demand_plot.py

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
import random
import pickle
import matplotlib.dates as mdates
from matplotlib.ticker import LinearLocator

import datetime
fn = "ATL_schedule_GA_blockGroup_commuter_13_$20.0_0.0.csv"

data = pd.read_csv(fn)

start = "homeVertIdx"
end = "workVertIdx"
t1 = "departureFromHomeVert"
t2 = "departureFromWorkVert"

n = len(data[start])

random.seed(1)
s = random.sample(range(n), n-10)

s = range(n)


starts = data[start][s].values
ends = data[end][s].values

t1s = data[t1][s].values
t2s = data[t2][s].values

A = np.zeros((13, 13))

for i in range(len(s)):

    m = [t1s[i], starts[i], ends[i]]

    m = [t2s[i], ends[i], starts[i]]

    A[starts[i], ends[i]] += 1
    A[ends[i], starts[i]] += 1


A = A / A.sum() * 2*len(s)

print(A.sum())
SMALL_SIZE = 8
MEDIUM_SIZE = 10
BIGGER_SIZE = 12

plt.rc('font', size=MEDIUM_SIZE)          # controls default text sizes
plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title
plt.rc('axes', labelsize=BIGGER_SIZE)    # fontsize of the x and y labels
plt.rc('xtick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels
plt.rc('ytick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels
plt.rc('legend', fontsize=MEDIUM_SIZE)    # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title

plt.imshow(A, cmap = "Greens")

for edge, spine in plt.gca().spines.items():
    spine.set_visible(False)
ax = plt.gca()
ax.set_xticks(np.arange(A.shape[1]+1)-.5, minor=True)
ax.set_yticks(np.arange(A.shape[0]+1)-.5, minor=True)

plt.xticks(range(13))
plt.yticks(range(13))
ax.grid(which="minor", color="w", linestyle='-', linewidth=3)
ax.tick_params(which="minor", bottom=False, left=False)

plt.colorbar(label="Number of flights")

plt.xlabel("Vertiport number")
plt.ylabel("Vertiport number")

plt.gcf().savefig('paper_ports_hist.pdf', dpi=150)

plt.figure()


_times = np.concatenate((t1s, t2s))
times = []
ts = datetime.datetime(2022, 1, 1, 0, 0)
for t in _times:

    t2 = ts + datetime.timedelta(hours = int(t)) + datetime.timedelta(minutes=60*(t - int(t)))
    times.append(t2)

plt.hist(times, bins=100, facecolor='green', alpha=0.75, edgecolor='black', linewidth=0.05)
plt.xlabel("Time of day")
plt.ylabel("Number of flights")

myFmt = mdates.DateFormatter('%H:%M')
plt.gca().xaxis.set_major_formatter(myFmt)
plt.gcf().autofmt_xdate()


ticks = [ts + datetime.timedelta(hours=2*i) for i in range(13)]
plt.gca().set_xticks(ticks, minor=False)

plt.xlim(ts,ts + datetime.timedelta(hours=24))

plt.gcf().savefig('paper_times_hist.pdf', dpi=150)



plt.figure()

B = A.sum(axis=0)
plt.bar(range(13), B, facecolor='teal', alpha=0.75)
plt.gca().set_xticks(range(13), minor=False)
plt.xlabel("Vertiport number")
plt.ylabel("Number of flights")
plt.gcf().savefig('paper_ports2_hist.pdf', dpi=150)