Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/pywt/tests/test_perfect_reconstruction.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python
+
+"""
+Verify DWT perfect reconstruction.
+"""
+
+from __future__ import division, print_function, absolute_import
+
+import numpy as np
+from numpy.testing import assert_
+
+import pywt
+
+
+def test_perfect_reconstruction():
+    families = ('db', 'sym', 'coif', 'bior', 'rbio')
+    wavelets = sum([pywt.wavelist(name) for name in families], [])
+    # list of mode names in pywt and matlab
+    modes = [('zero', 'zpd'),
+             ('constant', 'sp0'),
+             ('symmetric', 'sym'),
+             ('periodic', 'ppd'),
+             ('smooth', 'sp1'),
+             ('periodization', 'per')]
+
+    dtypes = (np.float32, np.float64)
+
+    for wavelet in wavelets:
+        for pmode, mmode in modes:
+            for dt in dtypes:
+                check_reconstruction(pmode, mmode, wavelet, dt)
+
+
+def check_reconstruction(pmode, mmode, wavelet, dtype):
+    data_size = list(range(2, 40)) + [100, 200, 500, 1000, 2000, 10000,
+                                      50000, 100000]
+    np.random.seed(12345)
+    # TODO: smoke testing - more failures for different seeds
+
+    if dtype == np.float32:
+        # was 3e-7 has to be lowered as db21, db29, db33, db35, coif14, coif16 were failing
+        epsilon = 6e-7
+    else:
+        epsilon = 5e-11
+
+    for N in data_size:
+        data = np.asarray(np.random.random(N), dtype)
+
+        # compute dwt coefficients
+        pa, pd = pywt.dwt(data, wavelet, pmode)
+
+        # compute reconstruction
+        rec = pywt.idwt(pa, pd, wavelet, pmode)
+
+        if len(data) % 2:
+            rec = rec[:len(data)]
+
+        rms_rec = np.sqrt(np.mean((data-rec)**2))
+        msg = ('[RMS_REC > EPSILON] for Mode: %s, Wavelet: %s, '
+               'Length: %d, rms=%.3g' % (pmode, wavelet, len(data), rms_rec))
+        assert_(rms_rec < epsilon, msg=msg)