import numpy as np
from powersimdata.utility.helpers import _check_import
from pyproj import Transformer
[docs]def project_branch(branch):
"""Projects branches on new coordinates system.
:param pandas.DataFrame branch: branch data frame.
:return: (*pandas.DataFrame*) -- projected branch data frame.
"""
transformer = Transformer.from_crs("epsg:4326", "epsg:3857")
from_lat, from_lon = branch.from_lat.to_numpy(), branch.from_lon.to_numpy()
from_x, from_y = transformer.transform(from_lat, from_lon)
to_lat, to_lon = branch.to_lat.to_numpy(), branch.to_lon.to_numpy()
to_x, to_y = transformer.transform(to_lat, to_lon)
new_columns = {
"from_x": from_x,
"from_y": from_y,
"to_x": to_x,
"to_y": to_y,
}
branch_map = branch.assign(**new_columns)
return branch_map
[docs]def project_bus(bus):
"""Projects buses on new coordinates system.
:param pandas.DataFrame bus: bus data frame.
:return: (*pandas.DataFrame*) -- projected bus data frame.
"""
transformer = Transformer.from_crs("epsg:4326", "epsg:3857")
lat, lon = bus.lat.to_numpy(), bus.lon.to_numpy()
x, y = transformer.transform(lat, lon)
bus_map = bus.assign(x=x, y=y)
return bus_map
[docs]def project_borders(us_states_dat, state_list=None):
"""Prepares US state borders data for use on the map.
:param dict us_states_dat: keys are state abbrevs, values are dicts with keys of
{"lats", "lons"}, values of coordinates.
:param iterable state_list: abbrevs of states to project, defaults to the keys of
us_states_dat minus AK, HI, DC, & PR.
:return: (*tuple*) -- reprojected coordinates for use on map.
"""
transformer = Transformer.from_crs("epsg:4326", "epsg:3857")
if state_list is None:
state_list = set(us_states_dat.keys()) - {"AK", "HI", "DC", "PR"}
state_xys = [
transformer.transform(us_states_dat[s]["lats"], us_states_dat[s]["lons"])
for s in state_list
]
all_state_xs, all_state_ys = zip(*state_xys)
return all_state_xs, all_state_ys
[docs]def convert_shapefile_to_latlon_dict(filename, key):
"""Converts a shapefile to a dictionary of lat/lon data.
:param str filename: the location of the shapefile to interpret.
:param str key: the shapefile column values used as dictionary keys.
:return: (*dict*) -- dictionary with keys from the specified shapefile column,
values are dict with keys of {"lat", "lon"}, values are coordinates, padded by
nan values to indicate the end of each polygon before the start of the next one.
:raises ValueError: if the specified key is not present in the shapefile, or the
shapefile contains at least one polygon with a hole.
"""
gpd = _check_import("geopandas")
shapes = gpd.read_file(filename)
if key not in shapes.columns:
raise ValueError("key must be present in the columns of the shapefile")
exploded_shapes = shapes.explode()
if sum([len(g.interiors) for g in exploded_shapes.geometry]) > 0:
raise ValueError("Cannot convert shapes with holes")
keys_to_latlon_dicts = {}
for i in shapes.index:
latlon_arrays_list = [np.array(g.xy) for g in exploded_shapes.exterior.loc[i]]
# Join individual arrays, padding inbetween with (nan, nan) coordinate point
nanpadded_array = np.concatenate(
[
np.concatenate([s.T, np.empty((1, 2)) * np.nan])
if i < (len(latlon_arrays_list) - 1)
else s.T
for i, s in enumerate(latlon_arrays_list)
]
).T
latlon_dict = {"lats": nanpadded_array[1], "lons": nanpadded_array[0]}
keys_to_latlon_dicts[shapes.loc[i, key]] = latlon_dict
return keys_to_latlon_dicts
