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lachlangroselachlangrose
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fix: adding io module
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‎loopstructural/main/io/__init__.py‎

Whitespace-only changes.

‎loopstructural/main/io/pyvista2qgis.py‎

Whitespace-only changes.

‎loopstructural/main/io/qgis2dataframe.py‎

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import pandas as pd
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import geopandas as gpd
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from qgis.core import QgsRaster, QgsWkbTypes
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def qgsLayerToGeoDataFrame(layer) -> gpd.GeoDataFrame:
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if layer is None:
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return None
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features = layer.getFeatures()
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fields = layer.fields()
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data = {'geometry': []}
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for f in fields:
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data[f.name()] = []
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for feature in features:
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geom = feature.geometry()
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if geom.isEmpty():
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continue
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data['geometry'].append(geom)
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for f in fields:
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data[f.name()].append(feature[f.name()])
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return gpd.GeoDataFrame(data, crs=layer.crs().authid())
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def qgsLayerToDataFrame(layer, dtm) -> pd.DataFrame:
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"""Convert a vector layer to a pandas DataFrame
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samples the geometry using either points or the vertices of the lines
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:param layer: _description_
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:type layer: _type_
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:param dtm: Digital Terrain Model to evaluate Z values
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:type dtm: _type_ or None
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:return: the dataframe object
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:rtype: pd.DataFrame
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"""
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if layer is None:
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return None
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fields = layer.fields()
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data = {}
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data['X'] = []
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data['Y'] = []
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data['Z'] = []
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for field in fields:
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data[field.name()] = []
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for feature in layer.getFeatures():
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geom = feature.geometry()
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points = []
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if geom.isMultipart():
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if geom.type() == QgsWkbTypes.PointGeometry:
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points = geom.asMultiPoint()
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elif geom.type() == QgsWkbTypes.LineGeometry:
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for line in geom.asMultiPolyline():
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points.extend(line)
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# points = geom.asMultiPolyline()[0]
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else:
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if geom.type() == QgsWkbTypes.PointGeometry:
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points = [geom.asPoint()]
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elif geom.type() == QgsWkbTypes.LineGeometry:
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points = geom.asPolyline()
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for p in points:
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coords = list(p.coords())
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data['X'].append(coords[0])
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data['Y'].append(coords[1])
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if dtm is not None:
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# if a DTM is provided, use it to get the Z value
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# Extract the value at the point
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z_value = dtm.dataProvider().identify(p, QgsRaster.IdentifyFormatValue)
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if z_value.isValid():
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z_value = z_value.results()[1]
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else:
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z_value = -9999
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data['Z'].append(z_value)
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elif len(coords) > 2:
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# if the geometry has Z values, use them
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data['Z'].append(coords[2])
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else:
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#otherwise set to 0
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data['Z'].append(0)
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for field in fields:
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data[field.name()].append(feature[field.name()])
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return pd.DataFrame(data)

‎loopstructural/main/io/qgis2pyvista.py‎

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def polyline2line(geodataframe):
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pass
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def gqsPoint2VtkPoint(geodataframe):
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pass
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‎loopstructural/main/io/samplers.py‎

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import pandas as pd
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import geopandas as gpd
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from typing import Callable
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from abc import ABC, abstractmethod
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class BaseSampler(ABC):
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"""Base class for samplers."""
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@abstractmethod
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def __call__(self, line: gpd.GeoDataFrame, dem: Callable, use_z: bool) -> pd.DataFrame:
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"""Sample the line and return a DataFrame with X, Y, Z coordinates and attributes."""
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pass
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class RegularSpacingSampler(BaseSampler):
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def __init__(self, spacing: float):
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self.spacing = spacing
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def __call__(self, line: gpd.GeoDataFrame, dem: Callable, use_z: bool) -> pd.DataFrame:
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"""Sample the line at regular intervals and return a DataFrame with X, Y, Z coordinates and attributes."""
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points = []
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feature_id = 0
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if line is None:
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return pd.DataFrame(points, columns=['X', 'Y', 'Z', 'feature_id'])
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for geom in line.geometry:
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attributes = line.iloc[feature_id].to_dict()
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attributes.pop('geometry', None) # Remove geometry from attributes
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if geom.geom_type == 'LineString':
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length = geom.length
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num_points = max(int(length // self.spacing), 1)
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for i in range(num_points + 1):
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point = geom.interpolate(i * self.spacing)
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x, y = point.x, point.y
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# Use Z from geometry if available, otherwise use DEM
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if use_z and hasattr(point, 'z'):
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z = point.z
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else:
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z = dem(x, y)
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points.append({'X': x, 'Y': y, 'Z': z, 'feature_id': feature_id, **attributes})
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elif geom.geom_type == 'MultiLineString':
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for l in geom.geoms:
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length = l.length
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num_points = max(int(length // self.spacing), 1)
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for i in range(num_points + 1):
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point = l.interpolate(i * self.spacing)
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x, y = point.x, point.y
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# Use Z from geometry if available, otherwise use DEM
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if use_z and hasattr(point, 'z'):
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z = point.z
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else:
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z = dem(x, y)
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points.append({'X': x, 'Y': y, 'Z': z, 'feature_id': feature_id, **attributes})
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elif geom.geom_type == 'Point':
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coords = list(geom.coords[0])
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# Use Z from geometry if available, otherwise use DEM
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if use_z and len(coords) > 2:
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z = coords[2]
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elif dem is not None:
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z = dem(coords[0], coords[1])
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else:
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z = 0
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points.append({'X': coords[0], 'Y': coords[1], 'Z': z, 'feature_id': feature_id, **attributes})
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feature_id += 1
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df = pd.DataFrame(points)
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return df
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class AllSampler(BaseSampler):
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"""This is a simple sampler that just returns all the points, or all of the vertices
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of a line. It will also copy the elevation from the DEM or the elevation set in the data manager.
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"""
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def __call__(self, line: gpd.GeoDataFrame, dem: Callable, use_z: bool) -> pd.DataFrame:
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"""Sample the line and return a DataFrame with X, Y, Z coordinates and attributes."""
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points = []
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feature_id = 0
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if line is None:
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return pd.DataFrame(points, columns=['X', 'Y', 'Z', 'feature_id'])
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for geom in line.geometry:
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attributes = line.iloc[feature_id].to_dict()
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attributes.pop('geometry', None) # Remove geometry from attributes
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if geom.geom_type == 'LineString':
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coords = list(geom.coords)
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for coord in coords:
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x, y = coord[0], coord[1]
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# Use Z from geometry if available, otherwise use DEM
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if use_z and len(coord) > 2:
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z = coord[2]
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else:
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z = dem(x, y)
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points.append({'X': x, 'Y': y, 'Z': z, 'feature_id': feature_id, **attributes})
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elif geom.geom_type == 'MultiLineString':
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for l in geom.geoms:
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coords = list(l.coords)
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for coord in coords:
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x, y = coord[0], coord[1]
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# Use Z from geometry if available, otherwise use DEM
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if use_z and len(coord) > 2:
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z = coord[2]
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else:
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z = dem(x, y)
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points.append(
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{'X': x, 'Y': y, 'Z': z, 'feature_id': feature_id, **attributes}
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)
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elif geom.geom_type == 'Point':
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coords = list(geom.coords[0])
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# Use Z from geometry if available, otherwise use DEM
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if use_z and len(coords) > 2:
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z = coords[2]
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elif dem is not None:
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z = dem(coords[0], coords[1])
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else:
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z = 0
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points.append({'X': coords[0], 'Y': coords[1], 'Z': z, 'feature_id': feature_id, **attributes})
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feature_id += 1
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df = pd.DataFrame(points)
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return df

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