Update workflow configuration and replace Altair with Matplotlib for signal visualizations

.forgejo/workflows/serve.yaml

@@ -9,12 +9,12 @@ jobs:
       - name: Checkout repository
         uses: actions/checkout@v4
       - name: Initialize virtual environment
-        run: /usr/bin/python -m venv .env
+        run: /usr/bin/python -m venv .venv
       - name: Install dependencies
-        run: ./.env/bin/pip install mystmd jupyter jupyterlab_myst ipykernel altair pandas
+        run: ./.venv/bin/pip install -r requirements.txt
       - name: Build static HTML
         run: |
-          . .env/bin/activate
+          . .venv/bin/activate
           myst build --execute --html
       - name: Copy files
         run: |

cours/SIN/01-capteurs.md

@@ -60,7 +60,7 @@ Une thermistance (@thermistance) ou une jauge de déformation (@jauge) sont des
 capteurs analogiques.
 
 ::::{figure}
-:label: analogique
+:label: cap_analogique
 :::{figure} https://upload.wikimedia.org/wikipedia/commons/3/3b/NTC_bead.jpg
 :label: thermistance
 

cours/SIN/02-signaux.md

@@ -32,32 +32,26 @@ et un niveau **bas** ("Low").
 :label: logique
 ```{code-cell} python
 :tags: [remove-input]
-import altair as alt
+import matplotlib.pyplot as plt
+from matplotlib import ticker
 import numpy as np
-import pandas as pd
 
 rng = np.random.default_rng(25)
 
 n = 16
 t = np.arange(n+1)
-s = rng.choice([0, 1], n+1)
-s[-1] = s[-2]
-data = pd.DataFrame({
-  "t": t,
-  "s": s,
-})
-alt.Chart(
-  data
-).mark_line(
-  interpolate="step-after",
-  strokeWidth=3,
-).encode(
-  alt.X("t:Q").axis(title="Temps (s)").scale(domain=(0,n)),
-  alt.Y("s:Q", axis=alt.Axis(title="Signal logique", values=[0, 1], format=".0f")).scale(domain=(0,1)),
-).properties(
-  width="container",
-  height=100,
+s = rng.choice([0, 1], n)
+
+fig, ax = plt.subplots()
+ax.stairs(s, t, lw=3)
+ax.set(
+  xlim=(0, n),
+  ylim=(-.5, 1.5),
+  xlabel="Temps (s)",
+  ylabel="Signal logique",
 )
+ax.yaxis.set_major_locator(ticker.MultipleLocator(1))
+ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
 ```
 Exemple de signal logique
 ````
@@ -77,35 +71,38 @@ Un exemple de signal analogique est donné en @analogique.
 :label: analogique
 ```{code-cell} python
 :tags: [remove-input]
-import altair as alt
+import matplotlib.pyplot as plt
+from matplotlib import ticker
 import numpy as np
-import pandas as pd
+from scipy.interpolate import CubicSpline
+from scipy.stats import qmc
+
 
 rng = np.random.default_rng(25)
 
 n = 20
 t_max = 16
 
-t = np.linspace(0, t_max, n)
-
+t_base = np.linspace(0, t_max, n)
+lhs = (qmc.LatinHypercube(d=n-2, rng=rng).random(1)[0] - .5) * t_max/n
+t = t_base + np.concatenate(([0], lhs, [0]))
+t = t_base
 s = 5 * rng.random(n)
 s[-1] = s[-2]
-data = pd.DataFrame({
-  "t": t,
-  "s": s,
-})
-alt.Chart(
-  data
-).mark_line(
-  interpolate="basis",
-  strokeWidth=3,
-).encode(
-  alt.X("t:Q").axis(title="Temps (s)").scale(domain=(0,t_max)),
-  alt.Y("s:Q", axis=alt.Axis(title="Signal analogique")).scale(domain=(0,5)),
-).properties(
-  width="container",
-  height=200,
+
+t_interp = np.linspace(0, t_max, 1024)
+s_interp = np.clip(CubicSpline(t, s)(t_interp), 0, 5)
+
+fig, ax = plt.subplots()
+ax.plot(t_interp, s_interp, lw=3)
+ax.set(
+  xlim=(0, t_max),
+  ylim=(-.5, 5.5),
+  xlabel="Temps (s)",
+  ylabel="Signal analogique",
 )
+ax.yaxis.set_major_locator(ticker.MultipleLocator(1))
+ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
 ```
 Exemple de signal analogique
 ````
@@ -119,32 +116,38 @@ Un exemple de signal analogique est donné en @numerique.
 :label: numerique
 ```{code-cell} python
 :tags: [remove-input]
-import altair as alt
+import matplotlib.pyplot as plt
+from matplotlib import ticker
 import numpy as np
-import pandas as pd
 
 rng = np.random.default_rng(25)
 
 n = 16
 t = np.arange(n+1)
-s = rng.integers(0, 16, n+1)
-s[-1] = s[-2]
-data = pd.DataFrame({
-  "t": t,
-  "s": s,
-})
-alt.Chart(
-  data
-).mark_line(
-  interpolate="step-after",
-  strokeWidth=3,
-).encode(
-  alt.X("t:Q").axis(title="Temps (s)").scale(domain=(0,n)),
-  alt.Y("s:Q", axis=alt.Axis(title="Signal numérique", values=np.arange(0, 16))).scale(domain=(0,15)),
-).properties(
-  width="container",
-  height=200,
+s = rng.integers(0, 16, n)
+
+fig, ax = plt.subplots()
+ax.stairs(s, t, lw=3)
+ax.set(
+  xlim=(0, n),
+  ylim=(-.5, 16.5),
+  xlabel="Temps (s)",
+  ylabel="Signal numérique",
 )
+ax.yaxis.set_major_locator(ticker.MultipleLocator(1))
+ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
+# alt.Chart(
+#   data
+# ).mark_line(
+#   interpolate="step-after",
+#   strokeWidth=3,
+# ).encode(
+#   alt.X("t:Q").axis(title="Temps (s)").scale(domain=(0,n)),
+#   alt.Y("s:Q", axis=alt.Axis(title="Signal numérique", values=np.arange(0, 16))).# scale(domain=(0,15)),
+# ).properties(
+#   width="container",
+#   height=200,
+# )
 ```
 Exemple de signal numérique
 ````

cours/SIN/matplotlibrc

@@ -0,0 +1 @@
+../../matplotlibrc

matplotlibrc

@@ -0,0 +1,43 @@
+lines.linewidth: 3
+
+font.family: Fira Code
+
+image.cmap: inferno
+
+axes.linewidth: 1
+axes.grid: True
+axes.grid.which: major
+axes.titlelocation: right
+axes.titleweight: 700
+axes.axisbelow: True
+
+axes.prop_cycle: cycler(color=["#4269d0","#efb118","#ff725c","#6cc5b0","#3ca951","#ff8ab7","#a463f2","#97bbf5","#9c6b4e","#9498a0"])
+
+axes.formatter.use_locale: True
+
+grid.color: "#bebebe"
+grid.linewidth: 1
+grid.alpha: 1
+
+hatch.linewidth: 8
+hatch.color: "#00000013"
+
+boxplot.showmeans: true
+boxplot.meanprops.markeredgecolor: "k"
+boxplot.meanprops.marker: "+"
+boxplot.flierprops.markerfacecolor: C0
+boxplot.medianprops.color: C0
+
+figure.figsize: 8, 4.5
+figure.dpi: 96
+figure.constrained_layout.use: True
+
+xtick.direction: in
+xtick.major.size: 4
+xtick.minor.size: 2
+
+ytick.direction: in
+ytick.major.size: 4
+ytick.minor.size: 2
+
+savefig.format: pdf

requirements.txt

@@ -0,0 +1,7 @@
+mystmd
+jupyter-server
+ipykernel
+matplotlib
+numpy
+pandas
+scipy