apply formatting

Author: gardner48

benchmarks/advection_reaction_3D/scripts/compare_error.py

@@ -15,7 +15,8 @@
 import glob
 import sys
 import matplotlib
-matplotlib.use('Agg')
+
+matplotlib.use("Agg")
 from mpl_toolkits.mplot3d import Axes3D
 import matplotlib.pyplot as plt
 import pandas as pd
@@ -25,75 +26,75 @@
 # load pickled data
 def load_data(file):
     data = np.load(file)
-    m = data['mesh']
-    t = data['t']
-    u = data['u']
-    v = data['v']
-    w = data['w']
+    m = data["mesh"]
+    t = data["t"]
+    u = data["u"]
+    v = data["v"]
+    w = data["w"]
 
-    hx = m[0,1] - m[0,0]
-    hy = m[1,1] - m[1,0]
-    hz = m[2,1] - m[2,0]
+    hx = m[0, 1] - m[0, 0]
+    hy = m[1, 1] - m[1, 0]
+    hz = m[2, 1] - m[2, 0]
 
-    return { 'm': m, 'h': (hx,hy,hz), 't': t, 'u': u, 'v': v, 'w': w }
+    return {"m": m, "h": (hx, hy, hz), "t": t, "u": u, "v": v, "w": w}
 
 
 # grid function norm
 def norm_3Dgrid(h, x, q=1):
-    hx,hy,hz = h
+    hx, hy, hz = h
     s = np.shape(x)
-    return (hx*hy*hz*np.sum(np.abs(x)**q, axis=(1,2,3)))**(1./q)
+    return (hx * hy * hz * np.sum(np.abs(x) ** q, axis=(1, 2, 3))) ** (1.0 / q)
 
 
 # load data files
-np111 = load_data('np-111/output-with-h-8.33e-02.npz')
-np211 = load_data('np-211/output-with-h-8.33e-02.npz')
-np311 = load_data('np-311/output-with-h-8.33e-02.npz')
-np131 = load_data('np-131/output-with-h-8.33e-02.npz')
-np113 = load_data('np-113/output-with-h-8.33e-02.npz')
-np911 = load_data('np-911/output-with-h-8.33e-02.npz')
+np111 = load_data("np-111/output-with-h-8.33e-02.npz")
+np211 = load_data("np-211/output-with-h-8.33e-02.npz")
+np311 = load_data("np-311/output-with-h-8.33e-02.npz")
+np131 = load_data("np-131/output-with-h-8.33e-02.npz")
+np113 = load_data("np-113/output-with-h-8.33e-02.npz")
+np911 = load_data("np-911/output-with-h-8.33e-02.npz")
 # np133 = load_data('np-133/output-with-h-8.33e-02.npz')
-np313 = load_data('np-313/output-with-h-8.33e-02.npz')
-np331 = load_data('np-331/output-with-h-8.33e-02.npz')
-np333 = load_data('np-333/output-with-h-8.33e-02.npz')
+np313 = load_data("np-313/output-with-h-8.33e-02.npz")
+np331 = load_data("np-331/output-with-h-8.33e-02.npz")
+np333 = load_data("np-333/output-with-h-8.33e-02.npz")
 # np666 = load_data('np-666/output-with-h-8.33e-02.npz')
 
-for component in ['u', 'v', 'w']:
+for component in ["u", "v", "w"]:
     # Reference solution
     ref = np111[component]
 
     # Now compute E(h) = ||U(h) - \bar{U}(h)|| using the grid-function norm
-    E_np211 = norm_3Dgrid(np211['h'], np211[component] - ref)
-    E_np311 = norm_3Dgrid(np311['h'], np311[component] - ref)
-    E_np131 = norm_3Dgrid(np131['h'], np131[component] - ref)
-    E_np113 = norm_3Dgrid(np113['h'], np113[component] - ref)
-    E_np911 = norm_3Dgrid(np911['h'], np911[component] - ref)
+    E_np211 = norm_3Dgrid(np211["h"], np211[component] - ref)
+    E_np311 = norm_3Dgrid(np311["h"], np311[component] - ref)
+    E_np131 = norm_3Dgrid(np131["h"], np131[component] - ref)
+    E_np113 = norm_3Dgrid(np113["h"], np113[component] - ref)
+    E_np911 = norm_3Dgrid(np911["h"], np911[component] - ref)
     # E_np133 = norm_3Dgrid(np133['h'], np133[component] - ref)
-    E_np313 = norm_3Dgrid(np313['h'], np313[component] - ref)
-    E_np331 = norm_3Dgrid(np331['h'], np331[component] - ref)
-    E_np333 = norm_3Dgrid(np333['h'], np333[component] - ref)
+    E_np313 = norm_3Dgrid(np313["h"], np313[component] - ref)
+    E_np331 = norm_3Dgrid(np331["h"], np331[component] - ref)
+    E_np333 = norm_3Dgrid(np333["h"], np333[component] - ref)
     # E_np666 = norm_3Dgrid(np666['h'], np666[component] - ref)
 
     # Plot error across time
-    X, Y = np.meshgrid(np111['m'][0,:], np111['t'])
+    X, Y = np.meshgrid(np111["m"][0, :], np111["t"])
     # fig = plt.figure()
     # ax = plt.subplot(311, projection='3d')
     # ax.plot_surface(X, Y, np.abs(np911[component][:,:,0,0] - ref[:,:,0,0]))
     # ax = plt.subplot(312, projection='3d')
     # ax.plot_surface(X, Y, np.abs(np911[component][:,0,:,0] - ref[:,0,:,0]))
     # ax = plt.subplot(313, projection='3d')
     # ax.plot_surface(X, Y, np.abs(np911[component][:,0,0,:] - ref[:,0,0,:]))
-    plt.plot(np111['t'], E_np211)
-    plt.plot(np111['t'], E_np131)
-    plt.plot(np111['t'], E_np113)
-    plt.plot(np111['t'], E_np911)
+    plt.plot(np111["t"], E_np211)
+    plt.plot(np111["t"], E_np131)
+    plt.plot(np111["t"], E_np113)
+    plt.plot(np111["t"], E_np911)
     # plt.plot(np111['t'], E_np133)
-    plt.plot(np111['t'], E_np313)
-    plt.plot(np111['t'], E_np331)
-    plt.plot(np111['t'], E_np333)
+    plt.plot(np111["t"], E_np313)
+    plt.plot(np111["t"], E_np331)
+    plt.plot(np111["t"], E_np333)
     # plt.plot(np111['t'], E_np666)
     # plt.legend(['2 1 1', '3 1 1', '1 3 3', '3 1 3', '3 3 1', '3 3 3', '6 6 6'])
     # plt.legend(['3 1 1', '1 3 1', '1 1 3', '9 1 1', '1 3 3', '3 1 3', '3 3 1'])
-    plt.ylabel('||E(hx,hy,hz)||')
-    plt.xlabel('time')
-    plt.savefig('compare-error-plot-%s.png' % component)
+    plt.ylabel("||E(hx,hy,hz)||")
+    plt.xlabel("time")
+    plt.savefig("compare-error-plot-%s.png" % component)

benchmarks/advection_reaction_3D/scripts/compute_error.py

@@ -15,7 +15,8 @@
 import glob
 import sys
 import matplotlib
-matplotlib.use('Agg')
+
+matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import pandas as pd
 import numpy as np
@@ -24,65 +25,67 @@
 # load pickled data
 def load_data(file):
     data = np.load(file)
-    m = data['mesh']
-    t = data['t']
-    u = data['u']
-    v = data['v']
-    w = data['w']
+    m = data["mesh"]
+    t = data["t"]
+    u = data["u"]
+    v = data["v"]
+    w = data["w"]
 
-    hx = m[0,1] - m[0,0]
-    hy = m[1,1] - m[1,0]
-    hz = m[2,1] - m[2,0]
+    hx = m[0, 1] - m[0, 0]
+    hy = m[1, 1] - m[1, 0]
+    hz = m[2, 1] - m[2, 0]
 
-    return { 'm': m, 'h': (hx,hy,hz), 't': t, 'u': u, 'v': v, 'w': w }
+    return {"m": m, "h": (hx, hy, hz), "t": t, "u": u, "v": v, "w": w}
 
 
 # grid function norm
 def norm_3Dgrid(h, x, q=1):
-    hx,hy,hz = h
-    return (hx*hy*hz*np.sum(np.abs(x)**q, axis=(1,2,3)))**(1/q)
+    hx, hy, hz = h
+    return (hx * hy * hz * np.sum(np.abs(x) ** q, axis=(1, 2, 3))) ** (1 / q)
 
 
 # computer order of accuracy p
 def calc_order(h1, Eh1, h2, Eh2):
-    return np.log( Eh1/Eh2 ) / np.log( np.prod(h1)/np.prod(h2) )
+    return np.log(Eh1 / Eh2) / np.log(np.prod(h1) / np.prod(h2))
 
 
 # load data files
-h_over_8 = load_data('middle-h/output-with-h-1.04e-02.npz')
-h_over_4 = load_data('large-h/output-with-h-2.08e-02.npz')
+h_over_8 = load_data("middle-h/output-with-h-1.04e-02.npz")
+h_over_4 = load_data("large-h/output-with-h-2.08e-02.npz")
 # h_over_2 = load_data('larger-h/output-with-h-4.16e-02.npz')
-h_over_1 = load_data('largest-h/output-with-h-8.33e-02.npz')
+h_over_1 = load_data("largest-h/output-with-h-8.33e-02.npz")
 
-for component in ['u', 'v', 'w']:
+for component in ["u", "v", "w"]:
     # Restrict reference to the coarsest grid
-    ref = h_over_8[component][:,::8,::8,::8]
+    ref = h_over_8[component][:, ::8, ::8, ::8]
 
     # Now compute E(h) = ||U(h) - \bar{U}(h)|| using the grid-function norm
-    Eh_over_4 = norm_3Dgrid(h_over_4['h'], h_over_4[component][:,::4,::4,::4] - ref)
-    Eh_over_1 = norm_3Dgrid(h_over_1['h'], h_over_1[component][:,:,:,:] - ref)
+    Eh_over_4 = norm_3Dgrid(h_over_4["h"], h_over_4[component][:, ::4, ::4, ::4] - ref)
+    Eh_over_1 = norm_3Dgrid(h_over_1["h"], h_over_1[component][:, :, :, :] - ref)
 
     # Compute order p as in O(h^p)
-    p = calc_order(h_over_1['h'], Eh_over_1, h_over_4['h'], Eh_over_4)
-    print('min p for %s component: %.4f' % (component, np.min(p)))
+    p = calc_order(h_over_1["h"], Eh_over_1, h_over_4["h"], Eh_over_4)
+    print("min p for %s component: %.4f" % (component, np.min(p)))
 
     # Plot error across time
     plt.figure()
-    plt.plot(h_over_8['t'], Eh_over_4, 'r-')
-    plt.plot(h_over_8['t'], Eh_over_1, 'b-')
-    plt.ylabel('||E(hx,hy,hz)||')
-    plt.xlabel('time')
-    plt.savefig('error-in-time-plot-%s.png' % component)
+    plt.plot(h_over_8["t"], Eh_over_4, "r-")
+    plt.plot(h_over_8["t"], Eh_over_1, "b-")
+    plt.ylabel("||E(hx,hy,hz)||")
+    plt.xlabel("time")
+    plt.savefig("error-in-time-plot-%s.png" % component)
 
     # Plot error norm with respect to h
     plt.figure()
-    x = np.array([np.prod(h_over_4['h']), np.prod(h_over_1['h'])])
-    plt.plot(x, x, 'k-')
-    plt.plot(x, x**2, 'k-')
-    plt.plot(x, [np.linalg.norm(Eh_over_4, np.Inf), np.linalg.norm(Eh_over_1, np.Inf)], 'r-')
-    plt.legend(['1st order', '2nd order', 'actual'])
-    plt.ylabel('|| ||E(hx,hy,hz)|| ||_inf')
-    plt.xlabel('hx * hy * hz')
-    plt.yscale('log')
-    plt.xscale('log')
-    plt.savefig('error-plot-%s.png' % component)
+    x = np.array([np.prod(h_over_4["h"]), np.prod(h_over_1["h"])])
+    plt.plot(x, x, "k-")
+    plt.plot(x, x**2, "k-")
+    plt.plot(
+        x, [np.linalg.norm(Eh_over_4, np.Inf), np.linalg.norm(Eh_over_1, np.Inf)], "r-"
+    )
+    plt.legend(["1st order", "2nd order", "actual"])
+    plt.ylabel("|| ||E(hx,hy,hz)|| ||_inf")
+    plt.xlabel("hx * hy * hz")
+    plt.yscale("log")
+    plt.xscale("log")
+    plt.savefig("error-plot-%s.png" % component)