def load(path, nchan, cutmin):
ndpoints = cutmin * 60 * 30000
dim = int(math.floor((ndpoints / 1024)))
raw = np.empty((dim * 1024, nchan))
for i in range(nchan):
i += 1
# dump=[]
data = op.loadContinuous(str(path) + '\\100_CH%s.continuous' % i,
stop_record=ndpoints / 1024)
print('loaded %s' % i, 'start cutting')
# cutting
timestamps = data['data'] #[0:cutmin*60*30000]
raw[:, i - 1] = (timestamps)
return raw
#del stim_array[0]
#st= np.array(stim_array)/25000.
##file_name = '/home/cat/neuron/in_vivo/dan/M149873/2015-02-06_13-02-32_flash_CSD/data/stim_times.txt'
#file_name = file_dir+'stim_times.txt'
#np.savetxt(file_name,st, fmt='%8.3f')
#quit()
#******************************* LOAD RAW DATA AND PREP FOR .TSF FILE ***************************
data=[]
for i in range(128):
file_name = file_dir + '100_CH'+ str(i+1) +'.continuous'
data.append(oe.loadContinuous(file_name)['data'])
dt = np.array(data, dtype=np.int16)
print dt.shape
####Plot first 10000 steps from channel 0
#x = np.arange(0,len(dt1),1.)/SampleFrequency
#plt.plot(x,dt1, 'r-', color='black',linewidth=1)
#plt.plot(x,dt2+1000, 'r-', color='black',linewidth=1)
#plt.plot(x,dt[probe128[0]][0:100000], 'r-', color='black',linewidth=1)
#plt.plot(x,dt[probe128[2]][0:100000]-100, 'r-', color='black',linewidth=1)
#plt.show()
pathname = f"./plx/{dirname}"
#Ephys形式で記録されたチャネルマップ配置
channel_map = [9, 8, 10, 7, 13, 4, 12, 5, 15, 2, 16, 1, 14, 3, 11, 6]
#刺激方法の設定をSetting.jsonのファイルから読み込む
#jsonファイルは日程-時間で記録されているため、result.jsonに記載された日程を参照する
with open(f"./json/{jsonfile[:14]}Settings.json",
encoding="UTF-8") as json_fp:
stim_setting = json.load(json_fp)
if not (os.path.exists(f"./waveform/{dirname}")):
os.mkdir(f"./waveform/{dirname}")
num = 1
for i in channel_map:
#OpenEphys.pyを使用してcontinuousファイルの読み込み
tmp = OpenEphys.loadContinuous(
f"./plx/{dirname}/101_CH{str(i)}.continuous")
#lowpassフィルタがかけられた波形を抽出
waveform = glia.nucleus.Waveform(lowpass(tmp["data"], 30000, 450, 600,
10, 30),
rate=glia.Frequency(30000))
#tmp(['header', 'timestamps', 'data', 'recordingNumber'])が記載されている
#timestampsはサンプリングレートで記録された記録点
timestamps = tmp["timestamps"][0]
if num < 10:
glia.save(f"./waveform/{dirname}/0{num}.lfp", waveform)
else:
glia.save(f"./waveform/{dirname}/{num}.lfp", waveform)
del tmp, waveform
gc.collect()
num += 1
#file_dir = 'M150566/2015-04-01_16-41-14_flashes_vis/'
#file_dir = 'M150566/2015-04-01_20-55-32_flashes_vis/'
#file_dir = 'M181420/181420_2015-04-07_13-25-07_flashes_vis/'
#file_dir = 'M181420/181420_2015-04-07_18-10-46_flash_vis/'
##********************** LOAD STIMULUS TIMES AND SAVE THEM *****************************
if False:
file_name = '103_PAI7.StimTimeshere.continuous'
data=[]
data = oe.loadContinuous(file_dir+mouse_dir+'/'+exp+dir+'/'+file_name)
dt = np.array(data['data'])
stim_array=[]
state=0
for i in range(len(dt)):
if state==0:
if dt[i]>1:
print "ON"
temp=i
state=1
if state==1:
if dt[i]<1:
print "OFF"
stim_array.append([temp,i])
state=0
DataFiles = glob.glob(''.join([RecFolder,'/*.continuous']))
DataFiles.sort()
#%% Generate TTLs
os.makedirs('DataArrays', exist_ok=True)
DirList = glob.glob('OpenEphysFiles/*'); DirList.sort()
for RecFolder in DirList:
DataFiles = glob.glob(''.join([RecFolder,'/*.continuous']))
EventsFile = ''.join([RecFolder,'/all_channels.events'])
DataFiles.sort()
TempData = OpenEphys.loadContinuous(DataFiles[0]) # Any ch would work ;)
Events = OpenEphys.loadEvents(EventsFile)
# Draw TTL
print('Drawing TTL channel...')
if len(Events['timestamps']) > 100: # arbitrary value, I never use < 100 stimulation pulses
TTLSound = [0] * len(TempData['data'])
for EvTS in range(len(Events['timestamps'])):
if Events['eventType'][EvTS] == 3: # if event is a TTL
if Events['eventId'][EvTS] == 1: # if TTL is on
TTLSound(find(TempTimestamps==EventsTimestamps(EvTS)): ...
find(TempTimestamps==EventsTimestamps(EvTS+1))) = 1;
end
end
end
else
#==============================================================================#
ntot = len(dfold_list)
ind = 0
for dfold in dfold_list:
ind = ind + 1
nrem = ntot - ind
print('Converting ' + dfold + ': ' + str(nrem) + ' remaining')
folderpath = ddir + dfold # folderpath where data is stored
#=============== SUBSAMPLE LOWPASS (LFP) SIGNAL AND CONVERT TO DAT ===========#
lfpname = '102_CH2.continuous'
filepath = ddir + dfold + '/' + lfpname
LFP = OpenEphys.loadContinuous(filepath, dtype=float)
LFP = LFP['data']
ssLFP = LFP[::10].copy() #subsampled LFP
# save as dat file
datnameLFP = dfold + '_LFP.dat'
ssLFP.tofile(os.path.join(folderpath, datnameLFP))
#==============================================================================#
#======================== CONVERT HIGHPASS SIGNALS TO DAT ======================#
# Load highpass signals of each sahnk in geometric order (bottom of shank to top)
# then save to flat binary file
# create shank1 and shank2 folders
os.makedirs(folderpath + '/2017/' + shank1_fname)
os.makedirs(folderpath + '/2017/' + shank2_fname)
duration = glia.milliseconds(400)
filename = i
jsonfile = rec_stim_matching[filename]
filename = "plx/" + filename
with open("json/" + jsonfile[:14] + "Settings.json",
encoding="utf-8") as json_fp:
stim_setting = json.load(json_fp)
if not reload and os.path.isfile("./waveform/" + filename[4:-4] +
".lfp") and os.path.isfile(
"./waveform/" + filename[4:-4] +
".trig"):
print("Load lfp, trig")
else:
wave = []
for j in channel_map:
tmp = OpenEphys.loadContinuous(filename + "/101_CH" + str(j) +
".continuous")
#gliaの形式にそってローパスフィルタをかけた波形の出力
wave.append(
glia.nucleus.Waveform(lowpass(tmp["data"], 30000, 450, 600, 10,
30),
rate=glia.Frequency(30000)))
timestamp = tmp["timestamps"][0]
events = OpenEphys.loadEvents(filename + "/all_channels.events")
e_tmp = (events["timestamps"] - timestamp)[0::2]
trigger = []
for i in (e_tmp / 30):
trigger.append(glia.millisecond(i))
trigger = np.array(trigger)
glia.save("./waveform/" + filename[4:] + ".lfp", wave)
glia.save("./waveform/" + filename[4:] + ".trig", trigger)
if not reload and os.path.isfile("./waveform/" + filename[4:-4] +
