Improve plotting script

This commit is contained in:
Midgard 2024-04-25 21:31:47 +02:00
parent 225dc70cc8
commit 0baab314ed
Signed by: midgard
GPG key ID: 511C112F1331BBB4
2 changed files with 53 additions and 25 deletions

1
.gitignore vendored
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@ -3,3 +3,4 @@ legacy/
__pycache__/ __pycache__/
*.pyc *.pyc
*.pyo *.pyo
*.png

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@ -1,7 +1,7 @@
#!/usr/bin/env python3 #!/usr/bin/env python3
from datetime import timezone, datetime from datetime import timezone, datetime
import parse_numberdealers from numberdealers import parse_numberdealers
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
@ -10,8 +10,8 @@ def xy(messages):
x = [] x = []
y = [] y = []
for msg in messages: for msg in messages:
x.append(datetime.fromtimestamp(msg.create_at / 1000, timezone.utc)) # x.append(datetime.fromtimestamp(msg.create_at / 1000, timezone.utc))
# x.append(msg.create_at / 1000) x.append(msg.create_at / 1000)
y.append(msg.recognized_number) y.append(msg.recognized_number)
return x, y return x, y
@ -22,44 +22,71 @@ def find(xs, condition):
return i return i
def abline(slope, intercept): def abline(slope, intercept, point1_x, point2_x):
"""Plot a line from slope and intercept""" """Plot a line from slope and intercept"""
axes = plt.gca() axes = plt.gca()
x_vals = np.array(axes.get_xlim()) x_vals = np.array([point1_x, point2_x])
y_vals = slope * x_vals + intercept y_vals = slope * x_vals + intercept
plt.plot(x_vals, y_vals, '--') plt.plot(x_vals, y_vals, linewidth=1, color='grey')
def main(): def main():
import sys import sys
if len(sys.argv) <= 2:
print("Usage: plot_numberdealers.py <numberdealers.json> <numberdealers-ng.json>")
return 1
with open(sys.argv[1], encoding="utf-8") as fh: with open(sys.argv[1], encoding="utf-8") as fh:
numbers_og, _errors = parse_numberdealers.parse(fh) numbers_og, _errors = parse_numberdealers.parse(fh)
with open(sys.argv[2], encoding="utf-8") as fh: with open(sys.argv[2], encoding="utf-8") as fh:
numbers_ng, _errors = parse_numberdealers.parse(fh) numbers_ng, _errors = parse_numberdealers.parse(fh)
# start_of_current_slope = find(numbers_og, lambda msg: msg.recognized_number <= 10464) start_of_current_slope = find(numbers_og, lambda msg: msg.create_at >= numbers_ng[0].create_at)
# slope_og = ( # a = (y2-y1) / (x2-x1)
# numbers_og[-1].recognized_number - numbers_og[start_of_current_slope].recognized_number slope_og = (
# ) / ( numbers_og[-1].recognized_number - numbers_og[start_of_current_slope].recognized_number
# numbers_og[-1].create_at/1000 - numbers_og[start_of_current_slope].create_at/1000 ) / (
# ) numbers_og[-1].create_at/1000 - numbers_og[start_of_current_slope].create_at/1000
# # b = y - a x )
# intercept_og = numbers_og[-1].recognized_number - slope_og * numbers_og[-1].create_at # b = y - a x
intercept_og = numbers_og[-1].recognized_number - slope_og * numbers_og[-1].create_at/1000
# slope_ng = ( slope_ng = (
# numbers_ng[-1].recognized_number - numbers_ng[0].recognized_number numbers_ng[-1].recognized_number - numbers_ng[0].recognized_number
# ) / ( ) / (
# numbers_ng[-1].create_at/1000 - numbers_ng[0].create_at/1000 numbers_ng[-1].create_at/1000 - numbers_ng[0].create_at/1000
# ) )
# intercept_ng = numbers_ng[-1].recognized_number - slope_ng * numbers_ng[-1].create_at intercept_ng = numbers_ng[-1].recognized_number - slope_ng * numbers_ng[-1].create_at/1000
fig, ax = plt.subplots() # a1 x + b1 = a2 x + b2
# (a1 - a2) x = b2 - b1
# x = (b2 - b1) / (a1 - a2)
intercept_x = (intercept_ng - intercept_og) / (slope_og - slope_ng)
intercept_y = slope_ng * intercept_x + intercept_ng
fig, ax = plt.subplots(figsize=(15, 6))
ax.plot(*xy(numbers_og)) ax.plot(*xy(numbers_og))
ax.plot(*xy(numbers_ng)) ax.plot(*xy(numbers_ng))
# abline(slope_og, -120000) abline(slope_og, intercept_og, numbers_og[-1].create_at/1000, intercept_x)
# abline(slope_ng, -500000) abline(slope_ng, intercept_ng, numbers_ng[-1].create_at/1000, intercept_x)
plt.show()
plt.margins(x=0)
locs = np.append(
np.linspace(numbers_og[0].create_at/1000, numbers_ng[0].create_at/1000, 6),
[numbers_ng[-1].create_at/1000, intercept_x]
)
# func = lambda x: x < intercept_x
# locs = np.append(locs[func(locs)][:-1], [intercept_x])
labels = ["{:%Y-%m-%d}".format(datetime.fromtimestamp(x, timezone.utc)) for x in locs]
plt.xticks(locs, labels)
plt.grid()
# plt.show()
plt.savefig("plot.png")
return 0
if __name__ == "__main__": if __name__ == "__main__":
main() import sys
sys.exit(main())