Apply Python linting fixes across src/ and exercise files

- Fix import sorting, unused imports, and undefined names
- Modernize syntax (f-strings, raw strings for regex)
- Add src/compat/ module with replacements for deprecated scitools
- Update pyproject.toml with ruff configuration
- Apply consistent formatting to exercise files in doc/.src/chapters/

Author: ggorman

doc/.src/chapters/diffu/exer-diffu/axisymm_flow.py

@@ -63,7 +63,7 @@ def solver_theta(I, a, R, Nr, D, T, theta=0.5, u_L=None, u_R=0, user_action=None
     r*alpha is needed midway between spatial mesh points, - use
     arithmetic mean of successive mesh values (i.e. of r_i*alpha_i)
     """
-    t0 = time.clock()
+    t0 = time.perf_counter()
 
     r = linspace(0, R, Nr + 1)  # mesh points in space
     dr = r[1] - r[0]
@@ -163,7 +163,7 @@ def solver_theta(I, a, R, Nr, D, T, theta=0.5, u_L=None, u_R=0, user_action=None
         # Switch variables before next step
         u_1, u = u, u_1
 
-    t1 = time.clock()
+    t1 = time.perf_counter()
     # return u_1, since u and u_1 are switched
     return u_1, t, t1 - t0
 

doc/.src/chapters/diffu/exer-diffu/surface_osc.py

@@ -35,21 +35,16 @@
 
 print(sol[0].shape)
 print(sol[1].shape)
-import scitools.std as plt
+import matplotlib.pyplot as plt
 
 counter = 0
 for u0, u1 in zip(sol[0][2:], sol[1][2:], strict=False):
     x0 = sol[0][0]
     x1 = sol[1][0]
-    plt.plot(
-        x0,
-        u0,
-        "r-",
-        x1,
-        u1,
-        "b-",
-        legend=["short", "long"],
-        savefig="tmp_%04d.png" % counter,
-        axis=[x1[0], x1[-1], -1.1, 1.1],
-    )
+    plt.clf()
+    plt.plot(x0, u0, "r-", label="short")
+    plt.plot(x1, u1, "b-", label="long")
+    plt.legend()
+    plt.axis([x1[0], x1[-1], -1.1, 1.1])
+    plt.savefig("tmp_%04d.png" % counter)
     counter += 1

doc/.src/chapters/diffu/exer-diffu/welding.py

@@ -27,25 +27,21 @@ def run(gamma, beta=10, delta=40, scaling=1, animate=False):
 
     import time
 
-    import scitools.std as plt
+    import matplotlib.pyplot as plt
 
     plot_arrays = []
 
     def process_u(u, x, t, n):
         global ymax
         if animate:
-            plt.plot(
-                x,
-                u,
-                "r-",
-                x,
-                f(x, t[n]) / delta,
-                "b-",
-                axis=[0, L, ymin, ymax],
-                title=f"t={t[n]:f}",
-                xlabel="x",
-                ylabel=f"u and f/{delta:g}",
-            )
+            plt.clf()
+            plt.plot(x, u, "r-", x, f(x, t[n]) / delta, "b-")
+            plt.axis([0, L, ymin, ymax])
+            plt.title(f"t={t[n]:f}")
+            plt.xlabel("x")
+            plt.ylabel(f"u and f/{delta:g}")
+            plt.draw()
+            plt.pause(0.001)
         if t[n] == 0:
             time.sleep(1)
             plot_arrays.append(x)
@@ -65,18 +61,10 @@ def process_u(u, x, t, n):
     x = plot_arrays[0]
     plt.figure()
     for u, f in plot_arrays[1:]:
-        plt.plot(
-            x,
-            u,
-            "r-",
-            x,
-            f,
-            "b--",
-            axis=[x[0], x[-1], 0, ymax],
-            xlabel="$x$",
-            ylabel=rf"$u, \ f/{delta:g}$",
-        )
-        plt.hold("on")
+        plt.plot(x, u, "r-", x, f, "b--")
+    plt.axis([x[0], x[-1], 0, ymax])
+    plt.xlabel("$x$")
+    plt.ylabel(rf"$u, \ f/{delta:g}$")
     plt.legend(
         [
             "$u,\\ t=0.2$",

doc/.src/chapters/trunc/exer-trunk/trunc_vib_ic_fw.py

@@ -29,7 +29,6 @@ def visualize(u, t, I, w):
     plot(t, u, "r--o")
     t_fine = linspace(0, t[-1], 1001)  # very fine mesh for u_e
     u_e = exact_solution(t_fine, I, w)
-    hold("on")
     plot(t_fine, u_e, "b-")
     legend(["numerical", "exact"], loc="upper left")
     xlabel("t")
@@ -100,8 +99,6 @@ def main():
     parser.add_argument("--dt", type=float, default=0.05)
     parser.add_argument("--num_periods", type=int, default=5)
     parser.add_argument("--savefig", action="store_true")
-    # Hack to allow --SCITOOLS options (read when importing scitools.std)
-    parser.add_argument("--SCITOOLS_easyviz_backend", default="matplotlib")
     a = parser.parse_args()
     I, w, dt, num_periods, savefig = a.I, a.w, a.dt, a.num_periods, a.savefig
     P = 2 * pi / w  # one period
@@ -122,7 +119,6 @@ def plot_empirical_freq_and_amplitude(u, t, I, w):
     a = amplitudes(minima, maxima)
     figure()
     plot(range(len(p)), 2 * pi / p, "r-")
-    hold("on")
     plot(range(len(a)), a, "b-")
     plot(range(len(p)), [w] * len(p), "r--")
     plot(range(len(a)), [I] * len(a), "b--")
@@ -144,8 +140,9 @@ def visualize_front(u, t, I, w, savefig=False):
     curves as they evolve in time.
     Makes it easy to plot very long time series.
     """
-    import scitools.std as st
-    from scitools.MovingPlotWindow import MovingPlotWindow
+    import matplotlib.pyplot as plt
+
+    from compat.moving_plot_window import MovingPlotWindow
 
     P = 2 * pi / w  # one period
     umin = 1.2 * u.min()
@@ -156,21 +153,18 @@ def visualize_front(u, t, I, w, savefig=False):
     for n in range(1, len(u)):
         if plot_manager.plot(n):
             s = plot_manager.first_index_in_plot
-            st.plot(
-                t[s : n + 1],
-                u[s : n + 1],
-                "r-1",
-                t[s : n + 1],
-                I * cos(w * t)[s : n + 1],
-                "b-1",
-                title=f"t={t[n]:6.3f}",
-                axis=plot_manager.axis(),
-                show=not savefig,
-            )  # drop window if savefig
+            plt.clf()
+            plt.plot(t[s : n + 1], u[s : n + 1], "r-")
+            plt.plot(t[s : n + 1], I * cos(w * t)[s : n + 1], "b-")
+            plt.title(f"t={t[n]:6.3f}")
+            plt.axis(plot_manager.axis())
             if savefig:
                 filename = "tmp_vib%04d.png" % n
-                st.savefig(filename)
+                plt.savefig(filename)
                 print("making plot file", filename, f"at t={t[n]:g}")
+            else:
+                plt.draw()
+                plt.pause(0.001)
         plot_manager.update(n)
 
 
@@ -182,7 +176,7 @@ def visualize_front_ascii(u, t, I, w, fps=10):
     """
     import time
 
-    from scitools.avplotter import Plotter
+    from compat.ascii_plotter import Plotter
 
     P = 2 * pi / w
     umin = 1.2 * u.min()

doc/.src/chapters/vib/exer-vib/binary_star.py

@@ -1,7 +1,6 @@
-# import matplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 import numpy as np
 import odespy
-import scitools.std as plt
 
 
 def solver(alpha, ic, T, dt=0.05):
@@ -38,9 +37,10 @@ def demo_circular():
     # mass A is at (1, 0) with vel. (0, 1)
     ic = [1, 0, 0, 1, 0, 0, 0, 0]
     x_A, x_B, y_A, y_B, t = solver(alpha=0.001, ic=ic, T=2 * np.pi, dt=0.01)
-    plt.plot(
-        x_A, x_B, "r2-", y_A, y_B, "b2-", legend=["A", "B"], daspectmode="equal"
-    )  # x and y axis have same scaling
+    plt.plot(x_A, x_B, "r-", label="A")
+    plt.plot(y_A, y_B, "b-", label="B")
+    plt.gca().set_aspect("equal")
+    plt.legend()
     plt.savefig("tmp_circular.png")
     plt.savefig("tmp_circular.pdf")
     plt.show()
@@ -63,39 +63,24 @@ def demo_two_stars(animate=True):
     if animate:
         # Animate motion and draw the objects' paths in time
         for i in range(len(x_A)):
-            plt.plot(
-                x_A[: i + 1],
-                x_B[: i + 1],
-                "r-",
-                y_A[: i + 1],
-                y_B[: i + 1],
-                "b-",
-                [x_A[0], x_A[i]],
-                [x_B[0], x_B[i]],
-                "r2o",
-                [y_A[0], y_A[i]],
-                [y_B[0], y_B[i]],
-                "b4o",
-                daspectmode="equal",  # axes aspect
-                legend=["A", "B", "A", "B"],
-                axis=[-1, 1, -1, 1],
-                savefig="tmp_%04d.png" % i,
-                title=f"t={t[i]:.2f}",
-            )
+            plt.clf()
+            plt.plot(x_A[: i + 1], x_B[: i + 1], "r-", label="A")
+            plt.plot(y_A[: i + 1], y_B[: i + 1], "b-", label="B")
+            plt.plot([x_A[0], x_A[i]], [x_B[0], x_B[i]], "ro")
+            plt.plot([y_A[0], y_A[i]], [y_B[0], y_B[i]], "bo")
+            plt.gca().set_aspect("equal")
+            plt.legend()
+            plt.axis([-1, 1, -1, 1])
+            plt.title(f"t={t[i]:.2f}")
+            plt.savefig("tmp_%04d.png" % i)
     else:
         # Make a simple static plot of the solution
-        plt.plot(
-            x_A,
-            x_B,
-            "r-",
-            y_A,
-            y_B,
-            "b-",
-            daspectmode="equal",
-            legend=["A", "B"],
-            axis=[-1, 1, -1, 1],
-            savefig="tmp_two_stars.png",
-        )
+        plt.plot(x_A, x_B, "r-", label="A")
+        plt.plot(y_A, y_B, "b-", label="B")
+        plt.gca().set_aspect("equal")
+        plt.legend()
+        plt.axis([-1, 1, -1, 1])
+        plt.savefig("tmp_two_stars.png")
     # plt.axes().set_aspect('equal')  # mpl
     plt.show()
 
@@ -107,4 +92,4 @@ def demo_two_stars(animate=True):
         demo_circular()
     else:
         demo_two_stars(True)
-    raw_input()
+    input()

doc/.src/chapters/vib/exer-vib/elastic_pendulum.py

@@ -1,6 +1,6 @@
+import matplotlib.pyplot as plt
 import numpy as np
 import odespy
-import scitools.std as plt
 
 
 def simulate(

doc/.src/chapters/vib/exer-vib/elastic_pendulum_drag.py

@@ -1,6 +1,6 @@
+import matplotlib.pyplot as plt
 import numpy as np
 import odespy
-import scitools.std as plt
 
 
 def simulate_drag(

doc/.src/chapters/vib/exer-vib/sliding_box.py

@@ -1,6 +1,5 @@
 import matplotlib.pyplot as plt
 import numpy as np
-import scitools.std as plt
 
 
 def plot_spring():
@@ -10,7 +9,6 @@ def plot_spring():
     for alpha in alpha_values:
         print(alpha, s(u))
         plt.plot(u, s(u))
-        plt.hold("on")
     plt.legend([rf"$\alpha={alpha:g}$" for alpha in alpha_values])
     plt.xlabel("u")
     plt.ylabel("Spring response $s(u)$")
@@ -51,7 +49,6 @@ def f(u, t, beta, gamma):
         for beta in beta_values:
             u, t = simulate(beta, gamma, 0, 6, 60)
             plt.plot(t, u)
-            plt.hold("on")
         plt.legend([rf"$\beta={beta:g}$" for beta in beta_values])
         plt.title(rf"$\gamma={gamma:g}$")
         plt.xlabel("$t$")
@@ -60,4 +57,4 @@ def f(u, t, beta, gamma):
         plt.savefig(filestem + ".png")
         plt.savefig(filestem + ".pdf")
     plt.show()
-    raw_input()
+    input()

doc/.src/chapters/vib/exer-vib/test_vib_undamped_exact_discrete_sol.py

@@ -30,19 +30,13 @@ def u_numerical_exact(t):
     u_e = u_numerical_exact(t)
     error = abs(u_e - u).max()
     # Make a plot in a file, but not on the screen
-    from scitools.std import plot
-
-    plot(
-        t,
-        u,
-        "bo",
-        t,
-        u_e,
-        "r-",
-        legend=("numerical", "exact"),
-        show=False,
-        savefig="tmp.png",
-    )
+    import matplotlib.pyplot as plt
+
+    plt.plot(t, u, "bo", label="numerical")
+    plt.plot(t, u_e, "r-", label="exact")
+    plt.legend()
+    plt.savefig("tmp.png")
+    plt.close()
 
     assert error < 1e-14
 

doc/.src/chapters/vib/exer-vib/vib_EulerCromer.py

@@ -85,7 +85,7 @@ def demo():
     w = 0.5
     P = 2 * pi / w
     T = 4 * P
-    import scitools.std as plt
+    import matplotlib.pyplot as plt
 
     from vib import solver as solver2
 
@@ -96,7 +96,7 @@ def demo():
         plt.plot(t, u, "r-", t2, u2, "b-")
         plt.legend(["Euler-Cromer", "centered scheme"])
         plt.title(f"dt={dt:.3g}")
-        raw_input()
+        input()
         plt.savefig("tmp_%d" % k + ".png")
         plt.savefig("tmp_%d" % k + ".pdf")
         dt /= 2