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segment_plotter.py
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import os
os.chdir(os.path.dirname(os.path.abspath(__file__)))
import fiona
import geopandas as gpd
from collections import defaultdict
import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
import random
import statistics as stats
import cartopy.crs as ccrs
from matplotlib_scalebar.scalebar import ScaleBar
import pandas as pd
from matplotlib.lines import Line2D
import haversine as hs
from haversine import Unit
from pyproj import Geod
import seaborn as sns
plt.rc('axes', labelsize=12)
plt.rc('figure', titlesize=25)
def get_random_colours(num_colours):
return ["#"+''.join([random.choice('0123456789ABCDEF') for j in range(6)])
for i in range(num_colours)]
def get_binary_colours(num_segments, c1, c2):
colours = []
for i in range(num_segments):
if i % 2 == 0:
colours.append(c1)
else:
colours.append(c2)
return colours
def plot_no2():
gpx_gdb = '/home/sophie/GitHub/uninotes_2021/sem2/gisci399/arc/no2_gpx_fusion.gdb/'
layers = fiona.listlayers(gpx_gdb)
data = defaultdict(dict)
# get data from geodatabase
for layer in layers:
if '_no2' in layer:
gdf = gpd.read_file(gpx_gdb, layer=layer)
gdf = gdf.dropna()
data[layer] = gdf
fig, ax = plt.subplots(figsize=(20, 20))
vmin = 10
vmax = 45
for item in data.values():
item.plot(ax=ax, column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
# set labels
ax.set_title('Predicted NO$_2$ Exposure while Cycling along Selected Routes in Auckland', fontsize=25)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
# add legend (colour map)
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
cbar = ax.figure.colorbar(
mpl.cm.ScalarMappable(norm=norm, cmap='viridis_r'),
ax=ax, pad=0.05, fraction=0.03,
label='NO$_2$ (\u00B5g / m$^3$)')
# add scale bar
scalebar = ScaleBar(70000)
plt.gca().add_artist(scalebar)
# add north arrow
x, y, arrow_length = 0.985, 0.07, 0.05
ax.annotate('N', xy=(x, y), xytext=(x, y-arrow_length),
arrowprops=dict(facecolor='black', width=5, headwidth=12),
ha='center', va='center', fontsize=22,
xycoords=ax.transAxes)
def plot_spatial_segments():
seg_gdb = '/home/sophie/GitHub/uninotes_2021/sem2/gisci399/arc/segmentation/no2_road_segmentation.gdb/'
layers = fiona.listlayers(seg_gdb)
data = defaultdict(dict)
for layer in layers:
gdf = gpd.read_file(seg_gdb, layer=layer)
gdf.dropna(inplace=True)
gdf = gdf.sort_values('DateTimeS', axis=0)
gdf.reset_index(inplace=True)
#gdf = gdf.dropna()
data[layer] = gdf
# MAP
vmin, vmax = 10, 45
fig, ax = plt.subplots(2, 2, figsize=(20, 10), sharex=True, sharey=True)
layers_list = list(data.values())
layers_list[0].plot(ax=ax[0, 0], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[0, 0].set_title('20m Segments')
layers_list[1].plot(ax=ax[0, 1], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[0, 1].set_title('50m Segments')
layers_list[2].plot(ax=ax[1, 0], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[1, 0].set_title('100m Segments')
layers_list[3].plot(ax=ax[1, 1], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[1, 1].set_title('300m Segments')
# add legend (colour map)
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
cbar = plt.colorbar(
mpl.cm.ScalarMappable(norm=norm, cmap='viridis_r'),
ax=ax, pad=0.05, fraction=0.02,
label='NO$_2$ (\u00B5g / m$^3$)')
# set labels
fig.text(0.49, 0.08, 'Longitude', ha='center', fontsize=22)
fig.text(0.075, 0.5, 'Latitude', va='center', rotation='vertical', fontsize=22)
# PLOT OF RASTERVALUE OVER TIME
fig, ax = plt.subplots(1, figsize=(13, 8))
segs = ['20m', '50m', '100m', '300m']
i = 0
for layer in layers_list:
layer['DateTimeS'] = pd.to_datetime(layer['DateTimeS'])
layer['epoch'] = layer['DateTimeS'].apply(lambda x: x.timestamp())
label = 'Segment: {} (mean NO$_2$: {})'.format(segs[i], round(np.nanmean(layer['RASTERVALU']), 1))
ax.plot(layer['epoch'], layer['RASTERVALU'], label=label)
i += 1
ax.legend()
ax.set_title('Track A')
ax.set_ylabel('NO$_2$ (\u00B5g / m$^3$)')
ax.set_xlabel('Time (Unix Epoch)')
def plot_all_segments():
gdb = '/home/sophie/GitHub/uninotes_2021/sem2/gisci399/arc/segmentation/final_segments.gdb/'
layers = fiona.listlayers(gdb)
data = defaultdict(dict)
colours = {
'300m': 'red',
'100m': 'orange',
'50m': 'blue',
'20m': 'green'}
for layer in layers:
gdf = gpd.read_file(gdb, layer=layer)
gdf = gdf.dropna()
gdf['DateTimeS'] = pd.to_datetime(gdf['DateTimeS'])
gdf['epoch'] = gdf['DateTimeS'].apply(lambda x: x.timestamp())
gdf = gdf.sort_values('epoch', axis=0)
gdf = gdf.reset_index()
temporal = layer.split('_')[1]
spatial = layer.split('_')[2]
data[temporal][spatial] = gdf
fig, ax = plt.subplots(3, 2, figsize=(20, 20), sharex=True, sharey=True)
for seg in data['1s']:
ax[0, 0].plot(data['1s'][seg]['epoch'], data['1s'][seg]['RASTERVALU'], label=seg, color=colours[seg])
for seg in data['5s']:
ax[0, 1].plot(data['5s'][seg]['epoch'], data['5s'][seg]['RASTERVALU'], label=seg, color=colours[seg])
for seg in data['10s']:
ax[1, 0].plot(data['10s'][seg]['epoch'], data['10s'][seg]['RASTERVALU'], label=seg, color=colours[seg])
for seg in data['60s']:
ax[1, 1].plot(data['60s'][seg]['epoch'], data['60s'][seg]['RASTERVALU'], label=seg, color=colours[seg])
for seg in data['120s']:
ax[2, 0].plot(data['120s'][seg]['epoch'], data['120s'][seg]['RASTERVALU'], label=seg, color=colours[seg])
for seg in data['300s']:
ax[2, 1].plot(data['300s'][seg]['epoch'], data['300s'][seg]['RASTERVALU'], label=seg, color=colours[seg])
font = 18
ax[0, 0].set_title('1 Second', fontsize=font)
ax[0, 1].set_title('5 Seconds', fontsize=font)
ax[1, 0].set_title('10 Seconds', fontsize=font)
ax[1, 1].set_title('60 Seconds', fontsize=font)
ax[2, 0].set_title('120 Seconds', fontsize=font)
ax[2, 1].set_title('300 Seconds', fontsize=font)
lines = []
labels = []
for colour in colours:
lines.append(Line2D([0], [0], color=colours[colour], lw=3))
labels.append(colour)
fig.legend(lines, labels, loc='center right', prop={'size': 19})
fig.text(0.51, 0.08, 'Time (Unix Epoch)', ha='center', fontsize=font)
fig.text(0.075, 0.5, 'NO$_2$ (\u00B5g / m$^3$)', va='center', rotation='vertical', fontsize=font)
def plot_two_segments():
gdb = '/home/sophie/GitHub/uninotes_2021/sem2/gisci399/arc/segmentation/final_segments.gdb/'
layers = fiona.listlayers(gdb)
data = defaultdict(dict)
colours = {
'300m': 'red',
'100m': 'orange',
'50m': 'blue',
'20m': 'green'}
for layer in layers:
gdf = gpd.read_file(gdb, layer=layer)
gdf = gdf.dropna()
gdf['DateTimeS'] = pd.to_datetime(gdf['DateTimeS'])
gdf['epoch'] = gdf['DateTimeS'].apply(lambda x: x.timestamp())
gdf = gdf.sort_values('epoch', axis=0)
gdf = gdf.reset_index()
temporal = layer.split('_')[1]
spatial = layer.split('_')[2]
data[temporal][spatial] = gdf
fig, ax = plt.subplots(2, 2, figsize=(15, 10), gridspec_kw={'width_ratios': [1.5, 0.7]})
vmin, vmax = 10, 45
data['10s']['50m'].plot(ax=ax[0, 0], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[0, 1].plot(data['10s']['50m']['epoch'], data['10s']['50m']['RASTERVALU'])
ax[0, 1].set_ylabel('NO$_2$ (\u00B5g / m$^3$)')
ax[0, 1].set_xlabel('Time (Unix Epoch)', labelpad=15)
ax[0, 0].set(xlabel='Longitude', ylabel='Latitude')
data['60s']['50m'].plot(ax=ax[1, 0], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[1, 1].plot(data['60s']['50m']['epoch'], data['60s']['50m']['RASTERVALU'])
ax[1, 1].set_ylabel('NO$_2$ (\u00B5g / m$^3$)')
ax[1, 1].set_xlabel('Time (Unix Epoch)', labelpad=15)
ax[1, 0].set(xlabel='Longitude', ylabel='Latitude')
fig.text(0.5, 0.5, s='60 Seconds, 50 Metres Segmented', ha='center', fontsize=18)
fig.text(0.5, 0.97, s='10 Seconds, 50 Metres Segmented', ha='center', fontsize=18)
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
cbar = plt.colorbar(
mpl.cm.ScalarMappable(norm=norm, cmap='viridis_r'),
ax=ax[1, 0], pad=0.02, fraction=0.1,
label='NO$_2$ (\u00B5g / m$^3$)')
cbar = plt.colorbar(
mpl.cm.ScalarMappable(norm=norm, cmap='viridis_r'),
ax=ax[0, 0], pad=0.02, fraction=0.1,
label='NO$_2$ (\u00B5g / m$^3$)')
fig.tight_layout(pad=4)
# add scale bar
scalebar1 = ScaleBar(100000)
ax[0, 0].add_artist(scalebar1)
scalebar2 = ScaleBar(100000)
ax[1, 0].add_artist(scalebar2)
# add north arrow
x, y, arrow_length = 0.98, 0.14, 0.1
ax[0, 0].annotate('N', xy=(x, y), xytext=(x, y-arrow_length),
arrowprops=dict(facecolor='black', width=3, headwidth=7),
ha='center', va='center', fontsize=12,
xycoords=ax[0, 0].transAxes)
ax[1, 0].annotate('N', xy=(x, y), xytext=(x, y-arrow_length),
arrowprops=dict(facecolor='black', width=3, headwidth=7),
ha='center', va='center', fontsize=12,
xycoords=ax[1, 0].transAxes)
def plot_by_road():
gdb = '/home/sophie/GitHub/uninotes_2021/sem2/gisci399/arc/segmentation/final_segments.gdb/'
layers = fiona.listlayers(gdb)
layers_of_interest = ['roads_10s_20m', 'roads_60s_20m']
roads_of_interest = ['Symonds Street', 'Domain Drive', 'Remuera Road',
'Kohimarama Road', 'Tamaki Drive', 'Queen Street']
data = defaultdict(dict)
# bar chart
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(15, 7))
road_highlight = 'Remuera Road'
layer_col = []
road_col = []
no2_col = []
for layer in layers:
if layer in layers_of_interest:
gdf = gpd.read_file(gdb, layer=layer)
gdf.dropna(inplace=True)
gdf['DateTimeS'] = pd.to_datetime(gdf['DateTimeS'])
gdf['epoch'] = gdf['DateTimeS'].apply(lambda x: x.timestamp())
gdf = gdf.sort_values('epoch', axis=0)
gdf = gdf.reset_index()
gdf = gdf.loc[gdf['full_road_'].isin(roads_of_interest)]
df = gdf.groupby('full_road_', as_index=False)['RASTERVALU'].mean()
temporal = layer.split('_')[1]
spatial = layer.split('_')[2]
data[temporal][spatial] = gdf
tmp = defaultdict(dict)
label = '{}, {}'.format(temporal, spatial)
for road in roads_of_interest:
this_road = gdf.loc[gdf['full_road_'] == road]
if len(this_road) > 0:
layer_col.append(label)
road_col.append(road)
no2_col.append(stats.mean(this_road['RASTERVALU']))
#ax[0].bar(df['full_road_'], df['RASTERVALU'], alpha=0.5, label=label)
series = gdf.loc[gdf['full_road_'] == road_highlight]
ax[1].plot(series['epoch'], series['RASTERVALU'], label=label)
df = pd.DataFrame([layer_col, road_col, no2_col]).T
sns.barplot(x=1, y=2, hue=0, data=df, ax=ax[0])
ax[0].legend()
ax[0].set_xlabel('Street Name', fontsize=15)
ax[0].set_ylabel('Average NO$_2$ (\u00B5g / m$^3$)', fontsize=15)
ax[0].tick_params(axis='x', labelrotation=45, labelsize=13)
ax[1].legend()
ax[1].set_title('{}'.format(road_highlight))
ax[1].set_xlabel('Time (Unix Epoch)')
ax[1].set_ylabel('NO$_2$ (\u00B5g / m$^3$)')
def plot_temporal():
gdb = '/home/sophie/GitHub/uninotes_2021/sem2/gisci399/arc/segmentation/temporal.gdb/'
layers = fiona.listlayers(gdb)
layers = ['roads_1s', 'roads_5s', 'roads_10s', 'roads_60s', 'roads_120s', 'roads_300s']
data = defaultdict(dict)
for layer in layers:
gdf = gpd.read_file(gdb, layer=layer)
gdf.dropna(inplace=True)
gdf['DateTimeS'] = pd.to_datetime(gdf['DateTimeS'])
gdf['epoch'] = gdf['DateTimeS'].apply(lambda x: x.timestamp())
gdf = gdf.sort_values('epoch', axis=0)
gdf = gdf.reset_index()
time = layer.split('_')[1]
data[time] = gdf
fig, ax = plt.subplots(1, figsize=(13, 8))
for gdf in data:
label = 'Interval: {} (mean NO$_2$: {})'.format(gdf, round(stats.mean(data[gdf]['RASTERVALU']), 2))
ax.plot(data[gdf]['epoch'], data[gdf]['RASTERVALU'], label=label)
ax.legend()
ax.set_title('Track A')
ax.set_xlabel('Time (Unix Epoch)')
ax.set_ylabel('NO$_2$ (\u00B5g / m$^3$)')
# MAP
vmin, vmax = 10, 45
fig, ax = plt.subplots(3, 2, figsize=(20, 15), sharex=True, sharey=True)
data['1s'].plot(ax=ax[0, 0], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[0, 0].set_title('1s Interval')
data['5s'].plot(ax=ax[0, 1], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[0, 1].set_title('5s Interval')
data['10s'].plot(ax=ax[1, 0], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[1, 0].set_title('10s Interval')
data['60s'].plot(ax=ax[1, 1], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[1, 1].set_title('60s Interval')
data['120s'].plot(ax=ax[2, 0], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[2, 0].set_title('60s Interval')
data['300s'].plot(ax=ax[2, 1], column='RASTERVALU', cmap='viridis_r',
vmin=vmin, vmax=vmax)
ax[2, 1].set_title('300s Interval')
# add legend (colour map)
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
cbar = plt.colorbar(
mpl.cm.ScalarMappable(norm=norm, cmap='viridis_r'),
ax=ax, pad=0.05, fraction=0.02,
label='NO$_2$ (\u00B5g / m$^3$)')
# set labels
fig.text(0.49, 0.08, 'Longitude', ha='center', fontsize=22)
fig.text(0.075, 0.5, 'Latitude', va='center', rotation='vertical', fontsize=22)
#plot_temporal()
#plot_by_road()
#plot_two_segments()
#plot_all_segments()
#plot_spatial_segments()