Autoformat with ruff

Author: jarrodmillman

advanced/mathematical_optimization/examples/plot_compare_optimizers.py

@@ -29,9 +29,11 @@
 method_names.sort(key=lambda x: x[::-1], reverse=True)
 
 for n_dim_index, ((n_dim, n_dim_bench), color) in enumerate(
-    zip(sorted(results.items()), colors)
+    zip(sorted(results.items()), colors, strict=True)
 ):
-    for (cost_name, cost_bench), symbol in zip(sorted(n_dim_bench.items()), symbols):
+    for (cost_name, cost_bench), symbol in zip(
+        sorted(n_dim_bench.items()), symbols, strict=True
+    ):
         for (
             method_index,
             method_name,
@@ -50,7 +52,7 @@
             )
 
 # Create a legend for the problem type
-for cost_name, symbol in zip(sorted(n_dim_bench.keys()), symbols):
+for cost_name, symbol in zip(sorted(n_dim_bench.keys()), symbols, strict=True):
     plt.semilogy(
         [
             -10,
@@ -71,7 +73,7 @@
 # Create a second legend for the problem dimensionality
 plt.twinx()
 
-for n_dim, color in zip(sorted(results.keys()), colors):
+for n_dim, color in zip(sorted(results.keys()), colors, strict=True):
     plt.plot(
         [
             -10,

advanced/mathematical_optimization/examples/plot_gradient_descent.py

@@ -10,7 +10,8 @@
 import matplotlib.pyplot as plt
 import scipy as sp
 
-import sys, os
+import sys
+import os
 
 sys.path.append(os.path.abspath("helper"))
 from cost_functions import (
@@ -245,7 +246,7 @@ def store(X):
     )
     contours = plt.contour(
         log_z,
-        levels=levels.get(f, None),
+        levels=levels.get(f),
         extent=[x_min, x_max, y_min, y_max],
         cmap=plt.cm.gnuplot,
         origin="lower",

intro/matplotlib/examples/plot_bar.py

@@ -18,10 +18,10 @@
 plt.bar(X, +Y1, facecolor="#9999ff", edgecolor="white")
 plt.bar(X, -Y2, facecolor="#ff9999", edgecolor="white")
 
-for x, y in zip(X, Y1):
+for x, y in zip(X, Y1, strict=True):
     plt.text(x + 0.4, y + 0.05, f"{y:.2f}", ha="center", va="bottom")
 
-for x, y in zip(X, Y2):
+for x, y in zip(X, Y2, strict=True):
     plt.text(x + 0.4, -y - 0.05, f"{y:.2f}", ha="center", va="top")
 
 plt.xlim(-0.5, n)

intro/matplotlib/examples/plot_polar.py

@@ -18,7 +18,7 @@
 width = np.pi / 4 * rng.random(N)
 bars = plt.bar(theta, radii, width=width, bottom=0.0)
 
-for r, bar in zip(radii, bars):
+for r, bar in zip(radii, bars, strict=True):
     bar.set_facecolor(plt.cm.jet(r / 10.0))
     bar.set_alpha(0.5)
 

intro/matplotlib/examples/pretty_plots/plot_polar_ext.py

@@ -17,7 +17,7 @@
 radii = 10 * rng.random(N)
 width = np.pi / 4 * rng.random(N)
 bars = plt.bar(theta, radii, width=width, bottom=0.0)
-for r, bar in zip(radii, bars):
+for r, bar in zip(radii, bars, strict=True):
     bar.set_facecolor(plt.cm.jet(r / 10.0))
     bar.set_alpha(0.5)
 plt.gca().set_xticklabels([])

packages/scikit-learn/examples/plot_pca.py

@@ -31,7 +31,7 @@
 import matplotlib.pyplot as plt
 
 plt.figure(figsize=(6, 5))
-for i, c, label in zip(target_ids, "rgbcmykw", iris.target_names):
+for i, c, label in zip(target_ids, "rgbcmykw", iris.target_names, strict=False):
     plt.scatter(X_pca[y == i, 0], X_pca[y == i, 1], c=c, label=label)
 plt.legend()
 plt.show()

packages/scikit-learn/examples/plot_tsne.py

@@ -38,7 +38,7 @@
 
 plt.figure(figsize=(6, 5))
 colors = "r", "g", "b", "c", "m", "y", "k", "w", "orange", "purple"
-for i, c, label in zip(target_ids, colors, digits.target_names):
+for i, c, label in zip(target_ids, colors, digits.target_names, strict=True):
     plt.scatter(X_2d[y == i, 0], X_2d[y == i, 1], c=c, label=label)
 plt.legend()
 plt.show()