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Fixed #34 Customizing scipy's oaconvolve #35
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72f0fb2
modified oaconvolve
NimaSarajpoor be0035e
update code logic
NimaSarajpoor 907e2e2
minor clean ups
NimaSarajpoor 969f187
major changes to imporve readability
NimaSarajpoor b366e35
Add param blocksize
NimaSarajpoor a3d2e44
add temp test for challenger
NimaSarajpoor 22d233b
add func for computing block size
NimaSarajpoor d6eedfa
remove redundant code
NimaSarajpoor 4e23694
added clearer functions
NimaSarajpoor 01a0e7a
minor change
NimaSarajpoor dddb708
minor change to help with future refactoring
NimaSarajpoor 41db845
minor change
NimaSarajpoor 99e450b
Added reference for finding optimal block size
NimaSarajpoor e8fa331
fixed test
NimaSarajpoor f45f541
revise comment
NimaSarajpoor 39e936c
removed overlap-add explanation. Created PR#36 instead
NimaSarajpoor f6fed15
renaming private functions to reflect valid convolution
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,14 +1,85 @@ | ||
| import math | ||
| import numpy as np | ||
| from scipy.special import lambertw | ||
| from scipy.fft import next_fast_len | ||
| from scipy.fft._pocketfft.basic import r2c, c2r | ||
| from . import pocketfft_r2c_c2r_sdp | ||
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| def setup(Q, T): | ||
| return | ||
| def _compute_block_size(m, n, conv_block_size=None): | ||
| """ | ||
| Return a block size for the overlap-add method. | ||
| """ | ||
| if conv_block_size is None: | ||
| # Find optimal block_size based on m and n | ||
| if m >= n / 2: | ||
| conv_block_size = n # i.e. no blocking | ||
| else: | ||
| # To minimize Eq. 3 in | ||
| # https://en.wikipedia.org/wiki/Overlap–add_method | ||
| overlap = m - 1 | ||
| opt_size = -overlap * lambertw(-1 / (2 * math.e * overlap), k=-1).real | ||
| conv_block_size = next_fast_len(math.ceil(opt_size), real=True) | ||
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| conv_block_size = max(conv_block_size, m) | ||
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| return min(conv_block_size, n) | ||
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| def _pocketfft_oaconvolve_block(Q, T, conv_block_size): | ||
| m = Q.shape[0] | ||
| n = T.shape[0] | ||
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| T_chunk_size = conv_block_size - (m - 1) | ||
| n_chunks = math.ceil(n / T_chunk_size) | ||
| last_chunk_start = (n_chunks - 1) * T_chunk_size | ||
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| tmp = np.empty((n_chunks + 1, conv_block_size), dtype=np.float64) | ||
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| # fill with T, block-wise | ||
| tmp[: n_chunks - 1, :T_chunk_size] = T[:last_chunk_start].reshape( | ||
| n_chunks - 1, T_chunk_size | ||
| ) | ||
| tmp[: n_chunks - 1, T_chunk_size:] = 0.0 | ||
| tmp[n_chunks - 1, : n - last_chunk_start] = T[last_chunk_start:] | ||
| tmp[n_chunks - 1, n - last_chunk_start :] = 0.0 | ||
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| # fill with Q | ||
| tmp[n_chunks, :m] = Q | ||
| tmp[n_chunks, m:] = 0.0 | ||
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| fft_2d = r2c(True, tmp, axis=-1) | ||
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| return c2r(False, np.multiply(fft_2d[:-1], fft_2d[[-1]]), n=conv_block_size) | ||
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| def sliding_dot_product(Q, T): | ||
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| def _pocketfft_valid_oaconvolve(Q, T, conv_block_size): | ||
| QT_conv_blocks = _pocketfft_oaconvolve_block(Q, T, conv_block_size) | ||
| overlap = len(Q) - 1 | ||
| out = QT_conv_blocks[:, :-overlap] | ||
| out[1:, :overlap] += QT_conv_blocks[:-1, -overlap:] | ||
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| return np.reshape(out, (-1,))[len(Q) - 1 : len(T)] | ||
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| def _valid_convolve(Q, T, conv_block_size=None): | ||
| m = len(Q) | ||
| l = T.shape[0] - m + 1 | ||
| out = np.empty(l) | ||
| for i in range(l): | ||
| out[i] = np.dot(Q, T[i : i + m]) | ||
| n = len(T) | ||
| conv_block_size = _compute_block_size(m, n, conv_block_size=conv_block_size) | ||
| if conv_block_size >= n: | ||
| out = pocketfft_r2c_c2r_sdp._pocketfft_valid_convolve(Q, T) | ||
| else: | ||
| out = _pocketfft_valid_oaconvolve(Q, T, conv_block_size) | ||
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| return out | ||
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| def setup(Q, T): | ||
| return | ||
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| def sliding_dot_product(Q, T, conv_block_size=None): | ||
| if len(Q) == len(T): | ||
| return np.dot(Q, T) | ||
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|
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| else: | ||
| return _valid_convolve(Q[::-1], T, conv_block_size=conv_block_size) | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
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@@ -210,3 +210,18 @@ def test_pyfftw_sdp_max_n(): | |
| np.testing.assert_allclose(comp, ref) | ||
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| return | ||
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| def test_oaconvolve_sdp_blocksize(): | ||
| from sdp.challenger_sdp import sliding_dot_product | ||
|
Collaborator
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This line needs to be modified if, at a later time, we decide to move the proposal to a new file (module). |
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| T = np.random.rand(2**10) | ||
| Q = np.random.rand(2**8) | ||
| conv_block_size = 2**9 | ||
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| comp = sliding_dot_product(Q, T, conv_block_size=conv_block_size) | ||
| ref = naive_sliding_dot_product(Q, T) | ||
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| np.testing.assert_allclose(comp, ref) | ||
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| return | ||
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