"""air network flows map
"""
import os
import sys
from collections import OrderedDict
import pandas as pd
import geopandas as gpd
import cartopy.crs as ccrs
import cartopy.io.shapereader as shpreader
import matplotlib.pyplot as plt
import numpy as np
from shapely.geometry import LineString
from atra.utils import *
[docs]def main():
config = load_config()
data_path = config['paths']['data']
air_edge_file_path = os.path.join(
config['paths']['data'], 'network', 'air_edges.shp')
air_flow_file_path = os.path.join(config['paths']['output'], 'flow_mapping_combined',
'air_passenger.csv')
mode_file = gpd.read_file(air_edge_file_path,encoding='utf-8')
flow_file = pd.read_csv(air_flow_file_path,encoding='utf-8-sig')
mode_file = pd.merge(mode_file,flow_file,how='left', on=['edge_id']).fillna(0)
mode_file['passengers_2016'] = 1.0*mode_file['passengers_2016']/365
color = '#252525'
color_by_type = {'air Line': color}
plot_sets = [
{
'file_tag': 'passenger',
'legend_label': "AADF (passenger/day)",
'divisor': 1,
'columns': ['passengers_2016'],
'title_cols': ['Total passengers'],
'significance':0
},
]
for plot_set in plot_sets:
for c in range(len(plot_set['columns'])):
# basemap
proj_lat_lon = ccrs.PlateCarree()
ax = get_axes()
plot_basemap(ax, data_path)
scale_bar(ax, location=(0.8, 0.05))
plot_basemap_labels(ax, data_path, include_regions=True)
column = plot_set['columns'][c]
weights = [
record[column]
for iter_, record in mode_file.iterrows()
]
max_weight = max(weights)
width_by_range = generate_weight_bins(weights, n_steps=7, width_step=0.02)
geoms_by_range = {}
for value_range in width_by_range:
geoms_by_range[value_range] = []
for iter_, record in mode_file.iterrows():
val = record[column]
geom = record.geometry
for nmin, nmax in geoms_by_range:
if nmin <= val and val < nmax:
geoms_by_range[(nmin, nmax)].append(geom)
# plot
for range_, width in width_by_range.items():
ax.add_geometries(
[geom.buffer(width) for geom in geoms_by_range[range_]],
crs=proj_lat_lon,
edgecolor='none',
facecolor=color,
zorder=2)
x_l = -58.4
x_r = x_l + 0.4
base_y = -45.1
y_step = 0.8
y_text_nudge = 0.2
x_text_nudge = 0.2
ax.text(
x_l,
base_y + y_step - y_text_nudge,
plot_set['legend_label'],
horizontalalignment='left',
transform=proj_lat_lon,
size=10)
divisor = plot_set['divisor']
significance_ndigits = plot_set['significance']
max_sig = []
for (i, ((nmin, nmax), line_style)) in enumerate(width_by_range.items()):
if round(nmin/divisor, significance_ndigits) < round(nmax/divisor, significance_ndigits):
max_sig.append(significance_ndigits)
elif round(nmin/divisor, significance_ndigits+1) < round(nmax/divisor, significance_ndigits+1):
max_sig.append(significance_ndigits+1)
elif round(nmin/divisor, significance_ndigits+2) < round(nmax/divisor, significance_ndigits+2):
max_sig.append(significance_ndigits+2)
else:
max_sig.append(significance_ndigits+3)
significance_ndigits = max(max_sig)
for (i, ((nmin, nmax), width)) in enumerate(width_by_range.items()):
y = base_y - (i*y_step)
line = LineString([(x_l, y), (x_r, y)])
ax.add_geometries(
[line.buffer(width)],
crs=proj_lat_lon,
linewidth=0,
edgecolor=color,
facecolor=color,
zorder=2)
if nmin == max_weight:
value_template = '>{:.' + str(significance_ndigits) + 'f}'
label = value_template.format(
round(max_weight/divisor, significance_ndigits))
else:
value_template = '{:.' + str(significance_ndigits) + \
'f}-{:.' + str(significance_ndigits) + 'f}'
label = value_template.format(
round(nmin/divisor, significance_ndigits), round(nmax/divisor, significance_ndigits))
ax.text(
x_r + x_text_nudge,
y - y_text_nudge,
label,
horizontalalignment='left',
transform=proj_lat_lon,
size=10)
plt.title('AADF - {}'.format(plot_set['title_cols'][c]), fontsize=10)
output_file = os.path.join(config['paths']['figures'],
'air_flow-map-{}-max-scale.png'.format(column))
save_fig(output_file)
plt.close()
if __name__ == '__main__':
main()