render in-memory caching

metrics/Dockerfile

@@ -11,6 +11,16 @@ RUN python3 /code/metrics.py
 RUN git fetch && git checkout 936f41735a4f7913e49fb16c44e89901bf703568
 RUN python3 /code/metrics.py
 
+RUN git fetch && git checkout f13a1382f8781231e01d375a13041884c87ddf0c
+RUN python3 /code/metrics.py
+
+RUN git fetch && git checkout ce65688e47b07f14ef2861971f64296c2197e778
+RUN python3 /code/metrics.py
+
+
+RUN git fetch && git checkout 7f1d72898ddd9ab40bf91e553f70a023a64fe647
+RUN python3 /code/metrics.py
+
 FROM python:3.11
 RUN python3 -m pip install matplotlib
 WORKDIR /code/

metrics/render.py

@@ -77,6 +77,7 @@ def render_ploc():
     plt.plot(X, Yc * (k := Yp[0] / Yc[0]), fmt, label=f"c/d x{round(k, 1)}", c="C1", **kwargs)
     plt.plot(X, Yb * (k := Yp[0] / Yb[0]), fmt, label=f"blank x{round(k, 1)}", c="C2", **kwargs)
     plt.legend()
+    plt.ylim(bottom=0)
     plt.savefig("/code/ploc.png")
 
 

xmetrics/Dockerfile

@@ -11,7 +11,7 @@ ENV SRCPATTERN="*.cs"
 FROM metrics-base as metrics-radn
 RUN git clone https://gitea.parrrate.ru/PTV/radn-rs.git
 WORKDIR /code/radn-rs/
-RUN git fetch && git checkout 936f41735a4f7913e49fb16c44e89901bf703568
+RUN git fetch && git checkout 7f1d72898ddd9ab40bf91e553f70a023a64fe647
 
 FROM metrics-base as metrics-mdbook
 RUN git clone https://github.com/rust-lang/mdBook.git

xmetrics/metrics.py

@@ -21,7 +21,7 @@ for i, commit in enumerate(reversed(commits)):
         lines = path.read_bytes().splitlines()
         lines = (line.strip() for line in lines)
         lines = (line for line in lines if line)
-        # lines = set(lines)
+        lines = set(lines)
         current_ctr.update(lines)
     added = current_ctr - last_ctr
     deleted = last_ctr - current_ctr

xmetrics/render.py

@@ -1,13 +1,14 @@
 import json
+from functools import cache
 
 import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.colors import hsv_to_rgb
-from scipy.io import wavfile
 
 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)
+plt.margins(x=0.025)
 
 
 with open("metrics.json", "r") as file:
@@ -19,35 +20,101 @@ with open("metrics.json", "r") as file:
 def render_ploc():
     X, Y, Ya, Yd = np.array(entries).transpose()
     plt.clf()
-    plt.plot(X, Y)
-    plt.fill_between(X, Y, Y - Ya, alpha=0.5, color="green")
-    plt.fill_between(X, Y, Y + Yd, alpha=0.5, color="red")
+    plt.plot(X, Y, linewidth=1.0)
+    plt.fill_between(
+        X,
+        Y - Ya,
+        Y,
+        alpha=0.5,
+        color="green",
+        linewidth=0.0,
+    )
+    plt.fill_between(
+        X,
+        Y,
+        Y + Yd,
+        alpha=0.5,
+        color="red",
+        linewidth=0.0,
+    )
+    plt.ylim(bottom=0)
     plt.savefig("/code/metrics/metrics.png")
 
 
-def render_cors(*, px, pc):
-    M = len(cors)
-    N = len(cors[0])
-    Y = np.array(cors)
+@cache
+def get_m():
+    return len(cors)
+
+
+@cache
+def get_n():
+    return len(cors[0])
+
+
+@cache
+def get_y():
+    return np.array(cors)
+
+
+@cache
+def _get_x(px: bool):
     if px:
-        X = abs(np.diff(Y, axis=1, prepend=0)).sum(axis=0).cumsum()
+        return abs(np.diff(get_y(), axis=1, prepend=0)).sum(axis=0).cumsum()
     else:
-        X = np.arange(N)
-    assert Y.shape == (M, N)
-    W = Y.max(axis=1)
-    I = W.cumsum()
-    assert I.shape == (M,)
-    plt.clf()
+        return np.arange(get_n())
+
+
+def get_x(*, px: bool):
+    return _get_x(px)
+
+
+@cache
+def get_w():
+    return get_y().max(axis=1)
+
+
+@cache
+def _get_z(pc: bool):
+    M = get_m()
     if pc:
-        Z = (I - W / 2) / I.max() * M
+        W = get_w()
+        I = W.cumsum()
+        assert I.shape == (M,)
+        return (I - W / 2) / I.max() * M
     else:
-        Z = np.arange(M)
-    colours = hsv_to_rgb(np.array([3.0 * Z / M % 1, 0.4 + Z * 0, 0.6 + 0.15 * (Z / M)]).transpose())
+        return np.arange(M)
+
+
+def get_z(*, pc: bool):
+    return _get_z(pc)
+
+
+@cache
+def _get_c(pc: bool):
+    M = get_m()
+    Z = get_z(pc=pc)
+    W = get_w()
+    return hsv_to_rgb(np.array([3.0 * Z / M % 1, 0.4 + Z * 0, 0.6 + 0.15 * (Z / M)]).transpose())
+
+
+def get_c(*, pc: bool):
+    return _get_c(pc)
+
+
+def render_cors(*, px, pc):
+    M = get_m()
+    N = get_n()
+    Y = get_y()
+    X = get_x(px=px)
+    assert Y.shape == (M, N)
+    plt.clf()
+    C = get_c(pc=pc)
     plt.stackplot(
         X,
         Y,
-        colors=colours,
+        colors=C,
         aa=False,
+        linewidth=0.0,
     )
     plt.savefig(f"/code/metrics/metrics-px{int(px)}-pc{int(pc)}.png")