43 lines
990 B
Python
43 lines
990 B
Python
import gc
|
|
import json
|
|
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
|
|
plt.rcParams["figure.figsize"] = [18, 9]
|
|
plt.style.use("dark_background")
|
|
plt.subplots_adjust(left=0.05, right=0.99, top=0.95, bottom=0.05)
|
|
|
|
|
|
def colour(k: int):
|
|
k, r = divmod(k, 256)
|
|
k, g = divmod(k, 256)
|
|
k, b = divmod(k, 256)
|
|
return r, g, b
|
|
|
|
|
|
with open("metrics.json", "r") as file:
|
|
entries = json.load(file)
|
|
|
|
h_colour = True
|
|
|
|
units = []
|
|
for i, entry in entries:
|
|
x = i
|
|
y = entry["metrics"]["halstead"]["difficulty"] or 0.0
|
|
nh = hash(entry["name"])
|
|
y += (nh % 201 - 100) / 500
|
|
if h_colour:
|
|
r, g, b = colour(nh)
|
|
units.append((x, y, r, g, b))
|
|
else:
|
|
c = entry["metrics"]["halstead"]["bugs"] or 0.0
|
|
units.append((x, y, c))
|
|
if h_colour:
|
|
X, Y, R, G, B = np.array(units).transpose()
|
|
C = np.array([R, G, B]).transpose() / 255
|
|
else:
|
|
X, Y, C = np.array(units).transpose()
|
|
plt.scatter(-X, Y, s=2.0, c=C)
|
|
plt.savefig("/code/metrics.png")
|