87 lines
2.3 KiB
Python
87 lines
2.3 KiB
Python
import json
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import matplotlib.pyplot as plt
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import numpy as np
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plt.rcParams["figure.figsize"] = [18, 9]
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plt.style.use("dark_background")
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plt.subplots_adjust(left=0.05, right=0.99, top=0.95, bottom=0.05)
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def colour(k: int):
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k, r = divmod(k, 256)
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k, g = divmod(k, 256)
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k, b = divmod(k, 256)
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return r, g, b
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with open("metrics.json", "r") as file:
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entries = json.load(file)
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entries_grouped: dict[int, list] = {}
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def group_entries():
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for i, entry in entries:
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entries_grouped.setdefault(i, []).append(entry)
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group_entries()
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def render_halstead(h_colour: bool):
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units = []
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for i, entry in entries:
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x = -i
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y = entry["metrics"]["halstead"]["difficulty"] or 0.0
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nh = hash(entry["name"])
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y += (nh % 201 - 100) / 500
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if h_colour:
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r, g, b = colour(nh)
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units.append((x, y, r, g, b))
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else:
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c = entry["metrics"]["halstead"]["bugs"] or 0.0
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units.append((x, y, c))
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if h_colour:
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X, Y, R, G, B = np.array(units).transpose()
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C = np.array([R, G, B]).transpose() / 255
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C = 0.25 + 0.75 * C
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else:
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X, Y, C = np.array(units).transpose()
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plt.clf()
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plt.scatter(X, Y, s=2.0, c=C)
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plt.savefig("/code/colour.png" if h_colour else "/code/metrics.png")
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def render_ploc():
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units = []
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for i, group in entries_grouped.items():
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x = -i
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ys = [
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sum(entry["metrics"]["loc"]["ploc"] for entry in group),
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sum(entry["metrics"]["loc"]["cloc"] for entry in group),
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sum(entry["metrics"]["loc"]["blank"] for entry in group),
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]
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units.append((x, *ys))
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X, Yp, Yc, Yb = np.array(units).transpose()
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plt.clf()
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plt.axhline(8000, alpha=0.5)
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plt.axhline(7000, alpha=0.5)
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plt.axhline(6000, alpha=0.5)
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plt.axhline(0, alpha=0.5)
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plt.plot(X, Yp, label="code")
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plt.plot(X, Yc, label="comments/docs")
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plt.plot(X, Yb, label="blank")
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fmt, kwargs = ":", dict(alpha=0.5)
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plt.plot(X, Yc * (k := Yp[0] / Yc[0]), fmt, label=f"c/d x{round(k, 1)}", c="C1", **kwargs)
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plt.plot(X, Yb * (k := Yp[0] / Yb[0]), fmt, label=f"blank x{round(k, 1)}", c="C2", **kwargs)
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plt.legend()
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plt.ylim(bottom=0)
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plt.savefig("/code/ploc.png")
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render_ploc()
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render_halstead(False)
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render_halstead(True)
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