def get_shp_with_offset(
df,
volume_column,
outer_average_width=15,
max_value=None,
color=None,
offset_col=None
):
to_shape = df.sort_values(by=volume_column).copy()
to_shape = to_shape[to_shape[volume_column] > 0]
to_shape['label'] = to_shape[volume_column]
if color is not None:
to_shape['color'] = color
else:
to_shape['color'] = data_visualization.color_series(to_shape[volume_column], max_value=max_value)
to_shape['width'] = data_visualization.width_series(
to_shape[volume_column],
outer_average_width=outer_average_width,
max_value=max_value)
if offset_col is not None:
to_shape['offset'] = data_visualization.width_series(
to_shape[offset_col],
outer_average_width=outer_average_width,
max_value=max_value)
return to_shape
def assigned_links_nodes_to_shp(links,
nodes,
gis_path,
epsg=None,
projection_file=None,
link_name='loaded_links.shp',
node_name='loaded_nodes.shp'):
if epsg is None and projection_file is None:
print('No projection defined --> considered as EPSG:4326')
projection_file = epsg4326
links = links.copy()
nodes = nodes.copy()
try:
links['color'] = links['line_color']
except KeyError:
links['color'] = links['line_color'] = 'gray'
links['width'] = 3
nodes['color'] = 'gray'
nodes['width'] = 3
pandasshp.write_shp(gis_path + 'nodes_linedraft.shp',
nodes,
epsg=epsg,
projection_file=projection_file,
style_file=point_style)
pandasshp.write_shp(gis_path + 'links_linedraft.shp',
links,
epsg=epsg,
projection_file=projection_file,
style_file=bordered_line_style)
links['width'] = visual.width_series(links['load'], outer_average_width=20)
links['color'] = links['line_color']
pandasshp.write_shp(gis_path + 'loaded_links_linedraft_color.shp',
links,
epsg=epsg,
style_file=line_style,
projection_file=projection_file)
links['color'] = visual.color_series(links['load'].fillna(0))
pandasshp.write_shp(gis_path + link_name,
links,
style_file=line_style,
epsg=epsg,
projection_file=projection_file)
nodes['width'] = visual.width_series(nodes['load'], outer_average_width=10)
nodes['color'] = visual.color_series(nodes['load'].fillna(0))
pandasshp.write_shp(gis_path + node_name,
nodes,
style_file=point_style,
epsg=epsg,
projection_file=projection_file)
def export(self,
volume_column,
file=None,
affected=False,
outer_average_width=15,
max_value=None,
projection_string=None,
style_file=line_style,
epsg=None,
color=None):
if projection_string == None and epsg == None:
print('No projection defined --> considered as EPSG:4326')
projection_string = epsg4326_string
if affected:
volume_column += '_transit'
else:
if not self.od_geometry:
print(
'can only map affected volumes with arg : od_geometry=False'
)
to_shape = self.volume.sort_values(by=volume_column).copy()
to_shape = to_shape[to_shape[volume_column] > 0]
to_shape['label'] = to_shape[volume_column]
if color is not None:
to_shape['color'] = color
else:
to_shape['color'] = data_visualization.color_series(
to_shape[volume_column], max_value=max_value)
to_shape['width'] = data_visualization.width_series(
to_shape[volume_column],
outer_average_width=outer_average_width,
max_value=max_value)
if not file:
return to_shape
else:
extension = file.split('.')[-1]
if extension == 'shp':
pandasshp.write_shp(file,
to_shape,
projection_string=projection_string,
style_file=style_file,
epsg=epsg)
elif extension == 'geojson':
gpd.GeoDataFrame(to_shape).to_file(file, driver='GeoJSON')
if epsg:
with open(file, 'r') as infile:
data = json.load(infile)
infile.close()
with open(file, 'w') as outfile:
data['crs'] = {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::{}".format(epsg)
}
}
json.dump(data, outfile)
def loaded_links_to_shp(
loaded_links,
gis_path,
load_column='load',
max_value=None,
outer_average_width=20,
color=True,
epsg=None,
projection_file=None,
name='loaded_links.shp',
create_legend=False,
*args,
**kwargs
):
if epsg is None and projection_file is None:
print('No projection defined --> considered as EPSG:4326')
projection_file = epsg4326
loaded_links = loaded_links.copy()
# Add colors
if color:
loaded_links['color'] = visual.color_series(
loaded_links[load_column].fillna(0),
max_value=max_value
)
# Add width
loaded_links['width'] = visual.width_series(
loaded_links[load_column].fillna(0),
max_value=max_value,
outer_average_width=outer_average_width
)
# Export
pandasshp.write_shp(
gis_path + name,
loaded_links,
style_file=line_style,
epsg=epsg,
projection_file=projection_file
)
# Legend
if create_legend==True:
create_load_legend(
legend_file_path=gis_path + name.split('.shp')[0] + '_legend.shp',
outer_average_width=outer_average_width,
epsg=epsg,
projection_file=projection_file,
max_value=max_value,
legend_type='LineString',
*args,
**kwargs
)
def ntlegs_centroids_to_shp(
ntlegs,
centroids,
gis_path,
epsg=None,
projection_file=None,
weighted=True
):
if epsg is None and projection_file is None:
print('No projection defined --> considered as EPSG:4326')
projection_file = epsg4326
ntlegs['width'] = 1
ntlegs['color'] = 'gray'
pandasshp.write_shp(
gis_path + 'ntlegs.shp',
ntlegs,
epsg=epsg,
projection_file=projection_file,
style_file=line_style)
try:
centroids['color'] = visual.color_series(
centroids['emission_rate'].fillna(0))
except:
pass
pandasshp.write_shp(
gis_path + 'centroids.shp',
centroids,
epsg=epsg,
projection_file=projection_file
)
if weighted:
centroids['width'] = visual.width_series(
np.sqrt(centroids['weight']), outer_average_width=15)
pandasshp.write_shp(
gis_path + 'weighted_centroids.shp',
centroids,
style_file=point_style,
epsg=epsg,
projection_file=projection_file
)
def assigned_nodes_to_shp(
nodes,
gis_path,
load_column='load',
max_value=None,
outer_average_width=10,
method='surface',
projection_file=None,
epsg=None,
color=True,
nodes_name='loaded_nodes.shp'
):
if epsg is None and projection_file is None:
print('No projection defined --> considered as EPSG:4326')
projection_file = epsg4326
nodes = nodes.copy()
# Add width
nodes['width'] = visual.width_series(
nodes[load_column],
max_value=max_value,
outer_average_width=outer_average_width,
method=method,
)
# Add color
if color:
nodes['color'] = visual.color_series(
nodes[load_column].fillna(0),
max_value=max_value,
)
# Export
pandasshp.write_shp(
gis_path + nodes_name,
nodes,
style_file=point_style,
epsg=epsg,
projection_file=projection_file
)
def create_load_legend(legend_file_path, coordinates, legend_type, values, max_value=None, style_file=line_style,
categories=None, outer_average_width=20, colors=True, delta=[1000, 1500], method='linear',
epsg=None, projection_file=None):
"""
Create a georeferenced legend in shp format for loaded links or points.
Args:
legend_file_path: name and path of the legend shp file
style_file: path to the style file to use
coordinates: coordinates of the georeferenced legend
type: Point or LineString
values: list of values to include in the legend
max_value: max value to calibrate the legend
categories: categories associated with the values
outer_average_width: width
delta: legend spacing (one value for Point legend, two values for Linestring)
"""
x = coordinates[0]
y = coordinates[1]
if legend_type == 'Point':
delta_y = delta[0] if isinstance(delta, list) else delta
legend_geometries = [geometry.Point([(x, y)])]
for i in range(len(values) - 1):
legend_geometries.append(
geometry.Point([(x, y + (i + 1) * delta_y)]))
elif legend_type == 'LineString':
delta_x = delta[0]
delta_y = delta[1]
legend_geometries = [geometry.LineString(
[(x, y), (x + delta_x, y)])]
for i in range(len(values) - 1):
legend_geometries.append(
geometry.LineString(
[
(x + (i +1) * delta_x, y ),
(x + (i + 2) * delta_x, y )
]
)
)
else:
raise Exception('Not implemented')
# Create legend df
legend_scale = pd.DataFrame({
'value': values,
'category': categories if categories else values,
'geometry': legend_geometries
}
)
if colors:
legend_scale['color'] = visual.color_series(
legend_scale['value'], max_value=max_value)
legend_scale['width'] = visual.width_series(
legend_scale['value'],
outer_average_width=outer_average_width,
max_value=max_value,
method=method
)
legend_scale['label'] = legend_scale['value']
# Write shp legend file
pandasshp.write_shp(
legend_file_path,
legend_scale,
style_file=style_file,
epsg=epsg,
projection_file=projection_file
)
