Note

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2D ndsplines vs. scipy.interpolateΒΆ

make_interp_spline, spline.__call__
  7 import numpy as np
  8 import time
  9
 10 from scipy import interpolate
 11 import ndsplines
 12
 13 import matplotlib.pyplot as plt
 14
 15 # number of time measurements per input/query size
 16 n_iter = 10
 17
 18
 19 def timeit(func, n_iter=1, return_samps=True, **func_kwargs):
 20     results = np.empty(n_iter, dtype=np.double)
 21     for i in range(n_iter):
 22         # gc.collect()
 23
 24         tstart = time.time()
 25         func(**func_kwargs)
 26         delta = time.time() - tstart
 27
 28         results[i] = delta
 29
 30     if return_samps:
 31         return results
 32     else:
 33         return np.mean(results)
 34
 35
 36 def gen_xyz(sizex, sizey):
 37     x = np.pi * np.linspace(-1, 1, sizex)
 38     y = np.pi * np.linspace(-1, 1, sizey)
 39     xx, yy = np.meshgrid(x, y, indexing="ij")
 40
 41     zz = np.sin(xx) * np.cos(yy)
 42     return x, y, zz
 43
 44
 45 def gen_xxyy(sizex, sizey):
 46     x = np.pi * np.linspace(-1, 1, sizex)
 47     y = np.pi * np.linspace(-1, 1, sizey)
 48     xx, yy = np.meshgrid(x, y, indexing="ij")
 49     return xx, yy
 50
 51
 52 # make_interp_spline timing
 53 x_sizes = np.logspace(1, 3, 10, dtype=int)
 54 t_scipy_build = np.empty((2, x_sizes.size))
 55 t_ndspl_build = np.empty((2, x_sizes.size))
 56 for i, size in enumerate(x_sizes):
 57     x, y, z = gen_xyz(size, size)
 58     t_scipy = 10e3 * timeit(
 59         interpolate.RectBivariateSpline,
 60         x=x.copy(),
 61         y=y.copy(),
 62         z=z.copy(),
 63         n_iter=n_iter,
 64     )
 65     t_ndspl = 10e3 * timeit(ndsplines.make_interp_spline, x=[x, y], y=z, n_iter=n_iter)
 66     t_scipy_build[:, i] = np.mean(t_scipy), np.std(t_scipy)
 67     t_ndspl_build[:, i] = np.mean(t_ndspl), np.std(t_ndspl)
 68
 69 # spline query timing
 70 x, y, z = gen_xyz(7, 5)
 71 xx_sizes = np.logspace(0, 2, 10, dtype=int)
 72 t_scipy_call = np.empty((2, xx_sizes.size))
 73 t_ndspl_pyx_call = np.empty((2, xx_sizes.size))
 74 for i, size in enumerate(xx_sizes):
 75     xx, yy = gen_xxyy(size, size)
 76     xxyy = np.stack((xx, yy), axis=-1)
 77     spl_scipy = interpolate.RectBivariateSpline(x.copy(), y.copy(), z)
 78     spl_ndspl = ndsplines.make_interp_spline((x, y), z)
 79     spl_ndspl.allocate_workspace_arrays(size)
 80     t_scipy = 10e3 * timeit(
 81         spl_scipy, x=xx.copy(), y=yy.copy(), grid=False, n_iter=n_iter
 82     )
 83     t_ndspl_pyx = 10e3 * timeit(spl_ndspl, x=xxyy, n_iter=n_iter)
 84
 85 # plot results
 86 fig, axes = plt.subplots(nrows=2)
 87
 88 axes[0].errorbar(
 89     x_sizes, t_scipy_build[0], capsize=3, yerr=t_scipy_build[1], label="scipy"
 90 )
 91 axes[0].errorbar(
 92     x_sizes, t_ndspl_build[0], capsize=3, yerr=t_ndspl_build[1], label="ndsplines"
 93 )
 94 axes[0].set_title("make_interp_spline")
 95
 96 axes[1].errorbar(
 97     xx_sizes,
 98     t_scipy_call[0],
 99     capsize=3,
100     yerr=t_scipy_call[1],
101     label="scipy.interpolate",
102 )
103 axes[1].errorbar(
104     xx_sizes,
105     t_ndspl_pyx_call[0],
106     capsize=3,
107     yerr=t_ndspl_pyx_call[1],
108     label="ndsplines pyx",
109 )
110 axes[1].set_title("spline.__call__")
111
112 for ax in axes:
113     ax.set_xlabel("input array size")
114     ax.set_ylabel("time [ms]")
115     ax.set_xscale("log")
116     ax.grid()
117
118 axes[-1].legend()
119 fig.tight_layout()
120
121 plt.show()

Total running time of the script: (0 minutes 3.932 seconds)

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