def LoadAllWavesFromPxp(filepath):
"""
Given a file path to an igor pxp file, loads all waves associated with it
Args:
filepath: path to igor pxp file
Returns:
list of WaveObj (see ParseSingleWave), containing data and metadata
"""
# XXX use file system to filter?
records,_ = loadpxp(filepath)
mWaves = []
for i,record in enumerate(records):
# if this is a wave with a proper name, go for it
if isinstance(record, WaveRecord):
mWave =record.wave
# determine if the wave is something we care about
if (not ProcessSingleWave.ValidName(mWave)):
continue
# POST: have a valid name
try:
WaveObj = ProcessSingleWave.WaveObj(record=mWave,
SourceFile=filepath)
except ValueError as e:
# strange tuple error?
continue
mWaves.append(WaveObj)
return mWaves
import pandas
import numpy
import matplotlib.pyplot as plt
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
experiment = loadpxp("./2019.01.01.SdrGBullCantileverRampClamp_clean.pxp")
# experiment = loadpxp("./2019.01.01.SdrGBullCantileverRampClamp_delTraceClean.pxp")
# unpack the pxp
_, file_structure = experiment
count = 0
# get the folder we care about
folder_we_care_about = file_structure['root']['ForceClamp']['SavedData']
print(count)
while count < 2000:
print (count)
strCount = str(count)
Defl_wave = folder_we_care_about['DefV'+strCount].wave
Defl_labels = Defl_wave['wave']['labels']
import numpy
import re
import pandas
import numpy
import matplotlib.pyplot as plt
import os.path
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
experiment = loadpxp("./210202.FLSopE2_BestTraces_clean.pxp")
# experiment = loadpxp("./2019.01.01.SdrGBullCantileverRampClamp_delTraceClean.pxp")
# unpack the pxp
_, file_structure = experiment
# get the folder we care about
folder_we_care_about = file_structure['root']['MyForceData']['WLCFits']
dictkeys = []
dictkeys = folder_we_care_about.keys()
print(dictkeys)
print(len(dictkeys))
print(type(folder_we_care_about))
count = 0
combinedData = numpy.array([])
for i in dictkeys:
print(str(i))
import matplotlib.pyplot as plt
import os.path
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
experiment = loadpxp("./FLSopE2.pxp")
# experiment = loadpxp("./2019.01.01.SdrGBullCantileverRampClamp_delTraceClean.pxp")
# unpack the pxp
_, file_structure = experiment
# get the folder we care about
folder_we_care_about = file_structure['root']['MyForceData']['WLCFits']
dictkeys = []
dictkeys = folder_we_care_about.keys()
print (dictkeys)
print (len(dictkeys))
print(type(folder_we_care_about))
count = 0
combinedData = numpy.array([])
for i in dictkeys:
print (str(i))
from dateutil.tz import tzlocal
import os.path
from pprint import pprint
import numpy
import platform
import matplotlib.pyplot as plt
import pynwb
filename = '141117c2.pxp'
filename = '141210c3.pxp'
protocols = {'nm10Dec2014c3_000': 'Control', 'nm10Dec2014c3_002': 'Norepinephrine', 'nm10Dec2014c3_003':'Washout'}
protocol_info = {'nm10Dec2014c3_000': 'Prior to drug application', 'nm10Dec2014c3_002': 'Application of norepinephrine (noradrenaline)', 'nm10Dec2014c3_003':'Following wash out of drug'}
path = os.path.join('./', filename)
records,filesystem = loadpxp(path)
from datetime import datetime
now = datetime.now() # current date and time
date_time = now.strftime("%d %B %Y, %H:%M:%S")
gen_info = 'NWB file generated on %s with pynwb v%s and Python %s' %(date_time, pynwb.__version__,platform.python_version())
print gen_info
sub = pynwb.file.Subject(
description='Mouse',
species='Mus musculus',
)
nwbfile = pynwb.NWBFile('Golgi cell ephys recordings', filename, datetime.now(tzlocal()),
experimenter='Frederic Lanore',
import numpy
import re
import pandas
import numpy
import matplotlib.pyplot as plt
import os.path
"""
<Description>
Args:
param1: This is the first param.
Returns:
This is a description of what is returned.
"""
experiment = loadpxp("./combinedGoodFiles_Sptp_clean.pxp")
# experiment = loadpxp("./2019.01.01.SdrGBullCantileverRampClamp_delTraceClean.pxp")
# unpack the pxp
_, file_structure = experiment
# get the folder we care about
folder_we_care_about = file_structure['root']['MyForceData']['WLCFits']
dictkeys = []
dictkeys = folder_we_care_about.keys()
print(dictkeys)
print(len(dictkeys))
print(type(folder_we_care_about))
count = 0
combinedData = numpy.array([])
for i in dictkeys:
print(str(i))