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buffer input frames #6

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buffer input frames #6

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494c390
buffer input frames
hcab14 Dec 6, 2020
7d6ad5a
make test_match process samples in batches
hcab14 Dec 8, 2020
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23 changes: 19 additions & 4 deletions samplerate/converters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -109,6 +109,10 @@ def __init__(self, converter_type='sinc_fastest', channels=1):
self._state = ffi.gc(state, src_delete)
self._converter_type = converter_type
self._channels = channels
if channels == 1:
self._frame_buffer = np.zeros(0, dtype=np.float32)
else:
self._frame_buffer = np.zeros((0,channels), dtype=np.float32)
if error != 0:
raise ResamplingError(error)

Expand All @@ -125,6 +129,10 @@ def channels(self):
def reset(self):
"""Reset internal state."""
from samplerate.lowlevel import src_reset
if self._channels == 1:
self._frame_buffer = np.empty(0, dtype=np.float32)
else:
self._frame_buffer = np.empty((0,channels), dtype=np.float32)
return src_reset(self._state)

def set_ratio(self, new_ratio):
Expand Down Expand Up @@ -158,11 +166,12 @@ def process(self, input_data, ratio, end_of_input=False, verbose=False):
from samplerate.exceptions import ResamplingError

input_data = np.require(input_data, requirements='C', dtype=np.float32)
self._frame_buffer = np.append(self._frame_buffer, input_data, axis=0)
if input_data.ndim == 2:
num_frames, channels = input_data.shape
num_frames, channels = self._frame_buffer.shape
output_shape = (int(num_frames * ratio), channels)
elif input_data.ndim == 1:
num_frames, channels = input_data.size, 1
num_frames, channels = self._frame_buffer.shape[0], 1
output_shape = (int(num_frames * ratio), )
else:
raise ValueError('rank > 2 not supported')
Expand All @@ -173,16 +182,22 @@ def process(self, input_data, ratio, end_of_input=False, verbose=False):
output_data = np.empty(output_shape, dtype=np.float32)

(error, input_frames_used, output_frames_gen) = src_process(
self._state, input_data, output_data, ratio, end_of_input)
self._state, self._frame_buffer, output_data, ratio, end_of_input)

if error != 0:
raise ResamplingError(error)

if channels > 1:
self._frame_buffer = self._frame_buffer[input_frames_used:, :]
else:
self._frame_buffer = self._frame_buffer[input_frames_used:]

if verbose:
info = ('samplerate info:\n'
'{} input frames used\n'
'{} output frames generated\n'
.format(input_frames_used, output_frames_gen))
'{} buffer size\n'
.format(input_frames_used, output_frames_gen, self._frame_buffer.shape[0]))
print(info)

return (output_data[:output_frames_gen, :]
Expand Down
18 changes: 15 additions & 3 deletions tests/test_samplerate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,12 +32,24 @@ def test_process(data, converter_type, ratio=2.0):
src.process(input_data, ratio)


def test_match(data, converter_type, ratio=2.0):
def test_match(data, converter_type, ratio=2.123):
num_channels, input_data = data
output_simple = samplerate.resample(input_data, ratio, converter_type)
resampler = samplerate.Resampler(converter_type, channels=num_channels)
output_full = resampler.process(input_data, ratio, end_of_input=True)
assert np.allclose(output_simple, output_full)
if num_channels == 2:
output_full = np.empty((0,num_channels), dtype=np.float32)
for i in range(10):
output_full = np.append(output_full, resampler.process(input_data[100*i:100*(i+1),:], ratio), axis=0)
m = output_simple.shape[0]
output_simple = np.resize(output_simple, output_full.shape)
assert np.allclose(output_simple, output_full) and output_full.shape[0] > 0.8*m
else:
output_full = np.empty(0, dtype=np.float32)
for i in range(10):
output_full = np.append(output_full, resampler.process(input_data[100*i:100*(i+1)], ratio))
m = len(output_simple)
output_simple = np.resize(output_simple, output_full.shape)
assert np.allclose(output_simple, output_full) and len(output_full) > 0.8*m


def test_callback(data, converter_type, ratio=2.0):
Expand Down