Map of tornado historic tornado traces
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# -*- coding: utf-8 -*-
import csv
from dataclasses import dataclass
from datetime import datetime
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import cartopy.feature as cfeature
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
from cartopy import geodesic
import shapely.geometry as sgeom
proj = ccrs.AlbersEqualArea(
central_longitude=-93,
central_latitude=35,
)
water_blue = "#7ebfd4"
def phys(name, resolv):
return cfeature.NaturalEarthFeature('physical', name, resolv, facecolor="none")
def cultural(name, resolv):
return cfeature.NaturalEarthFeature('cultural', name, resolv, facecolor="none")
land = phys("land", "50m")
rivers = phys("rivers_lake_centerlines", "50m")
lakes = phys("lakes", "50m")
countries = cultural("admin_0_countries", "50m")
states = cultural("admin_1_states_provinces_lines", "50m")
@dataclass
class Tornado:
om: str
yr: str
mo: str
dy: str
date: str
time: str
tz: str
st: str
stf: str
stn: str
mag: str
inj: str
fat: str
loss: str
closs: str
slat: str
slon: str
elat: str
elon: str
len: str
wid: str
ns: str
sn: str
sg: str
f1: str
f2: str
f3: str
f4: str
fc: str
def __post_init__(self):
self.id = int(self.om)
self.dt = datetime.strptime(self.date, "%Y-%m-%d")
self.slon = float(self.slon)
self.slat = float(self.slat)
self.elon = float(self.elon)
self.elat = float(self.elat)
def __repr__(self):
return "<tornado {id} {date}>".format(id=self.id, date=self.dt)
def read_data():
tornados = []
with open("1950-2017_actual_tornadoes.csv", newline='') as csvfile:
reader = csv.DictReader(csvfile)
for i, row in enumerate(reader):
tornados.append(Tornado(**row))
return tornados
def draw_map(lons, lats):
fig = plt.figure(frameon=False, figsize=(8, 4.61))
ax = fig.add_axes([0, 0, 1, 1], projection=proj)
ax.background_patch.set_facecolor(water_blue)
ax.set_extent([-122, -65, 20, 50], ccrs.Geodetic())
ax.add_feature(land, facecolor="#f0f0f0")
ax.add_feature(rivers, edgecolor=water_blue)
ax.add_feature(lakes, facecolor=water_blue)
ax.add_feature(countries, edgecolor="grey", linewidth=0.2, alpha=0.6, dashes='--')
ax.add_feature(states, edgecolor="grey", linewidth=0.2, alpha=0.4, dashes='--')
ax.plot(lons, lats, 'r', lw=0.2, alpha=0.7, transform=ccrs.Geodetic())
ax.axis('off')
plt.savefig("tornados_us.png", dpi=320)
if __name__ == '__main__':
ts = read_data()
lons = []
lats = []
for t in ts:
if t.elon < 0:
lons.append(t.slon)
lons.append(t.elon)
lons.append(None)
lats.append(t.slat)
lats.append(t.elat)
lats.append(None)
draw_map(lons, lats)