def convert_file(filename, output_filename=None):
"""
Convert a file to the pypore .h5 file format. Returns the new file's name.
"""
reader = get_reader_from_filename(filename)
sample_rate = reader.get_sample_rate()
n_points = reader.get_points_per_channel_total()
if output_filename is None:
output_filename = filename.split('.')[0] + '.h5'
save_file = data_file.open_file(output_filename, mode='w', sample_rate=sample_rate, n_points=n_points)
blocks_to_get = 1
data = reader.get_next_blocks(blocks_to_get)[0]
n = data.size
i = 0
while n > 0:
save_file.root.data[i:n + i] = data[:]
i += n
data = reader.get_next_blocks(blocks_to_get)[0]
n = data.size
reader.close()
save_file.flush()
save_file.close()
return output_filename
def filter_file(filename, filter_frequency, out_sample_rate, output_filename=None):
"""
Reads data from the filename file and uses a Butterworth low-pass filter with cutoff at filter_frequency. Outputs
the filtered waveform to a new :py:class:`pypore.filetypes.data_file.DataFile`.
:param StringType filename: Filename containing data to be filtered.
:param DoubleType filter_frequency: Cutoff frequency for the low-pass Butterworth filter.
:param DoubleType out_sample_rate: After the data is filtered, it can be resampled to roughly out_sample_rate. If \
out_sample_rate <= 0, the data will not be resampled.
:param StringType output_filename: (Optional) Filename for the filtered data. If not specified,
for an example filename='test.mat', the default output_filename would be 'test_filtered.h5'
:returns: StringType -- The output filename of the filtered data.
Usage:
>>> import pypore.file_converter as fC
>>> fC.filter_file("filename", 1.e4, 1.e5, "output.h5") // filter at 10kHz, resample at 100kHz
"""
reader = get_reader_from_filename(filename)
data = reader.get_all_data()[0]
sample_rate = reader.get_sample_rate()
final_sample_rate = sample_rate
n_points = len(data)
if output_filename is None:
output_filename = filename.split('.')[0] + '_filtered.h5'
# wn is a fraction of the Nyquist frequency (half the sampling frequency).
wn = filter_frequency / (0.5 * sample_rate)
b, a = sig.butter(6, wn)
filtered = sig.filtfilt(b, a, data)[:]
# resample the data, if requested.
if 0 < out_sample_rate < sample_rate:
n_out = int(np.ceil(n_points * out_sample_rate / sample_rate))
filtered = sig.resample(filtered, num=n_out)
final_sample_rate = sample_rate * (1.0*n_out/n_points)
save_file = data_file.open_file(output_filename, mode='w', sample_rate=final_sample_rate, n_points=filtered.size)
save_file.root.data[:] = filtered[:]
save_file.flush()
save_file.close()
return output_filename
