Add benchmark script for gridder

nifty5/library/bench_gridder.py

+from time import time
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import nifty5 as ift
+
+ift.fft.enable_fftw()
+np.random.seed(40)
+
+N0s, a0s, b0s, c0s = [], [], [], []
+N1s, a1s, b1s, c1s = [], [], [], []
+
+for ii in range(1, 8):
+    nu = 1024
+    nv = 1024
+    N = int(10**ii)
+    print('N = {}'.format(N))
+
+    uv = np.random.rand(N, 2) - 0.5
+    vis = np.random.randn(N) + 1j*np.random.randn(N)
+
+    uvspace = ift.RGSpace((nu, nv))
+
+    visspace = ift.UnstructuredDomain(N)
+
+    img = np.random.randn(nu*nv) + 1j*np.random.randn(nu*nv)
+    img = img.reshape((nu, nv))
+    img = ift.from_global_data(uvspace, img)
+
+    t0 = time()
+    GM = ift.GridderMaker(uvspace, eps=1e-7)
+    idx = GM.getReordering(uv)
+    uv = uv[idx]
+    vis = vis[idx]
+    vis = ift.from_global_data(visspace, vis)
+    op = GM.getFull(uv).adjoint
+    t1 = time()
+    op(img).to_global_data()
+    t2 = time()
+    op.adjoint(vis).to_global_data()
+    t3 = time()
+    N0s.append(N)
+    a0s.append(t1 - t0)
+    b0s.append(t2 - t1)
+    c0s.append(t3 - t2)
+
+    t0 = time()
+    op = ift.NFFT(uvspace, uv)
+    t1 = time()
+    op(img).to_global_data()
+    t2 = time()
+    op.adjoint(vis).to_global_data()
+    t3 = time()
+    N1s.append(N)
+    a1s.append(t1 - t0)
+    b1s.append(t2 - t1)
+    c1s.append(t3 - t2)
+
+print('Measure rest operator')
+sc = ift.StatCalculator()
+op = GM.getRest().adjoint
+for _ in range(10):
+    t0 = time()
+    res = op(img)
+    sc.add(time() - t0)
+t_fft = sc.mean
+print('FFT shape', res.shape)
+
+plt.scatter(N0s, a0s, label='Gridder mr')
+plt.scatter(N1s, a1s, marker='^', label='NFFT')
+plt.legend()
+plt.ylabel('time [s]')
+plt.title('Initialization')
+plt.loglog()
+plt.savefig('bench0.png')
+plt.close()
+
+plt.scatter(N0s, b0s, color='k', marker='^', label='Gridder mr times')
+plt.scatter(N1s, b1s, color='r', marker='^', label='NFFT times')
+plt.scatter(N0s, c0s, color='k', label='Gridder mr adjoint times')
+plt.scatter(N1s, c1s, color='r', label='NFFT adjoint times')
+plt.axhline(sc.mean, label='FFT')
+plt.axhline(sc.mean + np.sqrt(sc.var))
+plt.axhline(sc.mean - np.sqrt(sc.var))
+plt.legend()
+plt.ylabel('time [s]')
+plt.title('Apply')
+plt.loglog()
+plt.savefig('bench1.png')
+plt.close()