026-02-03T17:46:46.829536Z" + }, "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 0.051329, + "end_time": "2026-02-03T17:46:46.832255", + "exception": false, + "start_time": "2026-02-03T17:46:46.780926", + "status": "completed" }, "tags": [] }, @@ -285,11 +287,11 @@ "id": "6ee616c8", "metadata": { "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 0.007582, + "end_time": "2026-02-03T17:46:46.846669", + "exception": false, + "start_time": "2026-02-03T17:46:46.839087", + "status": "completed" }, "tags": [] }, @@ -300,25 +302,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "27650e63", "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:46.858537Z", + "iopub.status.busy": "2026-02-03T17:46:46.858224Z", + "iopub.status.idle": "2026-02-03T17:46:46.870202Z", + "shell.execute_reply": "2026-02-03T17:46:46.869003Z" + }, "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 0.021549, + "end_time": "2026-02-03T17:46:46.873061", + "exception": false, + "start_time": "2026-02-03T17:46:46.851512", + "status": "completed" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R0 = 0.020892795981931313\n", + "A1 = 7.843317809906947\n", + "A2 = 0.50813989753207\n" + ] + } + ], "source": [ "\n", "params,params_covariance = curve_fit(lambda h,r,a1,a2: r+h*a1/(1+h*a2),product_res[:,1],product_res[:,2],p0=[1.0,0.0,0.0])\n", - "print(\"R0 = \"+str(params[0])+\"\\n\")\n", - "print(\"A1 = \"+str(params[1])+\"\\n\")\n", - "print(\"A2 = \"+str(params[2])+\"\\n\")\n", + "print(f\"R0 = {params[0]}\")\n", + "print(f\"A1 = {params[1]}\")\n", + "print(f\"A2 = {params[2]}\")\n", "#################\n", "\n", "##########################\n" @@ -326,15 +344,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "bf31e3ea", "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:46.890068Z", + "iopub.status.busy": "2026-02-03T17:46:46.889655Z", + "iopub.status.idle": "2026-02-03T17:46:46.896242Z", + "shell.execute_reply": "2026-02-03T17:46:46.895326Z" + }, "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 0.017093, + "end_time": "2026-02-03T17:46:46.898017", + "exception": false, + "start_time": "2026-02-03T17:46:46.880924", + "status": "completed" }, "tags": [] }, @@ -357,11 +381,11 @@ "id": "949b0ccc", "metadata": { "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 0.006458, + "end_time": "2026-02-03T17:46:46.909938", + "exception": false, + "start_time": "2026-02-03T17:46:46.903480", + "status": "completed" }, "tags": [] }, @@ -371,19 +395,46 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "04ef9ba7", "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:46.920940Z", + "iopub.status.busy": "2026-02-03T17:46:46.920453Z", + "iopub.status.idle": "2026-02-03T17:46:48.106847Z", + "shell.execute_reply": "2026-02-03T17:46:48.106212Z" + }, "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 1.193905, + "end_time": "2026-02-03T17:46:48.109108", + "exception": false, + "start_time": "2026-02-03T17:46:46.915203", + "status": "completed" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig = plt.figure(0,figsize=(figwidth,figheight))\n", "ax = fig.add_subplot(111)\n", @@ -395,19 +446,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "8337a2d9", "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:48.122392Z", + "iopub.status.busy": "2026-02-03T17:46:48.122137Z", + "iopub.status.idle": "2026-02-03T17:46:49.149705Z", + "shell.execute_reply": "2026-02-03T17:46:49.149233Z" + }, "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 1.037541, + "end_time": "2026-02-03T17:46:49.152621", + "exception": false, + "start_time": "2026-02-03T17:46:48.115080", + "status": "completed" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "\n", "fig = plt.figure(0,figsize=(figwidth,figheight))\n", @@ -424,19 +492,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "e17ebb7c", "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:49.171599Z", + "iopub.status.busy": "2026-02-03T17:46:49.171360Z", + "iopub.status.idle": "2026-02-03T17:46:50.030366Z", + "shell.execute_reply": "2026-02-03T17:46:50.029565Z" + }, "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 0.870907, + "end_time": "2026-02-03T17:46:50.032635", + "exception": false, + "start_time": "2026-02-03T17:46:49.161728", + "status": "completed" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "\n", "fig = plt.figure(0,figsize=(figwidth,figheight))\n", @@ -451,19 +536,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "04ed5deb", "metadata": { + "execution": { + "iopub.execute_input": "2026-02-03T17:46:50.060419Z", + "iopub.status.busy": "2026-02-03T17:46:50.060167Z", + "iopub.status.idle": "2026-02-03T17:46:51.095915Z", + "shell.execute_reply": "2026-02-03T17:46:51.095192Z" + }, "papermill": { - "duration": null, - "end_time": null, - "exception": null, - "start_time": null, - "status": "pending" + "duration": 1.052436, + "end_time": "2026-02-03T17:46:51.099002", + "exception": false, + "start_time": "2026-02-03T17:46:50.046566", + "status": "completed" }, "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "\n", "fig = plt.figure(0,figsize=(figwidth,figheight))\n", @@ -484,7 +586,7 @@ ], "metadata": { "kernelspec": { - "display_name": "lyo-docs", + "display_name": "lyopronto", "language": "python", "name": "python3" }, @@ -498,21 +600,23 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.5" + "version": "3.13.11" }, "papermill": { "default_parameters": {}, - "duration": 4.468264, - "end_time": "2026-01-26T22:17:27.419267", + "duration": 9.165519, + "end_time": "2026-02-03T17:46:51.788903", "environment_variables": {}, - "exception": true, - "input_path": "C:\\Users\\iwheeler\\OneDrive - purdue.edu\\Documents\\01_Projects\\LyoPronto_dev\\docs\\examples\\unknownRp_PD.ipynb", - "output_path": "C:\\Users\\iwheeler\\OneDrive - purdue.edu\\Documents\\01_Projects\\LyoPronto_dev\\docs\\examples\\unknownRp_PD.ipynb", - "parameters": {}, - "start_time": "2026-01-26T22:17:22.951003", + "exception": null, + "input_path": ".\\docs\\examples\\unknownRp_PD.ipynb", + "output_path": ".\\docs\\examples\\unknownRp_PD.ipynb", + "parameters": { + "data_path": "./docs/examples/" + }, + "start_time": "2026-02-03T17:46:42.623384", "version": "2.6.0" } }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file From be36ef6eaba60f8ae11576de557dc5d3db600726 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 13:36:42 -0500 Subject: [PATCH 23/31] Update the main script for clarity --- main.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/main.py b/main.py index fd4c99a..efb0ac7 100644 --- a/main.py +++ b/main.py @@ -16,7 +16,6 @@ # You should have received a copy of the GNU General Public License # along with this program. If not, see . -import sys import numpy as np @@ -52,7 +51,7 @@ # For 'Optimizer': Kv and Rp must be known, Tpr_crit must be provided # Can use variable Pch and/or Tsh sim = { - "tool": "Design Space Generator", + "tool": "Primary Drying Calculator", "Kv_known": True, "Rp_known": True, "Variable_Pch": False, @@ -102,7 +101,7 @@ # KC in cal/s/K/cm^2, KP in cal/s/K/cm^2/Torr, KD in 1/Torr ht = {"KC": 2.75e-4, "KP": 8.93e-4, "KD": 0.46} elif not sim["Kv_known"]: - Kv_range = np.array([5.0, 20.0]) * 1e-4 # cal/s/K/cm^2, lower & upper bounds + Kv_range = [1.0e-4, 2.0e-3] # cal/s/K/cm^2, lower & upper bounds # Primary drying time t_dry_exp = 12.62 # in hr From b51e1c7a54a408a3f8b48d5e66df618c0b95bf25 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 14:01:46 -0500 Subject: [PATCH 24/31] Minor cleanups, prompted in part by Copilot --- lyopronto/design_space.py | 5 +++-- lyopronto/high_level.py | 31 +++++++++++++++++++++---------- tests/test_calc_unknownRp.py | 5 ++--- tests/test_main.py | 14 +++++++++++++- 4 files changed, 39 insertions(+), 16 deletions(-) diff --git a/lyopronto/design_space.py b/lyopronto/design_space.py index 46d71e3..f6236de 100644 --- a/lyopronto/design_space.py +++ b/lyopronto/design_space.py @@ -41,13 +41,14 @@ def dry(vial,product,ht,Pchamber,Tshelf,dt,eq_cap,nVial): ndarray: table of results for product isotherms ndarray: table of results for equipment capability curve - Each of the returns has 5 rows corresponding to: + The first two returns have 5 rows corresponding to: - Maximum product temperature in degC - Primary drying time in hr - Average sublimation flux in kg/hr/m^2 - Maximum/minimum sublimation flux in kg/hr/m^2 - Sublimation flux at the end of primary drying in kg/hr/m^2 - (noting that for equipment capability, average, maximum, and end sublimation fluxes are identical) + The third return has 3 rows corresponding to the first three of that list. + With nT setpoints in Tshelf['setpt'] and nP setpoints in Pchamber['setpt'], the returned arrays have the following shapes: - Shelf isotherms: (5, nT, nP) array - Product isotherms: (5, 2) array (for the lowest and highest Pchamber setpoints) diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index 7d2d7bc..e87505d 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -56,7 +56,7 @@ def execute_simulation(inputs): "With the current implementation, either Kv or Rp must be specified." ) - elif sim_type == "Design Space Generator": + elif sim_type == "Design Space Generator" or sim_type == "Design-Space-Generator": output_data = design_space.dry( inputs["vial"], inputs["product"], @@ -71,6 +71,13 @@ def execute_simulation(inputs): elif sim_type == "Optimizer": output_data = _run_optimizer(inputs) + else: + raise ValueError( + f"Invalid simulation tool {sim_type} selected." + " Valid options are: 'Freezing Calculator', 'Primary Drying Calculator', ", + "'Design Space Generator', 'Optimizer'." + ) + return output_data @@ -90,18 +97,20 @@ def obj(Kc): simulated_time = output[-1, 0] return simulated_time - inputs["t_dry_exp"] - if obj(Kv_range[0]) * obj(Kv_range[-1]) > 0: + lb_obj = obj(Kv_range[0]) + ub_obj = obj(Kv_range[-1]) + if lb_obj * ub_obj > 0: warn( "Given Kv bounds do not bracket the most likely value. Choosing either min or max." ) - if abs(obj(Kv_range[0])) < abs(obj(Kv_range[-1])): + if abs(lb_obj) < abs(ub_obj): best_Kv = Kv_range[0] else: best_Kv = Kv_range[-1] else: best_Kv = brentq(obj, Kv_range[0], Kv_range[-1]) - deviation = obj(best_Kv) + deviation = abs(obj(best_Kv)) / inputs["t_dry_exp"] * 100 output = calc_knownRp.dry( inputs["vial"], inputs["product"], @@ -296,9 +305,9 @@ def read_inputs(filename): inputs = yaml.load(yamlfile) if "product_temp_filename" in inputs: print( - "Note: input specifies a product temperature data file." - + "This data should be loaded separately and added to the inputs dictionary" - + "as `time_data` and `temp_data`." + "Note: input specifies a product temperature data file. " + + "This data should be loaded separately and added to the inputs " + + "dictionary as `time_data` and `temp_data`." ) return inputs finally: @@ -333,7 +342,7 @@ def save_csv(output_data, inputs, timestamp): np.savetxt(rpfile, output_data[1], delimiter=", ", header=header) data = output_data[0] else: - data = output_data # for all but unknown Rp, output_data is the only return + data = output_data # for all but unknown Rp, output_data is the only return header = ",".join( [ @@ -434,9 +443,9 @@ def generate_visualizations(output_data, inputs, timestamp): elif tool in ["Primary Drying Calculator", "Optimizer"]: if tool == "Primary Drying Calculator" and not inputs["sim"]["Rp_known"]: _plot_rp_results(output_data, figure_props, timestamp) - data = output_data[0] # There are extra returns for Rp fitting + data = output_data[0] # There are extra returns for Rp fitting else: - data = output_data # for all but unknown Rp, output_data is the only return + data = output_data # for all but unknown Rp, output_data is the only return _plot_drying_results(data, figure_props, timestamp) elif tool == "Design Space Generator": _plot_design_space(output_data, inputs, figure_props, timestamp) @@ -547,6 +556,7 @@ def _plot_drying_results(data, props, timestamp): plt.savefig(f"lyo_Temperatures_{timestamp}.pdf") plt.close() + def _plot_rp_results(data, props, timestamp): product_res = data[1] params = data[2] @@ -578,6 +588,7 @@ def _plot_rp_results(data, props, timestamp): plt.savefig(f"lyo_Rp_Fit_{timestamp}.pdf") plt.close() + def _plot_design_space(data, inputs, props, timestamp): """Generate design space boundary visualization.""" # Implementation for design space plotting diff --git a/tests/test_calc_unknownRp.py b/tests/test_calc_unknownRp.py index d2ecb8f..22ba813 100644 --- a/tests/test_calc_unknownRp.py +++ b/tests/test_calc_unknownRp.py @@ -155,7 +155,6 @@ def test_main_unknown_rp(self, mocker, standard_inputs_nodt, temperature_data): "Rp_known": False,} vial, product, ht, Pchamber, Tshelf = standard_inputs_nodt time_data, temp_data = temperature_data - print(time_data[-1]) mocked_func = mocker.patch("lyopronto.calc_unknownRp.dry", wraps=calc_unknownRp.dry) inputs = {"sim": sim,} @@ -167,8 +166,8 @@ def test_main_unknown_rp(self, mocker, standard_inputs_nodt, temperature_data): mocked_func.assert_called_once_with(vial, product, ht, Pchamber, Tshelf, time_data, temp_data) - assert_physically_reasonable_output(output) - assert_incomplete_drying(output) + assert_physically_reasonable_output(output[0]) + assert_incomplete_drying(output[0]) class TestCalcUnknownRpEdgeCases: diff --git a/tests/test_main.py b/tests/test_main.py index 1cafcaf..b357f3f 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -161,6 +161,7 @@ def test_design_space_fullstack(self, repo_root, tmp_path): assert (tmp_path / "lyo_DesignSpace_SublimationFlux_testtime.pdf").exists() assert (tmp_path / "lyo_DesignSpace_DryingTime_testtime.pdf").exists() + @pytest.mark.main def test_optimizer_novariable(self, repo_root, tmp_path): input_file = repo_root / "test_data" / "badexample_optimizer_noopt.yaml" with chdir(tmp_path): @@ -169,6 +170,7 @@ def test_optimizer_novariable(self, repo_root, tmp_path): execute_simulation(inputs) + @pytest.mark.main def test_opt_tsh_fullstack(self, mocker, repo_root, tmp_path, capsys): input_file = repo_root / "test_data" / "example_opt_tsh.yaml" mocked_func = mocker.patch("lyopronto.opt_Tsh.dry", wraps=opt_Tsh.dry, autospec=True) @@ -191,6 +193,7 @@ def test_opt_tsh_fullstack(self, mocker, repo_root, tmp_path, capsys): assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + @pytest.mark.main def test_opt_pch_tsh_fullstack(self, mocker, repo_root, tmp_path, capsys): input_file = repo_root / "test_data" / "example_opt_pch_tsh.yaml" mocked_func = mocker.patch("lyopronto.opt_Pch_Tsh.dry", wraps=opt_Pch_Tsh.dry, autospec=True) @@ -213,6 +216,7 @@ def test_opt_pch_tsh_fullstack(self, mocker, repo_root, tmp_path, capsys): assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + @pytest.mark.main def test_opt_pch_fullstack(self, mocker, repo_root, tmp_path, capsys): input_file = repo_root / "test_data" / "example_opt_pch.yaml" mocked_func = mocker.patch("lyopronto.opt_Pch.dry", wraps=opt_Pch.dry, autospec=True) @@ -233,4 +237,12 @@ def test_opt_pch_fullstack(self, mocker, repo_root, tmp_path, capsys): generate_visualizations(output, inputs, "testtime") assert (tmp_path / "lyo_Temperatures_testtime.pdf").exists() assert (tmp_path / "lyo_Pressure_SublimationFlux_testtime.pdf").exists() - assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() \ No newline at end of file + assert (tmp_path / "lyo_DryingProgress_testtime.pdf").exists() + + @pytest.mark.main + def test_misspelled(self, repo_root): + input_file = repo_root / "test_data" / "example_knownRp.yaml" + inputs = read_inputs(input_file) + inputs["sim"]["tool"] = "Primery Drying Calculator" # Misspelled on purpose + with pytest.raises(ValueError, match="Invalid simulation tool"): + execute_simulation(inputs) \ No newline at end of file From 2ff1dd6e639139c98b7c8c66268f6400eb31085c Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 14:03:29 -0500 Subject: [PATCH 25/31] Focus main tests on IO logic, etc., not on correctness --- tests/test_main.py | 7 ------- 1 file changed, 7 deletions(-) diff --git a/tests/test_main.py b/tests/test_main.py index b357f3f..c33358a 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -4,11 +4,6 @@ import pytest import numpy as np from lyopronto import * -from .utils import ( - assert_physically_reasonable_output, - assert_complete_drying, - assert_incomplete_drying, -) class TestHighLevelAPI: """Tests for the high-level API functions in lyopronto.high_level.""" @@ -95,7 +90,6 @@ def test_unknownkv_edgecases(self, repo_root, capsys): inputs["Kv_range"] = [1e-5, 2e-5] with pytest.warns(UserWarning, match="bracket"): output = execute_simulation(inputs) - assert_physically_reasonable_output(output) captured = capsys.readouterr() assert f"Optimal Kv: {2e-5}" in captured.out @@ -104,7 +98,6 @@ def test_unknownkv_edgecases(self, repo_root, capsys): inputs["Kv_range"] = [1e-3, 2e-3] with pytest.warns(UserWarning, match="bracket"): output = execute_simulation(inputs) - assert_physically_reasonable_output(output) captured = capsys.readouterr() assert f"Optimal Kv: {1e-3}" in captured.out From 85e40b0c3fca95b9be87b414f3a2ad14e26d18b4 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 14:30:32 -0500 Subject: [PATCH 26/31] Add a little function documentation. --- lyopronto/design_space.py | 2 +- lyopronto/plot_styling.py | 37 ++++++++++++++++++++++++++++++------- 2 files changed, 31 insertions(+), 8 deletions(-) diff --git a/lyopronto/design_space.py b/lyopronto/design_space.py index f6236de..3ac3a4c 100644 --- a/lyopronto/design_space.py +++ b/lyopronto/design_space.py @@ -22,7 +22,7 @@ ################# Primary drying at fixed set points ############### -# TODO: docuemnt this properly +# TODO: document this properly def dry(vial,product,ht,Pchamber,Tshelf,dt,eq_cap,nVial): """Compute quantities necessary for constructing a graphical design space. diff --git a/lyopronto/plot_styling.py b/lyopronto/plot_styling.py index 16953d2..5d677fb 100644 --- a/lyopronto/plot_styling.py +++ b/lyopronto/plot_styling.py @@ -27,7 +27,18 @@ def axis_tick_styling( minorTickLength = 20, labelPad = 30, ): - """ Function to set styling for matplotlib axes ticks """ + """_summary_ + + Args: + ax (matplotlib.Axes.Axes): Axes object to style + color (str, optional): Axis and tick color. Defaults to 'k'. + gcafontSize (int, optional): Font size for tick labels (and axis labels). Defaults to 60. + majorTickWidth (int, optional): Width of major ticks. Defaults to 5. + minorTickWidth (int, optional): Width of minor ticks. Defaults to 3. + majorTickLength (int, optional): Length of major ticks. Defaults to 30. + minorTickLength (int, optional): Length of minor ticks. Defaults to 20. + labelPad (int, optional): padding between axes and axis labels. Defaults to 30. + """ ax.minorticks_on() ax.tick_params(axis='both',direction='in',pad=labelPad,width=majorTickWidth,length=majorTickLength,bottom=1,top=0) ax.tick_params(axis='both',which='minor',direction='in',width=minorTickWidth,length=minorTickLength) @@ -39,7 +50,9 @@ def axis_tick_styling( ax.yaxis.labelpad = labelPad def axis_style_pressure(ax, **kwargs): - """ Function to set styling for axes, with time on x and pressure on y """ + """ Function to set styling for axes, with time on x and pressure on y. + See axis_tick_styling for more usable kwargs. + """ color = kwargs.get('color','b') gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) @@ -47,7 +60,9 @@ def axis_style_pressure(ax, **kwargs): axis_tick_styling(ax, **kwargs) def axis_style_subflux(ax, **kwargs): - """ Function to set styling for axes, with time on x and sublimation flux on y """ + """ Function to set styling for axes, with time on x and sublimation flux on y. + See axis_tick_styling for more usable kwargs. + """ color = kwargs.get('color',[0, 0.7, 0.3]) gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) @@ -55,7 +70,9 @@ def axis_style_subflux(ax, **kwargs): axis_tick_styling(ax, **kwargs) def axis_style_percdried( ax, **kwargs): - """ Function to set styling for axes, with time on x and percent dried on y """ + """ Function to set styling for axes, with time on x and percent dried on y. + See axis_tick_styling for more usable kwargs. + """ color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) @@ -63,7 +80,9 @@ def axis_style_percdried( ax, **kwargs): axis_tick_styling(ax, **kwargs) def axis_style_temperature(ax, **kwargs): - """ Function to set styling for axes, with time on x and temperature on y """ + """ Function to set styling for axes, with time on x and temperature on y. + See axis_tick_styling for more usable kwargs. + """ color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) @@ -71,14 +90,18 @@ def axis_style_temperature(ax, **kwargs): axis_tick_styling(ax, **kwargs) def axis_style_designspace(ax, ylabel, **kwargs): - """ Function to set styling for axes, with pressure on x and sublimation flux on y """ + """ Function to set styling for axes, with pressure on x and sublimation flux on y. + See axis_tick_styling for more usable kwargs. + """ gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Chamber Pressure [mTorr]",fontsize=gcafontSize,**default_font_spec) ax.set_ylabel(ylabel,fontsize=gcafontSize,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_rp(ax, **kwargs): - """ Function to set styling for axes, with dry layer height on x and product resistance on y """ + """ Function to set styling for axes, with dry layer height on x and product resistance on y. + See axis_tick_styling for more usable kwargs. + """ color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Dry Layer Height [cm]",fontsize=gcafontSize,**default_font_spec) From 4cbcd99b92919a2a16052ae00950844e315de49d Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 14:42:16 -0500 Subject: [PATCH 27/31] Get rid of alternate (hyphenated) spelling for design space --- lyopronto/high_level.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index e87505d..c1e4559 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -56,7 +56,7 @@ def execute_simulation(inputs): "With the current implementation, either Kv or Rp must be specified." ) - elif sim_type == "Design Space Generator" or sim_type == "Design-Space-Generator": + elif sim_type == "Design Space Generator": output_data = design_space.dry( inputs["vial"], inputs["product"], From 14d8deecbca49bff37205606b097a003e13800a1 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 14:42:51 -0500 Subject: [PATCH 28/31] Unnecessary assignments --- tests/test_main.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_main.py b/tests/test_main.py index c33358a..8839886 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -89,7 +89,7 @@ def test_unknownkv_edgecases(self, repo_root, capsys): inputs["sim"]["Rp_known"] = True inputs["Kv_range"] = [1e-5, 2e-5] with pytest.warns(UserWarning, match="bracket"): - output = execute_simulation(inputs) + execute_simulation(inputs) captured = capsys.readouterr() assert f"Optimal Kv: {2e-5}" in captured.out @@ -97,7 +97,7 @@ def test_unknownkv_edgecases(self, repo_root, capsys): inputs["sim"]["Rp_known"] = True inputs["Kv_range"] = [1e-3, 2e-3] with pytest.warns(UserWarning, match="bracket"): - output = execute_simulation(inputs) + execute_simulation(inputs) captured = capsys.readouterr() assert f"Optimal Kv: {1e-3}" in captured.out From a24979448e67a32f6cf1a728e31b02ecc757664b Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 14:46:33 -0500 Subject: [PATCH 29/31] Use context manager for file opening, as recommended by Copilot --- lyopronto/high_level.py | 10 ++-------- tests/test_main.py | 2 +- 2 files changed, 3 insertions(+), 9 deletions(-) diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index c1e4559..acbc1fd 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -291,17 +291,13 @@ def save_inputs(inputs, timestamp): copied.pop("time_data", None) copied.pop("temp_data", None) # Then save - try: - yamlfile = open("lyopronto_input_" + timestamp + ".yaml", "w") + with open(f"lyopronto_input_{timestamp}.yaml", "w") as yamlfile: yaml.dump(copied, yamlfile) - finally: - yamlfile.close() def read_inputs(filename): "Read inputs from a YAML file." - try: - yamlfile = open(filename, "r") + with open(filename, "r") as yamlfile: inputs = yaml.load(yamlfile) if "product_temp_filename" in inputs: print( @@ -310,8 +306,6 @@ def read_inputs(filename): + "dictionary as `time_data` and `temp_data`." ) return inputs - finally: - yamlfile.close() def save_csv(output_data, inputs, timestamp): diff --git a/tests/test_main.py b/tests/test_main.py index 8839886..3ca3eee 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -234,7 +234,7 @@ def test_opt_pch_fullstack(self, mocker, repo_root, tmp_path, capsys): @pytest.mark.main def test_misspelled(self, repo_root): - input_file = repo_root / "test_data" / "example_knownRp.yaml" + input_file = repo_root / "test_data" / "example_knownrp.yaml" inputs = read_inputs(input_file) inputs["sim"]["tool"] = "Primery Drying Calculator" # Misspelled on purpose with pytest.raises(ValueError, match="Invalid simulation tool"): From 316752cbe5fc35aba1b9f760fc4e50feaa0ec7c3 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Mon, 9 Feb 2026 14:50:13 -0500 Subject: [PATCH 30/31] Take some more Copilot suggestions --- lyopronto/high_level.py | 4 ++-- lyopronto/plot_styling.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/lyopronto/high_level.py b/lyopronto/high_level.py index acbc1fd..7fa8d32 100644 --- a/lyopronto/high_level.py +++ b/lyopronto/high_level.py @@ -73,8 +73,8 @@ def execute_simulation(inputs): else: raise ValueError( - f"Invalid simulation tool {sim_type} selected." - " Valid options are: 'Freezing Calculator', 'Primary Drying Calculator', ", + f"Invalid simulation tool {sim_type} selected. " + "Valid options are: 'Freezing Calculator', 'Primary Drying Calculator', " "'Design Space Generator', 'Optimizer'." ) diff --git a/lyopronto/plot_styling.py b/lyopronto/plot_styling.py index 5d677fb..7cbecbd 100644 --- a/lyopronto/plot_styling.py +++ b/lyopronto/plot_styling.py @@ -86,7 +86,7 @@ def axis_style_temperature(ax, **kwargs): color = kwargs.get('color','k') gcafontSize = kwargs.get('gcafontSize',60) ax.set_xlabel("Time [hr]",fontsize=gcafontSize,**default_font_spec) - ax.set_ylabel("Product Temperature [°C]",fontsize=gcafontSize,color=color,**default_font_spec) + ax.set_ylabel("Temperature [°C]",fontsize=gcafontSize,color=color,**default_font_spec) axis_tick_styling(ax, **kwargs) def axis_style_designspace(ax, ylabel, **kwargs): From 196fb22c088cfbd58c727b650138866a943d3312 Mon Sep 17 00:00:00 2001 From: Isaac Wheeler Date: Tue, 10 Feb 2026 20:30:26 -0500 Subject: [PATCH 31/31] Catch and fix another bug in freezing, for multiple ramps --- lyopronto/freezing.py | 4 +++- tests/test_freezing.py | 45 +++++++++++++++++++++++++++++++++++++++--- 2 files changed, 45 insertions(+), 4 deletions(-) diff --git a/lyopronto/freezing.py b/lyopronto/freezing.py index 324b607..b80d0c2 100644 --- a/lyopronto/freezing.py +++ b/lyopronto/freezing.py @@ -124,6 +124,7 @@ def freeze(vial,product,h_freezing,Tshelf,dt): t_last = ts Tpr0 = Tpr # degC + Tsh0 = Tsh while(tt) # Get first index where time trigger exceeds current time @@ -131,12 +132,13 @@ def freeze(vial,product,h_freezing,Tshelf,dt): i_prev = i t_last = t_tr[i-1] Tpr0 = Tpr + Tsh0 = Tsh # Evaluate shelf temperature at current time point Tsh = Tshr(t) # degC # Product temperature - Tpr = functions.lumped_cap_Tpr_ice(t-t_last,Tpr0,V_frozen,h_freezing,vial['Av'],Tsh,Tsh_tr[i-1],r[i]) + Tpr = functions.lumped_cap_Tpr_ice(t-t_last,Tpr0,V_frozen,h_freezing,vial['Av'],Tsh,Tsh0,r[i]) # Update record as functions of the cycle time freezing_output_saved = np.append(freezing_output_saved, [[t, Tsh, Tpr]],axis=0) diff --git a/tests/test_freezing.py b/tests/test_freezing.py index dc32115..174f5a7 100644 --- a/tests/test_freezing.py +++ b/tests/test_freezing.py @@ -25,7 +25,7 @@ def freezing_params(): Tshelf = { "init": 10.0, "setpt": np.array([-40.0]), - "dt_setpt": np.array([1800]), + "dt_setpt": np.array([240]), "ramp_rate": 1.0, } dt = 0.01 @@ -39,7 +39,7 @@ def test_crystallization_time(self, freezing_params): def Tshelf_t(t): return Tshelf["setpt"][0] - t_cryst = crystallization_time_FUN( + args = [ vial["Vfill"], h_freezing, vial["Av"], @@ -47,10 +47,22 @@ def Tshelf_t(t): product["Tn"], Tshelf_t, 0.0, - ) + ] + + t_cryst = crystallization_time_FUN(*args) assert t_cryst > 0 assert t_cryst < 10 + double_fill = args.copy() + double_fill[0] *= 2 + t_cryst_double = crystallization_time_FUN(*double_fill) + assert t_cryst_double == pytest.approx(t_cryst * 2) + + half_h = args.copy() + half_h[1] /= 2 + t_cryst_half_h = crystallization_time_FUN(*half_h) + assert t_cryst_half_h == pytest.approx(t_cryst * 2) + def test_lumped_cap(self, freezing_params): vial, product, h_freezing, Tshelf, dt = freezing_params Tpr0 = product["Tpr0"] @@ -109,6 +121,33 @@ def test_freezing_basics(self, freezing_params): # Since default setup has long hold, product should approach shelf assert results[-1, 2] == pytest.approx(results[-1, 2], abs=0.1) + def test_freezing_cin(self, freezing_params): + """Test that freezing with imitated controlled ice nucleation is physically + reasonable. This also tests that if crystallization finished during a ramp, + the code correctly handles transition to final shelf temperature.""" + vial, product, h_freezing, _, dt = freezing_params + product["Tn"] = -5.01 # Set nucleation temp just below controlled for ramp + Tshelf = { + "init": 15.0, + "setpt": np.array([-5.0, -50.0]), + "dt_setpt": np.array([60, 120]), + "ramp_rate": 1.0, + } + results = freeze(vial, product, h_freezing, Tshelf, dt) + + # Check that nucleation occurs just after first set point ends + crystallization_period = results[results[:, 2] == product["Tf"], 0] + assert crystallization_period[0] > Tshelf["dt_setpt"][0] / constant.hr_To_min + assert crystallization_period[0] < Tshelf["dt_setpt"][0] / constant.hr_To_min + 0.05 + + + # Check that product temp changes smoothly (less than 5 degrees per time point) + np.testing.assert_array_less( + np.abs(np.diff(results[:, 2])), + 5.0, + "Product temperature should change smoothly during freezing", + ) + class TestFreezingEdgeCases: """Test freezing edge cases."""