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Switch from deprecated scipy.misc.factorial #2

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Switch from deprecated scipy.misc.factorial #2

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307bf3c
Switch from deprecated scipy.misc.factorial
ar4 Sep 28, 2019
43c708d
Change CWT to be Tensor to Tensor
ar4 Sep 28, 2019
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40 changes: 20 additions & 20 deletions wavelets_pytorch/transform.py
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Original file line number Diff line number Diff line change
Expand Up @@ -299,29 +299,29 @@ def cwt(self, x):
self.signal_length = signal_length

# Move to GPU and perform CWT computation
x = torch.from_numpy(x).type(torch.FloatTensor)
x.requires_grad_(requires_grad=False)
#x = torch.from_numpy(x).type(torch.FloatTensor)
#x.requires_grad_(requires_grad=False)

if self._cuda: x = x.cuda()
cwt = self._extractor(x)

# Move back to CPU
cwt = cwt.detach()
if self._cuda: cwt = cwt.cpu()
cwt = cwt.numpy()

if self.complex_wavelet:
# Combine real and imag parts, returns object of shape
# [n_batch,n_scales,signal_length] of type np.complex128
cwt = (cwt[:,:,0,:] + cwt[:,:,1,:]*1j).astype(self.output_dtype)
else:
# Just squeeze the chn_out dimension (=1) to obtain an object of shape
# [n_batch,n_scales,signal_length] of type np.float64
cwt = np.squeeze(cwt, 2).astype(self.output_dtype)

# Squeeze batch dimension if single example
if num_examples == 1:
cwt = cwt.squeeze(0)
## Move back to CPU
#cwt = cwt.detach()
#if self._cuda: cwt = cwt.cpu()
#cwt = cwt.numpy()

#if self.complex_wavelet:
# # Combine real and imag parts, returns object of shape
# # [n_batch,n_scales,signal_length] of type np.complex128
# cwt = (cwt[:,:,0,:] + cwt[:,:,1,:]*1j).astype(self.output_dtype)
#else:
# # Just squeeze the chn_out dimension (=1) to obtain an object of shape
# # [n_batch,n_scales,signal_length] of type np.float64
# cwt = np.squeeze(cwt, 2).astype(self.output_dtype)

## Squeeze batch dimension if single example
#if num_examples == 1:
# cwt = cwt.squeeze(0)
return cwt

@property
Expand All @@ -340,4 +340,4 @@ def signal_length(self):
@signal_length.setter
def signal_length(self, value):
super(WaveletTransformTorch, self.__class__).signal_length.fset(self, value)
self._extractor.set_filters(self._filters)
self._extractor.set_filters(self._filters)
4 changes: 2 additions & 2 deletions wavelets_pytorch/wavelets.py
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Expand Up @@ -21,7 +21,7 @@
import scipy.signal
import scipy.optimize
import scipy.special
from scipy.misc import factorial
from scipy.special import factorial

__all__ = ['Morlet', 'Paul', 'DOG', 'Ricker', 'Marr', 'Mexican_hat']

Expand Down Expand Up @@ -380,4 +380,4 @@ def __init__(self):

# aliases for DOG2
Marr = Ricker
Mexican_hat = Ricker
Mexican_hat = Ricker