本文整理汇总了Python中parameters.Parameters.items方法的典型用法代码示例。如果您正苦于以下问题：Python Parameters.items方法的具体用法？Python Parameters.items怎么用？Python Parameters.items使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类parameters.Parameters的用法示例。
在下文中一共展示了Parameters.items方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: spike_detection_from_raw_data
# 需要导入模块: from parameters import Parameters [as 别名]
# 或者: from parameters.Parameters import items [as 别名]
def spike_detection_from_raw_data(basename, DatFileNames, n_ch_dat, Channels_dat,
ChannelGraph, probe, max_spikes):
"""
Filter, detect, extract from raw data.
"""
### Detect spikes. For each detected spike, send it to spike writer, which
### writes it to a spk file. List of times is small (memorywise) so we just
### store the list and write it later.
np.savetxt("dat_channels.txt", Channels_dat, fmt="%i")
# Create HDF5 files
h5s = {}
h5s_filenames = {}
for n in ['main', 'waves']:
filename = basename+'.'+n+'.h5'
h5s[n] = tables.openFile(filename, 'w')
h5s_filenames[n] = filename
for n in ['raw', 'high', 'low']:
if Parameters['RECORD_'+n.upper()]:
filename = basename+'.'+n+'.h5'
h5s[n] = tables.openFile(filename, 'w')
h5s_filenames[n] = filename
main_h5 = h5s['main']
# Shanks groups
shanks_group = {}
shank_group = {}
shank_table = {}
for k in ['main', 'waves']:
h5 = h5s[k]
shanks_group[k] = h5.createGroup('/', 'shanks')
for i in probe.shanks_set:
shank_group[k, i] = h5.createGroup(shanks_group[k], 'shank_'+str(i))
# waveform data for wave file
for i in probe.shanks_set:
shank_table['waveforms', i] = h5s['waves'].createTable(
shank_group['waves', i], 'waveforms',
waveform_description(len(probe.channel_set[i])))
# spikedetekt data for main file, and links to waveforms
for i in probe.shanks_set:
shank_table['spikedetekt', i] = main_h5.createTable(shank_group['main', i],
'spikedetekt', shank_description(len(probe.channel_set[i])))
main_h5.createExternalLink(shank_group['main', i], 'waveforms',
shank_table['waveforms', i])
# Metadata
n_samples = np.array([num_samples(DatFileName, n_ch_dat) for DatFileName in DatFileNames])
for k, h5 in h5s.items():
metadata_group = h5.createGroup('/', 'metadata')
parameters_group = h5.createGroup(metadata_group, 'parameters')
for k, v in Parameters.items():
if not k.startswith('_'):
if isinstance(v, bool):
r = int(v)
elif isinstance(v, (int, float)):
r = v
else:
r = repr(v)
h5.setNodeAttr(parameters_group, k, r)
h5.setNodeAttr(metadata_group, 'probe', json.dumps(probe.probes))
h5.createArray(metadata_group, 'datfiles_offsets_samples',
np.hstack((0, np.cumsum(n_samples)))[:-1])
########## MAIN TIME CONSUMING LOOP OF PROGRAM ########################
for (USpk, Spk, PeakSample,FracPeakSample,
ChannelMask, FloatChannelMask) in extract_spikes(h5s, basename,
DatFileNames,
n_ch_dat,
Channels_dat,
ChannelGraph,
max_spikes,
):
# what shank are we in?
nzc, = ChannelMask.nonzero()
internzc = list(set(nzc).intersection(probe.channel_to_shank.keys()))
if internzc:
shank = probe.channel_to_shank[internzc[0]]
else:
continue
# write only the channels of this shank
channel_list = np.array(sorted(list(probe.channel_set[shank])))
t = shank_table['spikedetekt', shank]
t.row['time'] = PeakSample
t.row['float_time'] = FracPeakSample
t.row['mask_binary'] = ChannelMask[channel_list]
t.row['mask_float'] = FloatChannelMask[channel_list]
t.row.append()
# and the waveforms
t = shank_table['waveforms', shank]
t.row['wave'] = Spk[:, channel_list]
t.row['unfiltered_wave'] = USpk[:, channel_list]
t.row.append()
for h5 in h5s.values():
h5.flush()
# Feature extraction
for shank in probe.shanks_set:
X = shank_table['waveforms', shank].cols.wave[:Parameters['PCA_MAXWAVES']]
if len(X) == 0:
continue
#.........这里部分代码省略.........