def _init_freq_one_hot_coded_seqs(self):
"""Perform a fft on the array of coded sequences.
Currently disabled because the optimization isnt being used.
"""
return None
if self.seq_len > self.max_fft_seq_len:
return None
fshape = (
next_good_fshape(len(self)),
next_good_fshape(self.seq_len+self.max_bs_len-1),
self.one_hot_coded_seqs.shape[2]
)
return rfftn(self.one_hot_coded_seqs, fshape)
def _clever_score_binding_sites(self, model, reverse_comp):
"""Score binding sites by a cached fft convolve.
Only works when the sequence length is less than 10kb
and the binsing site length is less than
self.max_bs_len (200 bp).
This has been disabled because it doesn't appear to work
in a multi-threaded environment and the speedup is minimal
over the naive implmentation.
"""
assert isinstance(model, ConvolutionalDNABindingModel)
n_channels = model.shape[1]
assert n_channels == self.one_hot_coded_seqs.shape[2]
assert model.binding_site_len < self.max_bs_len
convolutional_filter = model.convolutional_filter
if reverse_comp:
convolutional_filter = np.flipud(np.fliplr(convolutional_filter))
h_freq = rfftn(
model.convolutional_filter,
(self.freq_one_hot_coded_seqs.shape[1], n_channels))
conv_freq = self.freq_one_hot_coded_seqs*h_freq[None,:,:]
return irfftn(conv_freq)[:len(self), :self.seq_len, n_channels-1]
