analysis project

project.py

import pandas as pd
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from colour import Color

color_table = [Color("red"), Color("orange"), Color(
    "yellow"), Color("green"), Color("blue")]

df = pd.read_csv('analysis/covid19_data.csv')
df = df.loc[(df["Country/Region"] == "US")]
df = df.loc[df["Province/State"].str.contains(r', CA')]

last_date = '3/31/20'
last_index = np.where(df.columns.values == last_date)[0][0]

eqs = []

for index, row in df.iterrows():
    min_d, min_i = 100000, None
    for index2, row2 in df.iterrows():
        if index != index2:
            d = np.sqrt((row2["Lat"]-row["Lat"])**2 +
                        (row2["Long"]-row["Long"])**2)
            if d < min_d and row2[last_date] < row[last_date]:
                min_d, min_i = d, row2
    if min_i is not None:
        print("main point", row["Lat"], row["Long"],
              row[last_date], row["Response Severity"])
        print("closest point", min_d,
              min_i["Lat"], min_i["Long"], min_i[last_date], min_i["Response Severity"])
        d_calc = (-(row["Lat"] - min_i["Lat"])**2 -
                  (row["Long"] - min_i["Long"])**2)/(-row[last_date])
        eqs.append((row["Lat"], row["Long"], d_calc, row[last_date],
                    color_table[int(row["Response Severity"]-1)], color_table[int(min_i["Response Severity"]-1)]))
        print(eqs[-1])


def elliptic_parab(eq, x, y):
    return [(-((x - eq[0])**2 / eq[2]) - ((y - eq[1])**2 / eq[2]))+eq[3], eq[4]]


x = np.arange(df["Lat"].min().round(1)-1, df["Lat"].max().round(1)+1, 0.01)
y = np.arange(df["Long"].min().round(1)-1, df["Long"].max().round(1)+1, 0.01)
x, y = np.meshgrid(x, y)

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

colors = np.empty(x.shape, dtype='|U18')
colors.fill(color_table[4].hex_l)
z_final = np.zeros(x.shape)

for eq in eqs:
    z, c = elliptic_parab(eq, x, y)
    # z_final = np.maximum(z_final, z)

    for yi in range(x.shape[1]):
        for xi in range(x.shape[0]):
            if z_final[xi][yi] < z[xi][yi]:
                z_final[xi][yi] = z[xi][yi]
                colors[xi][yi] = c.hex_l

ax.plot(df["Lat"].round(1), df["Long"].round(1), df[last_date],
        marker='o', linestyle='', alpha=1)
surf = ax.plot_surface(x, y, z_final, linewidth=0, facecolors=colors)
ax.set_xlabel('Latitude')
ax.set_ylabel('Longitude')
ax.set_zlabel('# of Cases')

plt.show()

Color(
    "yellow")