xox/coronavis
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

increase figure width

Browse Source
This commit is contained in:
fordprefect
2020-03-27 17:00:36 +01:00
parent 99a9677642
commit d8ebab65f3
5 changed files with 13 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
basics.py
View File

@@ -4,11 +4,11 @@ Plot total cases of countries over time on log scale
import matplotlib.pyplot as pp import matplotlib.pyplot as pp
def plot(data, countries): def plot(data, countries):
figsize = (10,5)
tcp, tc = pp.subplots() tcp, tc = pp.subplots(figsize=figsize)
tdp, td = pp.subplots() tdp, td = pp.subplots(figsize=figsize)
ncp, nc = pp.subplots() ncp, nc = pp.subplots(figsize=figsize)
ndp, nd = pp.subplots() ndp, nd = pp.subplots(figsize=figsize)
for loc in data: for loc in data:
if loc not in countries: if loc not in countries:
continue continue

3
death_per_case.py
View File

@@ -6,13 +6,14 @@ import numpy as np
name="death_per_case" name="death_per_case"
def plot(data, countries): def plot(data, countries):
figsize = (10,5)
for loc in data: for loc in data:
if loc not in countries: if loc not in countries:
continue continue
time, new_cases, new_deaths, total_cases, total_deaths = data[loc] time, new_cases, new_deaths, total_cases, total_deaths = data[loc]
# death/case # death/case
pp.figure(name) pp.figure(name, figsize=figsize)
pp.plot(time, np.array(total_deaths)/np.array(total_cases), label=f"{loc}", marker=".") pp.plot(time, np.array(total_deaths)/np.array(total_cases), label=f"{loc}", marker=".")
pp.yscale("log") pp.yscale("log")

3
delay_from_china.py
View File

@@ -6,12 +6,13 @@ import numpy as np
name="delay" name="delay"
def plot(data, countries): def plot(data, countries):
figsize = (10,5)
for loc in data: for loc in data:
if loc not in countries: if loc not in countries:
continue continue
time, new_cases, new_deaths, total_cases, total_deaths = data[loc] time, new_cases, new_deaths, total_cases, total_deaths = data[loc]
pp.figure(name) pp.figure(name, figsize=figsize)
day_of_above_hundred_cases = np.argwhere(np.array(total_cases) > 100)[0][0] day_of_above_hundred_cases = np.argwhere(np.array(total_cases) > 100)[0][0]
new_time_axis = np.arange(len(time)) - day_of_above_hundred_cases new_time_axis = np.arange(len(time)) - day_of_above_hundred_cases

3
delay_from_usa.py
View File

@@ -6,12 +6,13 @@ import numpy as np
name="delay" name="delay"
def plot(data, countries): def plot(data, countries):
figsize = (10,5)
for loc in data: for loc in data:
if loc not in countries: if loc not in countries:
continue continue
time, new_cases, new_deaths, total_cases, total_deaths = data[loc] time, new_cases, new_deaths, total_cases, total_deaths = data[loc]
pp.figure(name) pp.figure(name, figsize=figsize)
day_of_above_hundred_cases = np.argwhere(np.array(total_cases) > 100)[0][0] day_of_above_hundred_cases = np.argwhere(np.array(total_cases) > 100)[0][0]
new_time_axis = np.arange(len(time)) - day_of_above_hundred_cases new_time_axis = np.arange(len(time)) - day_of_above_hundred_cases

3
normalized_to_first_death.py
View File

@@ -6,12 +6,13 @@ import numpy as np
name="normalized_to_first_death" name="normalized_to_first_death"
def plot(data, countries): def plot(data, countries):
figsize = (10,5)
for loc in data: for loc in data:
if loc not in countries: if loc not in countries:
continue continue
time, new_cases, new_deaths, total_cases, total_deaths = data[loc] time, new_cases, new_deaths, total_cases, total_deaths = data[loc]
pp.figure(name) pp.figure(name, figsize=figsize)
day_of_first_death = np.argwhere(np.array(total_deaths) > 0)[0][0] day_of_first_death = np.argwhere(np.array(total_deaths) > 0)[0][0]
new_time_axis = np.arange(len(time)) - day_of_first_death new_time_axis = np.arange(len(time)) - day_of_first_death
pp.plot(new_time_axis, np.array(total_cases), label=f"{loc}", marker=".") pp.plot(new_time_axis, np.array(total_cases), label=f"{loc}", marker=".")