In [1]:
%matplotlib inline
from __future__ import division
import pdb
import sys
import pandas as pd
import numpy as np
import scipy.io as sio
import matplotlib.pyplot as plt
import matplotlib
import scipy.signal as sg
import math
import scipy as sp
import socket
import os
import multiprocessing
matplotlib.style.use('ggplot')
comp_name=socket.gethostname()
if comp_name == 'Ezequiels-MacBook-Pro.local':
print 'Computer: ' + comp_name
sys.path.append('/Users/zeke/experiment/ephysDataManagement/ephysScripts')
experiment_folder = os.path.join('/Users','zeke','experiment')
else:
print 'Computer: ' + 'server'
sys.path.append('/experiment/ephysDataManagement/ephysScripts')
experiment_folder = os.path.join('/','experiment')
import unitToolsv2
from data_handling import ephys_names as en
from data_handling.basic_plot import decim, plot_raster, make_psth, col_binned
from data_handling import data_load as dl
from data_handling.data_load import get_warping_parameters
from analysis import stimulus as st
from analysis import response_functions as rf
#load all the records, to not load all the records for every stimulus
fn = en.file_names(root = experiment_folder)
cells_path = os.path.join(fn.fold_exp_data, 'data_play', 'all')
uf = dl.list_cells(cells_path)
all_cells = [f for f in uf if f.find('ZKawakeM72_029')>-1]
all_cells = uf
#print all_cells
all_records = dl.load_cells(cells_path, all_cells)
#all_records = dl.load_cells(cells_path)
## create a stimulus and initialize it (load its responses)
high_2hydroxy = st.Odor(['2-hydroxyacetophenone','2hydroxyacetophenone'], 0.0051)
st_1 = st.Stimulus(high_2hydroxy, records = all_records, tags = {'light':1} )
#get the first response and plot it
warp = True
#st_1.responses['ZKawakeM72_013_e_010'].get_response_onset(warped=warp)
#rp = st_1.responses['ZKawakeM72_013_e_010'].plot(warped=warp)
#make all the odor stimuli
tags = {'light':1}
# {odor_name: [stim_aliases], conc, records, tags, extra_plot_pars}
all_odors_list = {'2-hydroxy_high': [['2-hydroxyacetophenone','2hydroxyacetophenone'], 0.0051,
all_records, tags, {'color': '#9F000F', 'alpha': 1.}],
'2-hydroxy_med': [['2-hydroxyacetophenone','2hydroxyacetophenone'], 2.97e-4,
all_records, tags, {'color': '#F62217', 'alpha': .5}],
'2-hydroxy_low': [['2-hydroxyacetophenone','2hydroxyacetophenone'], 1.8e-5,
all_records, tags, {'color': '#E77471', 'alpha': .25}],
'ethyl_tiglate': [['ethyl_tiglate','ethyltiglate'], 1.3e-4,
all_records, tags, {'color': '#41a317', 'alpha': 1.}],
'acetophenone': [['acetophenone','acetoph'], 7.9e-4,
all_records, tags, {'color': '#43c6db', 'alpha': 1.}],
'4-methyl': [['4-methylacetophenone','4methyl'], 1.8e-3,
all_records, tags, {'color': '#FF00FF', 'alpha': 1.}],
'benzaldehyde': [['benzaldehyde', 'benz'], 1.9e-4,
all_records, tags, {'color': '#F88017', 'alpha': 1.}],
'2-4-dimethyl': [['2-4-dimethylacetophenone', '24-dimethylacetophenone'], 5.8e-3,
all_records, tags, {'color': '#FFD801', 'alpha': 1.}],
'menthone_high': [['menthone', 'mentone'], 1.6e-2,
all_records,tags, {'color': '#000080', 'alpha': 1.}],
'menthone_med': [['menthone', 'mentone'], 1.6e-3,
all_records, tags, {'color': '#1569c7', 'alpha': 0.5}],
'menthone_low': [['menthone', 'mentone'], 7e-5,
all_records, tags, {'color': '#188AC7', 'alpha': .25}]
}
all_odors = {}
for key, sd in all_odors_list.iteritems():
all_odors.update({key: st.Stimulus(st.Odor(sd[0], sd[1]), records=sd[2], tags=sd[3], extra_plot_pars=sd[4])})
all_odors_population = {}
for key, sd in all_odors_list.iteritems():
all_odors_population.update({key: st.Stimulus(st.Odor(sd[0], sd[1]), records=sd[2], tags = {'light':0}, extra_plot_pars=sd[4])})
all_odor_responses = {'litral': all_odors, 'population': all_odors_population}
print all_odors.keys()
#[r.plot(warped=True) for r in list(st_1.responses.values())]
Computer: server
Computer: server
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/experiment/export_data/data_play/all/ZKawakeM72_030_022_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_023_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_024_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_025_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_026_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_027_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_028_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_029_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_030_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_031_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_032_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_033_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_034_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_035_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_036_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_037_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_038_cell.mat
/experiment/export_data/data_play/all/ZKawakeM72_030_039_cell.mat
['ethyl_tiglate', '4-methyl', 'menthone_med', 'menthone_high', 'acetophenone', '2-4-dimethyl', 'menthone_low', '2-hydroxy_med', '2-hydroxy_high', '2-hydroxy_low', 'benzaldehyde']
In [2]:
# compute cell_response properties for all the cellresponses in a list of stimuli
def worker(procnum, stim_list, params=None):
#print str(procnum)
default_params = {'warp': False, 'bin_size':15, 'p': 0.05}
par = default_params
if params is not None:
for key, val in params.iteritems():
par.update({key: val})
if type(stim_list) is not list:
stim_list = [stim_list]
for stim in stim_list:
for r_name, r in list(stim.cell_responses.iteritems()):
try:
r.get_response_onset(warped=par['warp'], bin_size=par['bin_size'], p_ks=par['p'])
r.get_spike_count()
#r.plot(warped=warp)
print 'ok ' + r_name
except:
print 'fail in ' + r_name
In [51]:
#get all the population rec
all_odors_population = {}
for key, sd in all_odors_list.iteritems():
all_odors_population.update({key: st.Stimulus(st.Odor(sd[0], sd[1]), records=sd[2], tags = {'light':0}, extra_plot_pars=sd[4])})
In [3]:
procs = 8
jobs =[]
n_stim = len(all_odors)
stim_per_proc = int(math.ceil(n_stim/procs))
for i in range(0, procs):
keys = all_odors_population.keys()[i*stim_per_proc: (i+1)*stim_per_proc]
stim = [all_odors_population[key] for key in keys]
if not stim == []:
print keys
print i
process = multiprocessing.Process(target=worker(i, stim))
jobs.append(process)
[j.start() for j in jobs]
[j.join() for j in jobs]
['ethyl_tiglate', '4-methyl']
0
ok ZKawakeM72_011_004
fail in KPawakeM72_016_001
ok ZKawakeM72_011_007
fail in KPawakeM72_016_007
fail in KPawakeM72_016_006
fail in KPawakeM72_016_005
ok ZKawakeM72_011_003
fail in KPawakeM72_016_009
fail in KPawakeM72_016_008
ok ZKawakeM72_011_006
ok ZKawakeM72_012_009
ok ZKawakeM72_012_008
ok ZKawakeM72_012_010
ok ZKawakeM72_012_011
ok ZKawakeM72_012_012
ok ZKawakeM72_012_013
ok ZKawakeM72_012_003
fail in KPawakeM72_014_017
ok KPawakeM72_014_007
ok KPawakeM72_014_006
ok ZKawakeM72_012_007
ok ZKawakeM72_012_006
ok ZKawakeM72_012_005
ok ZKawakeM72_012_004
ok KPawakeM72_014_001
ok KPawakeM72_014_004
fail in KPawakeM72_016_025
fail in KPawakeM72_016_019
fail in ZKawakeM72_010_003
fail in ZKawakeM72_010_002
fail in KPawakeM72_016_021
fail in KPawakeM72_016_020
fail in KPawakeM72_016_023
fail in KPawakeM72_016_017
fail in KPawakeM72_016_010
fail in KPawakeM72_016_011
fail in KPawakeM72_016_012
fail in ZKawakeM72_011_005
fail in KPawakeM72_016_001
fail in ZKawakeM72_011_010
fail in KPawakeM72_016_007
fail in KPawakeM72_016_006
fail in KPawakeM72_016_005
fail in ZKawakeM72_011_012
fail in ZKawakeM72_011_011
fail in KPawakeM72_016_008
fail in KPawakeM72_016_009
ok KPawakeM72_014_017
ok ZKawakeM72_004_020
ok ZKawakeM72_004_021
fail in ZKawakeM72_004_010
fail in ZKawakeM72_004_006
fail in ZKawakeM72_004_007
fail in ZKawakeM72_004_022
ok ZKawakeM72_004_023
fail in KPawakeM72_016_025
fail in ZKawakeM72_004_008
ok ZKawakeM72_009_003
fail in ZKawakeM72_009_002
ok ZKawakeM72_009_001
fail in KPawakeM72_016_011
ok ZKawakeM72_010_004
fail in KPawakeM72_016_019
fail in KPawakeM72_016_021
fail in KPawakeM72_016_020
fail in KPawakeM72_016_023
fail in KPawakeM72_016_017
fail in KPawakeM72_016_010
fail in ZKawakeM72_009_005
fail in KPawakeM72_016_012
['menthone_med', 'menthone_high']
1
fail in KPawakeM72_016_001
fail in ZKawakeM72_029_005
fail in KPawakeM72_016_006
ok ZKawakeM72_020_019
ok ZKawakeM72_020_018
ok ZKawakeM72_020_017
ok ZKawakeM72_020_016
ok ZKawakeM72_020_015
ok KPawakeM72_019_003
ok ZKawakeM72_020_013
ok ZKawakeM72_020_012
ok ZKawakeM72_020_011
ok ZKawakeM72_020_010
fail in ZKawakeM72_030_025
ok ZKawakeM72_030_027
fail in ZKawakeM72_030_026
fail in KPawakeM72_016_007
fail in ZKawakeM72_030_029
fail in ZKawakeM72_027_001
fail in ZKawakeM72_029_004
ok ZKawakeM72_004_003
ok ZKawakeM72_023_004
fail in ZKawakeM72_004_006
fail in KPawakeM72_016_005
ok ZKawakeM72_004_004
ok ZKawakeM72_004_005
fail in KPawakeM72_021_030
fail in KPawakeM72_021_031
fail in ZKawakeM72_004_008
ok ZKawakeM72_029_006
ok KPawakeM72_014_006
ok ZKawakeM72_029_009
fail in ZKawakeM72_030_039
fail in KPawakeM72_016_009
fail in ZKawakeM72_020_026
ok ZKawakeM72_020_027
ok ZKawakeM72_020_024
fail in KPawakeM72_016_008
fail in ZKawakeM72_020_023
fail in ZKawakeM72_020_020
fail in KPawakeM72_019_018
ok KPawakeM72_019_004
fail in KPawakeM72_019_015
fail in KPawakeM72_019_014
fail in KPawakeM72_019_013
fail in KPawakeM72_019_011
fail in KPawakeM72_019_010
ok ZKawakeM72_012_010
ok KPawakeM72_019_006
ok ZKawakeM72_012_012
ok ZKawakeM72_012_013
ok ZKawakeM72_023_005
fail in KPawakeM72_019_007
fail in ZKawakeM72_004_011
ok ZKawakeM72_004_012
fail in ZKawakeM72_004_015
ok ZKawakeM72_004_014
fail in ZKawakeM72_004_017
fail in ZKawakeM72_004_016
ok ZKawakeM72_004_019
fail in ZKawakeM72_004_018
fail in KPawakeM72_021_028
fail in KPawakeM72_021_023
ok KPawakeM72_019_020
fail in ZKawakeM72_028_017
fail in ZKawakeM72_028_016
fail in ZKawakeM72_028_015
fail in ZKawakeM72_028_014
fail in ZKawakeM72_028_012
fail in KPawakeM72_021_026
fail in ZKawakeM72_028_019
ok ZKawakeM72_011_004
ok ZKawakeM72_020_031
ok ZKawakeM72_020_030
ok ZKawakeM72_020_033
ok KPawakeM72_019_021
ok KPawakeM72_023_003
ok KPawakeM72_023_001
ok KPawakeM72_023_006
ok ZKawakeM72_012_009
ok ZKawakeM72_012_008
ok ZKawakeM72_012_003
ok KPawakeM72_014_017
ok ZKawakeM72_030_005
ok ZKawakeM72_030_004
ok ZKawakeM72_012_007
ok ZKawakeM72_012_006
ok ZKawakeM72_012_005
ok ZKawakeM72_012_004
fail in KPawakeM72_021_016
fail in ZKawakeM72_004_025
fail in KPawakeM72_021_012
fail in KPawakeM72_021_029
fail in KPawakeM72_021_010
fail in KPawakeM72_021_011
fail in ZKawakeM72_030_003
fail in ZKawakeM72_020_021
fail in ZKawakeM72_028_022
fail in ZKawakeM72_028_023
fail in ZKawakeM72_028_020
fail in ZKawakeM72_028_021
fail in ZKawakeM72_030_001
fail in KPawakeM72_016_021
fail in KPawakeM72_016_020
fail in KPawakeM72_016_023
ok KPawakeM72_019_005
fail in KPawakeM72_016_025
ok ZKawakeM72_022_004
fail in ZKawakeM72_020_008
ok ZKawakeM72_020_009
ok ZKawakeM72_011_006
ok ZKawakeM72_011_007
ok ZKawakeM72_011_003
ok ZKawakeM72_022_002
ok ZKawakeM72_020_002
ok ZKawakeM72_020_003
fail in ZKawakeM72_020_004
fail in ZKawakeM72_022_003
ok ZKawakeM72_020_006
ok ZKawakeM72_020_007
fail in ZKawakeM72_030_036
fail in ZKawakeM72_030_037
fail in ZKawakeM72_030_034
fail in ZKawakeM72_030_035
fail in ZKawakeM72_030_032
ok ZKawakeM72_020_028
ok ZKawakeM72_030_030
ok ZKawakeM72_030_031
ok ZKawakeM72_027_003
ok KPawakeM72_014_004
ok KPawakeM72_014_007
ok ZKawakeM72_020_029
ok KPawakeM72_014_001
fail in ZKawakeM72_030_038
fail in ZKawakeM72_004_007
fail in KPawakeM72_016_017
fail in KPawakeM72_021_006
fail in ZKawakeM72_030_033
fail in KPawakeM72_021_003
fail in ZKawakeM72_030_002
fail in ZKawakeM72_020_025
ok ZKawakeM72_020_032
fail in KPawakeM72_016_019
fail in ZKawakeM72_010_003
fail in ZKawakeM72_010_002
fail in ZKawakeM72_029_003
ok ZKawakeM72_021_002
fail in KPawakeM72_016_010
fail in KPawakeM72_016_011
fail in KPawakeM72_016_012
ok ZKawakeM72_012_011
fail in ZKawakeM72_029_003
fail in ZKawakeM72_029_005
ok ZKawakeM72_029_004
ok KPawakeM72_019_020
ok ZKawakeM72_020_018
ok ZKawakeM72_020_017
ok ZKawakeM72_020_016
ok KPawakeM72_023_001
ok KPawakeM72_019_003
ok KPawakeM72_019_004
ok KPawakeM72_023_006
ok KPawakeM72_019_006
ok KPawakeM72_019_007
fail in ZKawakeM72_030_025
ok ZKawakeM72_030_027
fail in ZKawakeM72_030_026
fail in ZKawakeM72_028_020
ok ZKawakeM72_029_009
ok ZKawakeM72_020_031
ok ZKawakeM72_030_005
ok ZKawakeM72_030_004
fail in ZKawakeM72_030_003
fail in ZKawakeM72_030_002
fail in ZKawakeM72_030_001
ok ZKawakeM72_020_030
ok KPawakeM72_021_016
ok KPawakeM72_021_017
ok KPawakeM72_021_014
ok ZKawakeM72_020_009
fail in KPawakeM72_021_012
ok KPawakeM72_021_013
ok KPawakeM72_021_010
ok KPawakeM72_021_011
fail in KPawakeM72_021_030
ok ZKawakeM72_030_029
ok ZKawakeM72_029_006
fail in ZKawakeM72_028_022
fail in ZKawakeM72_028_023
ok KPawakeM72_021_018
fail in ZKawakeM72_028_021
ok KPawakeM72_023_003
ok KPawakeM72_021_009
fail in KPawakeM72_024_003
ok ZKawakeM72_020_015
ok ZKawakeM72_020_027
fail in ZKawakeM72_022_003
ok ZKawakeM72_020_028
ok ZKawakeM72_020_029
fail in ZKawakeM72_030_036
fail in ZKawakeM72_030_037
fail in ZKawakeM72_030_034
ok ZKawakeM72_030_035
fail in ZKawakeM72_030_032
fail in ZKawakeM72_030_033
ok ZKawakeM72_020_033
ok ZKawakeM72_030_031
ok ZKawakeM72_027_003
fail in ZKawakeM72_027_001
fail in ZKawakeM72_020_010
fail in ZKawakeM72_030_038
fail in ZKawakeM72_030_039
ok KPawakeM72_021_005
ok KPawakeM72_021_004
ok KPawakeM72_019_021
ok KPawakeM72_021_006
ok KPawakeM72_019_005
ok KPawakeM72_021_003
fail in KPawakeM72_021_029
fail in KPawakeM72_021_028
fail in KPawakeM72_021_026
fail in KPawakeM72_021_023
ok KPawakeM72_021_008
fail in ZKawakeM72_028_017
fail in ZKawakeM72_028_016
fail in ZKawakeM72_028_015
fail in ZKawakeM72_028_014
ok ZKawakeM72_020_032
fail in ZKawakeM72_028_012
fail in KPawakeM72_021_031
ok ZKawakeM72_020_019
ok ZKawakeM72_030_030
fail in ZKawakeM72_028_019
['acetophenone', '2-4-dimethyl']
2
fail in KPawakeM72_016_001
fail in KPawakeM72_016_007
fail in KPawakeM72_016_006
fail in KPawakeM72_016_005
fail in KPawakeM72_016_009
fail in KPawakeM72_016_008
ok ZKawakeM72_004_003
ok ZKawakeM72_012_009
ok ZKawakeM72_012_008
ok ZKawakeM72_012_003
fail in KPawakeM72_014_017
ok ZKawakeM72_012_007
ok ZKawakeM72_012_006
ok ZKawakeM72_012_005
ok ZKawakeM72_012_004
fail in ZKawakeM72_004_025
ok ZKawakeM72_004_004
ok ZKawakeM72_004_005
fail in KPawakeM72_016_021
fail in KPawakeM72_016_020
fail in KPawakeM72_016_023
fail in KPawakeM72_016_025
ok ZKawakeM72_011_004
ok ZKawakeM72_011_006
ok ZKawakeM72_011_007
ok ZKawakeM72_011_003
ok ZKawakeM72_012_010
ok ZKawakeM72_012_011
ok ZKawakeM72_012_012
ok ZKawakeM72_012_013
ok KPawakeM72_014_004
ok KPawakeM72_014_007
fail in KPawakeM72_014_006
ok KPawakeM72_014_001
fail in ZKawakeM72_004_011
ok ZKawakeM72_004_012
fail in ZKawakeM72_004_015
ok ZKawakeM72_004_014
fail in ZKawakeM72_004_017
ok ZKawakeM72_004_016
fail in ZKawakeM72_004_019
fail in ZKawakeM72_004_018
fail in KPawakeM72_016_019
fail in ZKawakeM72_010_003
fail in ZKawakeM72_010_002
fail in KPawakeM72_016_017
fail in KPawakeM72_016_010
fail in KPawakeM72_016_011
fail in KPawakeM72_016_012
fail in ZKawakeM72_011_005
fail in KPawakeM72_016_001
fail in ZKawakeM72_011_010
fail in KPawakeM72_016_007
fail in KPawakeM72_016_006
fail in KPawakeM72_016_005
fail in ZKawakeM72_011_012
fail in ZKawakeM72_011_011
fail in KPawakeM72_016_008
fail in KPawakeM72_016_009
ok KPawakeM72_014_017
ok ZKawakeM72_004_020
ok ZKawakeM72_004_021
fail in ZKawakeM72_004_010
fail in ZKawakeM72_004_006
fail in ZKawakeM72_004_007
fail in ZKawakeM72_004_022
fail in ZKawakeM72_004_023
fail in KPawakeM72_016_025
fail in ZKawakeM72_004_008
ok ZKawakeM72_009_003
ok ZKawakeM72_009_002
ok ZKawakeM72_009_001
fail in KPawakeM72_016_011
ok ZKawakeM72_010_004
fail in KPawakeM72_016_019
fail in KPawakeM72_016_021
fail in KPawakeM72_016_020
fail in KPawakeM72_016_023
fail in KPawakeM72_016_017
fail in KPawakeM72_016_010
ok ZKawakeM72_009_005
fail in KPawakeM72_016_012
['menthone_low', '2-hydroxy_med']
3
ok ZKawakeM72_020_027
ok ZKawakeM72_020_029
ok ZKawakeM72_020_031
ok ZKawakeM72_020_030
ok KPawakeM72_019_020
ok KPawakeM72_019_021
ok KPawakeM72_023_003
ok ZKawakeM72_020_016
ok ZKawakeM72_020_015
ok KPawakeM72_019_003
ok KPawakeM72_019_004
ok KPawakeM72_023_006
ok ZKawakeM72_020_028
ok ZKawakeM72_020_010
ok ZKawakeM72_020_009
ok KPawakeM72_019_006
fail in KPawakeM72_021_029
fail in ZKawakeM72_027_003
fail in KPawakeM72_021_012
fail in ZKawakeM72_027_001
ok KPawakeM72_019_007
fail in KPawakeM72_021_016
fail in KPawakeM72_021_006
ok KPawakeM72_019_005
ok ZKawakeM72_020_033
fail in KPawakeM72_021_003
fail in KPawakeM72_021_011
fail in KPawakeM72_021_030
fail in KPawakeM72_021_031
ok ZKawakeM72_020_018
fail in KPawakeM72_021_023
fail in KPawakeM72_021_028
fail in KPawakeM72_021_010
ok ZKawakeM72_020_017
ok ZKawakeM72_020_032
fail in KPawakeM72_021_026
ok ZKawakeM72_020_019
fail in KPawakeM72_024_003
ok KPawakeM72_023_001
fail in ZKawakeM72_020_026
ok KPawakeM72_023_003
ok KPawakeM72_023_001
ok ZKawakeM72_020_013
ok ZKawakeM72_020_012
ok ZKawakeM72_020_011
fail in KPawakeM72_019_007
fail in KPawakeM72_019_010
ok ZKawakeM72_029_011
fail in ZKawakeM72_020_004
ok KPawakeM72_021_016
ok KPawakeM72_021_017
ok KPawakeM72_021_014
ok KPawakeM72_021_013
ok KPawakeM72_021_010
ok KPawakeM72_021_011
ok ZKawakeM72_020_002
fail in KPawakeM72_019_018
ok KPawakeM72_021_018
fail in ZKawakeM72_028_001
ok ZKawakeM72_028_002
ok ZKawakeM72_028_003
fail in ZKawakeM72_028_004
fail in ZKawakeM72_028_005
fail in ZKawakeM72_028_006
ok ZKawakeM72_028_007
fail in ZKawakeM72_028_008
ok ZKawakeM72_028_009
fail in KPawakeM72_019_015
ok ZKawakeM72_029_012
fail in ZKawakeM72_029_013
ok ZKawakeM72_020_024
ok ZKawakeM72_020_025
ok ZKawakeM72_020_023
fail in ZKawakeM72_020_020
fail in ZKawakeM72_020_021
fail in KPawakeM72_019_013
ok ZKawakeM72_022_004
fail in KPawakeM72_019_014
ok ZKawakeM72_022_002
fail in KPawakeM72_019_011
ok ZKawakeM72_020_007
ok KPawakeM72_023_006
ok ZKawakeM72_020_006
ok ZKawakeM72_027_003
ok ZKawakeM72_023_005
fail in ZKawakeM72_023_004
ok ZKawakeM72_027_006
ok KPawakeM72_021_005
ok KPawakeM72_021_004
ok KPawakeM72_021_006
ok KPawakeM72_021_003
fail in ZKawakeM72_029_010
ok KPawakeM72_021_009
ok KPawakeM72_021_008
ok ZKawakeM72_028_011
ok ZKawakeM72_028_010
ok ZKawakeM72_021_002
fail in ZKawakeM72_020_008
fail in ZKawakeM72_020_003
['2-hydroxy_high', '2-hydroxy_low']
4
fail in KPawakeM72_016_001
ok ZKawakeM72_028_010
fail in KPawakeM72_016_007
fail in KPawakeM72_016_006
ok ZKawakeM72_020_019
ok ZKawakeM72_020_018
ok ZKawakeM72_020_017
ok ZKawakeM72_020_016
fail in ZKawakeM72_011_011
fail in ZKawakeM72_011_010
ok ZKawakeM72_020_013
ok ZKawakeM72_020_012
ok ZKawakeM72_020_011
ok ZKawakeM72_020_010
fail in ZKawakeM72_030_024
ok ZKawakeM72_030_021
fail in ZKawakeM72_030_020
ok ZKawakeM72_030_023
fail in ZKawakeM72_030_022
fail in KPawakeM72_016_008
ok ZKawakeM72_030_013
ok ZKawakeM72_030_012
ok ZKawakeM72_004_003
ok ZKawakeM72_023_004
fail in ZKawakeM72_004_006
fail in KPawakeM72_016_005
ok ZKawakeM72_004_004
ok ZKawakeM72_004_005
fail in KPawakeM72_021_030
fail in KPawakeM72_021_031
fail in ZKawakeM72_004_008
ok KPawakeM72_019_021
fail in ZKawakeM72_028_001
ok ZKawakeM72_028_002
ok ZKawakeM72_028_003
fail in ZKawakeM72_028_004
ok ZKawakeM72_028_005
fail in ZKawakeM72_028_006
fail in ZKawakeM72_011_012
fail in ZKawakeM72_028_008
fail in ZKawakeM72_028_009
ok ZKawakeM72_020_015
fail in ZKawakeM72_020_026
ok ZKawakeM72_020_027
ok ZKawakeM72_020_024
ok KPawakeM72_019_003
ok ZKawakeM72_020_023
fail in ZKawakeM72_020_020
fail in KPawakeM72_019_018
ok KPawakeM72_019_004
fail in KPawakeM72_019_015
fail in KPawakeM72_019_014
fail in KPawakeM72_019_013
fail in KPawakeM72_019_011
ok KPawakeM72_019_005
fail in ZKawakeM72_030_018
fail in ZKawakeM72_030_019
ok ZKawakeM72_020_029
ok ZKawakeM72_012_010
ok KPawakeM72_019_006
ok ZKawakeM72_012_012
ok ZKawakeM72_012_013
ok ZKawakeM72_030_010
ok ZKawakeM72_023_005
fail in KPawakeM72_019_007
ok ZKawakeM72_030_014
ok ZKawakeM72_030_015
ok ZKawakeM72_030_016
ok ZKawakeM72_030_017
fail in ZKawakeM72_004_011
fail in ZKawakeM72_004_010
ok ZKawakeM72_004_012
ok ZKawakeM72_004_014
fail in KPawakeM72_021_029
fail in KPawakeM72_021_028
ok ZKawakeM72_004_019
fail in KPawakeM72_021_026
fail in ZKawakeM72_009_005
fail in KPawakeM72_021_023
ok ZKawakeM72_009_002
ok ZKawakeM72_009_001
fail in ZKawakeM72_028_007
fail in ZKawakeM72_028_011
fail in ZKawakeM72_004_018
fail in ZKawakeM72_029_012
fail in ZKawakeM72_029_010
ok ZKawakeM72_020_031
ok ZKawakeM72_020_030
ok KPawakeM72_019_020
ok ZKawakeM72_020_032
ok KPawakeM72_023_003
ok ZKawakeM72_009_003
ok KPawakeM72_023_001
ok ZKawakeM72_027_003
ok KPawakeM72_023_006
ok ZKawakeM72_012_003
ok ZKawakeM72_012_009
ok ZKawakeM72_012_008
ok ZKawakeM72_030_009
ok ZKawakeM72_030_008
ok ZKawakeM72_030_007
ok ZKawakeM72_030_006
ok ZKawakeM72_012_007
ok ZKawakeM72_012_006
ok ZKawakeM72_012_005
ok ZKawakeM72_012_004
ok KPawakeM72_021_016
ok KPawakeM72_021_017
ok KPawakeM72_021_014
fail in KPawakeM72_021_012
ok ZKawakeM72_004_021
ok KPawakeM72_021_010
ok KPawakeM72_021_011
fail in ZKawakeM72_020_021
ok KPawakeM72_021_018
fail in ZKawakeM72_004_025
fail in ZKawakeM72_020_008
fail in ZKawakeM72_004_017
fail in KPawakeM72_016_017
fail in KPawakeM72_016_021
fail in KPawakeM72_016_020
fail in KPawakeM72_016_023
fail in KPawakeM72_016_025
ok ZKawakeM72_022_004
ok ZKawakeM72_011_004
fail in ZKawakeM72_011_005
ok ZKawakeM72_011_006
ok ZKawakeM72_011_007
ok ZKawakeM72_011_003
fail in ZKawakeM72_029_013
ok ZKawakeM72_022_002
ok ZKawakeM72_020_002
fail in ZKawakeM72_020_003
ok ZKawakeM72_020_004
fail in ZKawakeM72_022_003
ok ZKawakeM72_020_006
ok ZKawakeM72_020_007
ok ZKawakeM72_020_009
ok ZKawakeM72_020_028
ok ZKawakeM72_020_033
ok KPawakeM72_014_017
ok ZKawakeM72_004_020
ok KPawakeM72_014_007
ok KPawakeM72_014_006
ok KPawakeM72_014_001
ok ZKawakeM72_027_006
ok KPawakeM72_021_013
ok KPawakeM72_021_005
ok KPawakeM72_021_004
ok KPawakeM72_021_006
fail in ZKawakeM72_004_022
ok KPawakeM72_021_003
ok ZKawakeM72_020_025
ok ZKawakeM72_004_023
ok KPawakeM72_021_009
ok KPawakeM72_021_008
fail in KPawakeM72_019_010
ok ZKawakeM72_010_004
ok KPawakeM72_014_004
fail in ZKawakeM72_004_007
fail in ZKawakeM72_029_011
fail in KPawakeM72_016_019
fail in ZKawakeM72_010_003
fail in ZKawakeM72_010_002
fail in KPawakeM72_016_009
ok ZKawakeM72_021_002
fail in KPawakeM72_016_010
fail in KPawakeM72_016_011
fail in KPawakeM72_016_012
ok ZKawakeM72_012_011
ok ZKawakeM72_029_012
ok KPawakeM72_023_003
ok KPawakeM72_023_001
ok ZKawakeM72_020_013
ok KPawakeM72_023_006
ok ZKawakeM72_020_011
ok ZKawakeM72_029_011
ok KPawakeM72_021_010
ok KPawakeM72_021_016
ok KPawakeM72_021_017
ok KPawakeM72_021_014
ok KPawakeM72_021_013
ok ZKawakeM72_004_004
ok KPawakeM72_021_011
ok KPawakeM72_021_018
fail in ZKawakeM72_004_025
fail in ZKawakeM72_020_008
fail in ZKawakeM72_004_017
fail in ZKawakeM72_020_026
fail in ZKawakeM72_029_013
ok ZKawakeM72_020_024
ok ZKawakeM72_020_025
ok ZKawakeM72_020_023
fail in ZKawakeM72_020_020
fail in ZKawakeM72_020_021
ok ZKawakeM72_020_002
fail in ZKawakeM72_020_003
ok ZKawakeM72_020_004
ok KPawakeM72_021_005
fail in ZKawakeM72_020_006
ok ZKawakeM72_020_012
ok ZKawakeM72_004_012
ok ZKawakeM72_027_003
ok ZKawakeM72_023_005
ok ZKawakeM72_023_004
ok ZKawakeM72_027_006
fail in ZKawakeM72_004_011
ok KPawakeM72_021_004
ok KPawakeM72_021_006
fail in ZKawakeM72_004_015
ok ZKawakeM72_004_014
ok KPawakeM72_021_003
ok ZKawakeM72_004_016
fail in ZKawakeM72_029_010
fail in ZKawakeM72_004_018
ok ZKawakeM72_004_005
ok KPawakeM72_021_009
ok KPawakeM72_021_008
ok ZKawakeM72_004_003
ok ZKawakeM72_004_019
fail in ZKawakeM72_020_007
ok ZKawakeM72_021_002
['benzaldehyde']
5
fail in ZKawakeM72_011_005
fail in KPawakeM72_016_001
fail in ZKawakeM72_011_010
fail in KPawakeM72_016_007
fail in KPawakeM72_016_006
fail in KPawakeM72_016_005
ok ZKawakeM72_011_012
fail in ZKawakeM72_011_011
fail in KPawakeM72_016_008
fail in KPawakeM72_016_009
ok KPawakeM72_014_017
fail in ZKawakeM72_004_020
ok ZKawakeM72_004_021
fail in ZKawakeM72_004_010
fail in ZKawakeM72_004_006
fail in ZKawakeM72_004_007
fail in ZKawakeM72_004_022
ok ZKawakeM72_004_023
fail in KPawakeM72_016_025
fail in ZKawakeM72_004_008
ok ZKawakeM72_009_003
fail in ZKawakeM72_009_002
fail in ZKawakeM72_009_001
fail in KPawakeM72_016_011
ok ZKawakeM72_010_004
fail in KPawakeM72_016_019
fail in KPawakeM72_016_021
fail in KPawakeM72_016_020
fail in KPawakeM72_016_023
fail in KPawakeM72_016_017
fail in KPawakeM72_016_010
ok ZKawakeM72_009_005
fail in KPawakeM72_016_012
/usr/local/anaconda/lib/python2.7/site-packages/numpy/core/_methods.py:59: RuntimeWarning: Mean of empty slice.
warnings.warn("Mean of empty slice.", RuntimeWarning)
Out[3]:
[None, None, None, None, None, None]
In [6]:
#plot all the responses to all the stimuli
response_row = np.zeros(1, dtype=[('stim', '|S32'), ('resp', '|S32'), ('latency', 'f4'), ('onset_lvl','f4'),
('spikes_inh', 'f4'), ('spikes_exh', 'f4'), ('spikes', 'f4'), ('ratio','f4')])
non_litrals = np.zeros_like(response_row)
#print litrals
warp = False
bin_size = 15
p=0.05
for st_name, stim in all_odors_population.iteritems():
#print st_name
#print stim.responses.keys()
for r_name, r in list(stim.cell_responses.iteritems()):
this_resp = np.zeros_like(response_row)
this_resp['stim'] = st_name
this_resp['resp'] = r_name
if r.response_onset is None:
continue
this_resp['latency'] = r.response_onset['onset']
this_resp['onset_lvl'] = r.response_onset['response'] - r.response_onset['baseline']
this_resp['spikes_inh'] = r.spikes['inh']
this_resp['spikes_exh'] = r.spikes['exh']
this_resp['spikes'] = this_resp['spikes_inh'] + this_resp['spikes_exh']
this_resp['ratio'] = this_resp['spikes_inh']/this_resp['spikes_exh']
non_litrals = np.append(non_litrals, this_resp)
#r.plot(warped=warp)
In [4]:
#get a list of cells, a list of stimuli and compute them all in parallel
#load all the records, to not load all the records for every stimulus
fn = en.file_names(root = experiment_folder)
cells_path = os.path.join(fn.fold_exp_data, 'data_play')
uf = dl.list_cells(cells_path)
all_cells = [f for f in uf if f.find('KPawakeM72_019')>-1]
print all_cells
all_records = dl.load_cells(cells_path, all_cells)
#all_records = dl.load_cells(cells_path)
#get the first response and plot it
warp = True
#st_1.responses['ZKawakeM72_013_e_010'].get_response_onset(warped=warp)
#rp = st_1.responses['ZKawakeM72_013_e_010'].plot(warped=warp)
#make all the odor stimuli
tags = {'light':1}
odor_dicts_list = []
recs_list = []
path_list = []
for key, sd in all_odors_list.iteritems():
one_odor = {key: st.Stimulus(st.Odor(sd[0], sd[1]), records=sd[2], tags=sd[3], extra_plot_pars=sd[4])}
odor_dicts_list.append(one_odor)
recs_list.append(sd[2])
path_list.append(cells_path)
['KPawakeM72_019_002', 'KPawakeM72_019_003', 'KPawakeM72_019_004', 'KPawakeM72_019_005', 'KPawakeM72_019_006', 'KPawakeM72_019_007', 'KPawakeM72_019_010', 'KPawakeM72_019_011', 'KPawakeM72_019_013', 'KPawakeM72_019_014', 'KPawakeM72_019_015', 'KPawakeM72_019_018', 'KPawakeM72_019_020', 'KPawakeM72_019_021']
/experiment/export_data/data_play/KPawakeM72_019_002_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_003_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_004_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_005_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_006_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_007_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_010_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_011_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_013_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_014_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_015_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_018_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_020_cell.mat
/experiment/export_data/data_play/KPawakeM72_019_021_cell.mat
In [5]:
#plot all the responses to all the stimuli
response_row = np.zeros(1, dtype=[('stim', '|S32'), ('resp', '|S32'), ('latency', 'f4'), ('onset_lvl','f4'),
('spikes_inh', 'f4'), ('spikes_exh', 'f4'), ('spikes', 'f4'), ('ratio','f4')
]
)
litrals = np.zeros_like(response_row)
#print litrals
warp = False
bin_size = 15
p=0.05
for st_name, stim in all_odors.iteritems():
#print st_name
#print stim.responses.keys()
for r_name, r in list(stim.cell_responses.iteritems()):
this_resp = np.zeros_like(response_row)
this_resp['stim'] = st_name
this_resp['resp'] = r_name
this_resp['latency'] = r.response_onset['onset']
this_resp['onset_lvl'] = r.response_onset['response'] - r.response_onset['baseline']
this_resp['spikes_inh'] = r.spikes['inh']
this_resp['spikes_exh'] = r.spikes['exh']
this_resp['spikes'] = this_resp['spikes_inh'] + this_resp['spikes_exh']
this_resp['ratio'] = this_resp['spikes_inh']/this_resp['spikes_exh']
litrals = np.append(litrals, this_resp)
#r.plot(warped=warp)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-6db463bef4fd> in <module>()
16 this_resp['stim'] = st_name
17 this_resp['resp'] = r_name
---> 18 this_resp['latency'] = r.response_onset['onset']
19 this_resp['onset_lvl'] = r.response_onset['response'] - r.response_onset['baseline']
20 this_resp['spikes_inh'] = r.spikes['inh']
TypeError: 'NoneType' object has no attribute '__getitem__'
In [30]:
r=all_odors['2-4-dimethyl'].responses['KPawakeM72_014_b_012']
In [7]:
feature_fig = plt.figure()
ax = feature_fig.add_axes([0, 0, 1, 1])
n_recs = 0
prop = 'latency'
litrals.sort(order = 'resp')
for odor, stim in all_odors.iteritems():
#print odor
feat = litrals[litrals['stim'] == odor][prop]
#print feat
stim.plot_pars['marker'] = 'o'
stim.plot_pars['ms'] = 8
ax.plot(feat, np.arange(1, feat.shape[0]+1), **stim.plot_pars)
n_recs = max(n_recs, feat.shape[0])
ax.set_ylim(0, n_recs+1)
Out[7]:
(0, 1)
In [62]:
feature_fig = plt.figure()
ax = feature_fig.add_axes([0, 0, 1, 1])
n_recs = 0
# for odor, stim in all_odors.iteritems():
# #print odor
# feat = litrals[litrals['stim'] == odor][prop]
# #print feat
# stim.plot_pars['marker'] = 'v'
# ax.plot(feat, np.arange(1, feat.shape[0]+1), **stim.plot_pars)
# n_recs = max(n_recs, feat.shape[0])
# ax.set_ylim(0, n_recs+1)
# prop = 'spikes_inh'
# for odor, stim in all_odors.iteritems():
# #print odor
# feat = litrals[litrals['stim'] == odor][prop]
# #print feat
# stim.plot_pars['marker'] = '^'
# ax.plot(feat, np.arange(1, feat.shape[0]+1), **stim.plot_pars)
# n_recs = max(n_recs, feat.shape[0])
prop = 'latency'
non_litrals.sort(order = 'resp')
for odor, stim in all_odors.iteritems():
#print odor
feat = non_litrals[non_litrals['stim'] == odor][prop]
#print feat
stim.plot_pars['marker'] = 'o'
stim.plot_pars['ms'] = 8
ax.plot(feat, np.arange(1, feat.shape[0]+1), **stim.plot_pars)
n_recs = max(n_recs, feat.shape[0])
ax.set_ylim(0, n_recs+1)
Out[62]:
(0, 182)
In [158]:
import numbers
response_row = np.zeros(1, dtype=[('stim', '|S32'), ('resp', '|S32'), ('litral','?'), ('latency', 'f4'),
('onset_lvl','f4'), ('spikes_inh', 'f4'), ('spikes_exh', 'f4'),
('spikes', 'f4'), ('ratio','f4')
]
)
responses_array = np.zeros_like(response_row)
for field in responses_array.dtype.names:
print field
if isinstance(responses_array[field][0], numbers.Number):
responses_array[field][0] = np.nan
print responses_array[:]
stim
resp
litral
latency
onset_lvl
spikes_inh
spikes_exh
spikes
ratio
[('', '', False, nan, nan, nan, nan, nan, nan)]
In [157]:
isinstance(responses_array[field][0], numbers.Number)
Out[157]:
True
In [171]:
st = all_odors['2-4-dimethyl']
r = st.responses[st.responses.keys()[0]]
In [154]:
stim = all_odors
Out[154]:
numpy.float32
In [186]:
responses_array['litral'] = r.rec['meta']['light']
print responses_array[:]
[('', '', True, nan, nan, nan, nan, nan, nan)]
In [5]:
stim=all_odors[all_odors.keys()[0]]
stim.responses.itervalues().next().rec['meta']
Out[5]:
{'comment': 'response to all ligands, beautiful order',
'id': 'ZKawakeM72_013_e_011',
'light': 1,
'mouse': 'ZKawakeM72',
'odor': 1,
'quality': 1,
'rec': 'e',
'sess': 13,
'sessCell': 11,
'u_id': 'ZKawakeM72_013_011'}
In [203]:
print r.rec
r
{'meta': {'comment': 'response to all weak ligands, 2 hydroxy first; stim set 2, waveform clu and responses look same as e4', 'sess': 13, 'mouse': 'ZKawakeM72', 'rec': 'f', 'light': 1, 'odor': 1, 'u_id': 'ZKawakeM72_013_010', 'quality': 1, 'id': 'ZKawakeM72_013_f_010', 'sessCell': 10}, 'rec_id': 'ZKawakeM72_013_f'}
Out[203]:
<analysis.stimulus.Response instance at 0x7fa5353dcb00>
In [211]:
stim = all_odors['2-hydroxy_high']
for key, value in stim.responses.iteritems():
print value.rec['meta'] ['u_id'] + ' - ' + value.rec['meta'] ['id']
myset = set([value.rec['meta']['u_id'] for value in stim.responses.itervalues()])
print myset
KPawakeM72_817_001 - KPawakeM72_817_f_001
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
KPawakeM72_016_018 - KPawakeM72_016_a_018
KPawakeM72_016_016 - KPawakeM72_016_a_016
KPawakeM72_019_002 - KPawakeM72_019_b_002
KPawakeM72_021_001 - KPawakeM72_021_b_001
KPawakeM72_024_001 - KPawakeM72_024_a_001
ZKawakeM72_012_001 - ZKawakeM72_012_a_001
ZKawakeM72_005_001 - ZKawakeM72_005_a_001
KPawakeM72_021_001 - KPawakeM72_021_a_001
ZKawakeM72_012_002 - ZKawakeM72_012_a_002
KPawakeM72_014_012 - KPawakeM72_014_b_012
ZKawakeM72_011_001 - ZKawakeM72_011_d_001
KPawakeM72_024_002 - KPawakeM72_024_b_002
ZKawakeM72_020_001 - ZKawakeM72_020_g_001
KPawakeM72_019_002 - KPawakeM72_019_d_002
ZKawakeM72_020_001 - ZKawakeM72_020_d_001
KPawakeM72_023_005 - KPawakeM72_023_a_005
ZKawakeM72_004_001 - ZKawakeM72_004_i_001
ZKawakeM72_004_002 - ZKawakeM72_004_i_002
ZKawakeM72_004_001 - ZKawakeM72_004_h_001
ZKawakeM72_013_011 - ZKawakeM72_013_e_011
ZKawakeM72_013_010 - ZKawakeM72_013_e_010
ZKawakeM72_013_010 - ZKawakeM72_013_f_010
ZKawakeM72_027_004 - ZKawakeM72_027_e_004
ZKawakeM72_020_001 - ZKawakeM72_020_e_001
ZKawakeM72_015_001 - ZKawakeM72_015_d_001
ZKawakeM72_022_001 - ZKawakeM72_022_d_001
ZKawakeM72_020_001 - ZKawakeM72_020_c_001
ZKawakeM72_004_002 - ZKawakeM72_004_h_002
ZKawakeM72_010_001 - ZKawakeM72_010_b_001
set(['ZKawakeM72_015_001', 'KPawakeM72_019_002', 'KPawakeM72_023_005', 'ZKawakeM72_010_001', 'ZKawakeM72_012_002', 'ZKawakeM72_012_001', 'KPawakeM72_817_001', 'KPawakeM72_014_012', 'ZKawakeM72_004_002', 'ZKawakeM72_004_001', 'KPawakeM72_024_001', 'KPawakeM72_024_002', 'ZKawakeM72_011_001', 'ZKawakeM72_020_001', 'ZKawakeM72_022_001', 'ZKawakeM72_005_001', 'ZKawakeM72_027_004', 'KPawakeM72_021_001', 'ZKawakeM72_013_011', 'ZKawakeM72_013_010', 'KPawakeM72_016_018', 'KPawakeM72_016_016', 'ZKawakeM72_006_001'])
In [219]:
key
dir(value)
#value.rec
value.all_trials
Out[219]:
{'ZKawakeM72_010_b_1010205': {'mouse': 'ZKawakeM72',
'odor': 'menthone',
'odor_c': 0.0015999999595806003,
'odor_t': array([ 329, 3329]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 532., 564., 550., ..., 275., 279., 259.]),
'sniff_zero': array([[-5360, -4879, -4368, -3912, -3402, -2905, -2429, -1934, -1471,
-963, -459, 1, 313, 751, 1182, 1703, 2233, 2839,
3444, 3958, 4441, 4912, 5431, 5939],
[-5238, -4761, -4242, -3784, -3279, -2783, -2303, -1806, -1343,
-838, -336, 114, 401, 811, 1282, 1827, 2364, 2985,
3578, 4092, 4581, 5046, 5558, 6071]]),
'start': 1010005},
'ZKawakeM72_010_b_1038885': {'mouse': 'ZKawakeM72',
'odor': '2-hydroxyacetophenone',
'odor_c': 0.005100000184029341,
'odor_t': array([ 275, 3275]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([-268., -260., -275., ..., 175., 191., 228.]),
'sniff_zero': array([[-5026, -4921, -4771, -4660, -4542, -4407, -4289, -4158, -4060,
-3952, -3849, -3734, -3623, -3512, -3395, -3273, -3165, -3041,
-2897, -2782, -2652, -2537, -2416, -2303, -2194, -2070, -1950,
-1817, -1703, -1590, -1423, -1287, -1139, -1001, -870, -110,
1, 135, 245, 368, 495, 611, 737, 878, 1026,
1184, 1328, 1470, 2185, 2358, 2554, 2711, 2876, 3047,
3539, 4000, 4259, 4422, 4630, 4851, 5126, 5277, 5423,
5577],
[-4984, -4881, -4732, -4618, -4501, -4367, -4248, -4119, -4018,
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-834, -407, -1, 414, 878, 1214, 1705, 2317, 2539,
2934, 3355, 3611, 3983, 4459, 4970, 5495],
[-4975, -4493, -4000, -3468, -2963, -2549, -2103, -1637, -1188,
-701, -289, 115, 506, 931, 1313, 1922, 2367, 2594,
3000, 3417, 3693, 4115, 4596, 5119, 5642]]),
'start': 459477},
'ZKawakeM72_010_b_492105': {'mouse': 'ZKawakeM72',
'odor': 'menthone',
'odor_c': 0.0015999999595806003,
'odor_t': array([ 280, 3280]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 1357., 1369., 1398., ..., 2580., 2588., 2569.]),
'sniff_zero': array([[-5445, -4912, -4389, -3890, -3373, -2876, -2457, -1998, -1513,
-1014, -564, -82, 305, 832, 1364, 1967, 2606, 3191,
3801, 4266, 4729, 5212, 5768],
[-5304, -4777, -4249, -3744, -3222, -2740, -2323, -1865, -1379,
-883, -425, 63, 406, 955, 1498, 2108, 2755, 3344,
3948, 4409, 4873, 5362, 5920]]),
'start': 491905},
'ZKawakeM72_010_b_4953856': {'mouse': 'ZKawakeM72',
'odor': 'acetophenone',
'odor_c': 0.00023700000019744039,
'odor_t': array([ 355, 2355]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 491., 500., 516., ..., -2518., -2548., -2550.]),
'sniff_zero': array([[-5000, -4670, -4433, -4252, -3917, -3676, -3518, -3194, -3021,
-2781, -2538, -2386, -2218, -2040, -1872, -1603, -1415, -1181,
-762, -441, 2, 454, 887, 1332, 1906, 2453, 3070,
3663, 4206, 4773, 5352, 5923],
[-4920, -4605, -4377, -4192, -3852, -3629, -3472, -3148, -2983,
-2742, -2495, -2341, -2182, -2002, -1834, -1570, -1372, -1135,
-698, -355, 103, 549, 930, 1431, 2026, 2585, 3189,
3783, 4339, 4898, 5466, 6048]]),
'start': 4953656},
'ZKawakeM72_010_b_524659': {'mouse': 'ZKawakeM72',
'odor': 'ethyl_tiglate',
'odor_c': 0.00013000000035390258,
'odor_t': array([ 328, 3328]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 1327., 1318., 1375., ..., 1480., 1454., 1420.]),
'sniff_zero': array([[-5270, -4748, -4299, -3820, -3386, -2886, -2380, -1882, -1407,
-911, -441, -2, 396, 813, 1407, 1935, 2521, 3067,
3546, 3958, 4293, 4527, 4766, 5025, 5360, 5682],
[-5121, -4598, -4188, -3688, -3260, -2766, -2250, -1744, -1281,
-769, -299, 129, 499, 935, 1540, 2078, 2669, 3181,
3654, 4059, 4335, 4575, 4829, 5116, 5473, 5774]]),
'start': 524459},
'ZKawakeM72_010_b_556658': {'mouse': 'ZKawakeM72',
'odor': '2-hydroxyacetophenone',
'odor_c': 0.005100000184029341,
'odor_t': array([ 309, 3309]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 1134., 1139., 1168., ..., -2771., -2789., -2817.]),
'sniff_zero': array([[-5156, -4697, -4310, -3894, -3466, -3067, -2670, -2207, -1781,
-1348, -881, -430, -2, 367, 910, 1383, 1891, 2442,
2981, 3421, 3911, 4391, 4858, 5295, 5772],
[-5028, -4568, -4202, -3776, -3342, -2947, -2557, -2086, -1670,
-1229, -753, -298, 110, 472, 1049, 1509, 2031, 2588,
3129, 3569, 4059, 4537, 4999, 5436, 5865]]),
'start': 556458},
'ZKawakeM72_010_b_585473': {'mouse': 'ZKawakeM72',
'odor': 'acetophenone',
'odor_c': 0.0007900000200606883,
'odor_t': array([ 348, 3348]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 739., 774., 805., ..., 835., 849., 808.]),
'sniff_zero': array([[-5309, -4869, -4389, -4000, -3620, -3205, -2782, -2338, -1866,
-1393, -919, -454, -1, 313, 796, 1274, 1774, 2258,
2740, 3262, 3726, 4203, 4652, 5166, 5606],
[-5191, -4732, -4246, -3875, -3512, -3086, -2651, -2211, -1729,
-1259, -791, -322, 141, 416, 927, 1407, 1909, 2402,
2888, 3409, 3873, 4347, 4801, 5311, 5735]]),
'start': 585273},
'ZKawakeM72_010_b_615460': {'mouse': 'ZKawakeM72',
'odor': 'ethyl_tiglate',
'odor_c': 0.00013000000035390258,
'odor_t': array([ 288, 3288]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 791., 796., 805., ..., 657., 637., 623.]),
'sniff_zero': array([[-5038, -4575, -4166, -3716, -3228, -2758, -2296, -1810, -1365,
-941, -512, -47, 301, 704, 1226, 1742, 2236, 2801,
3240, 3660, 4153, 4476, 4717, 4985, 5282, 5577, 5912],
[-4914, -4447, -4037, -3585, -3091, -2633, -2183, -1695, -1240,
-825, -388, 81, 394, 823, 1358, 1859, 2383, 2946,
3357, 3818, 4288, 4524, 4792, 5075, 5377, 5688, 6021]]),
'start': 615260},
'ZKawakeM72_010_b_62619': {'mouse': 'ZKawakeM72',
'odor': 'acetophenone',
'odor_c': 0.0007900000200606883,
'odor_t': array([ 228, 3228]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 254., 268., 270., ..., 39., 42., 51.]),
'sniff_zero': array([[-5581, -4965, -4325, -3658, -3018, -2472, -1839, -1197, -565,
86, 607, 1085, 1420, 1704, 2309, 2779, 3343, 3723,
4293, 4553, 5217],
[-5426, -4822, -4183, -3515, -2860, -2331, -1691, -1050, -412,
197, 715, 1174, 1475, 1795, 2442, 2875, 3492, 3821,
4362, 4660, 5414]]),
'start': 62419},
'ZKawakeM72_010_b_648193': {'mouse': 'ZKawakeM72',
'odor': 'menthone',
'odor_c': 0.0015999999595806003,
'odor_t': array([ 285, 3285]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([-7333., -7458., -7517., ..., -6819., -6853., -6853.]),
'sniff_zero': array([[-5311, -4878, -4617, -4233, -3826, -3382, -2969, -2733, -2316,
-1918, -1593, -1258, -1052, -849, -412, -210, -1, 282,
484, 831, 1272, 1546, 1996, 2467, 3329, 3902, 4224,
4345, 4466, 4772, 5155, 5295, 5698],
[-5235, -4831, -4521, -4116, -3710, -3258, -2917, -2616, -2183,
-1801, -1493, -1177, -992, -784, -335, -160, 79, 324,
558, 875, 1322, 1589, 2059, 2528, 3401, 3984, 4264,
4471, 4512, 4858, 5196, 5378, 5809]]),
'start': 647993},
'ZKawakeM72_010_b_680181': {'mouse': 'ZKawakeM72',
'odor': '2-hydroxyacetophenone',
'odor_c': 0.005100000184029341,
'odor_t': array([ 259, 3259]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 937., 921., 928., ..., -4086., -4005., -3905.]),
'sniff_zero': array([[-5107, -4660, -4206, -3735, -3299, -2847, -2369, -1897, -1456,
-995, -542, -83, 341, 854, 1402, 1900, 2428, 2938,
3434, 3893, 4341, 4808, 5250, 5699],
[-4966, -4525, -4078, -3593, -3163, -2712, -2234, -1760, -1321,
-863, -406, 61, 445, 988, 1536, 2051, 2571, 3078,
3586, 4038, 4488, 4955, 5389, 5838]]),
'start': 679981},
'ZKawakeM72_010_b_708431': {'mouse': 'ZKawakeM72',
'odor': 'acetophenone',
'odor_c': 0.0007900000200606883,
'odor_t': array([ 341, 3341]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 896., 888., 878., ..., -5539., -5569., -5606.]),
'sniff_zero': array([[-5379, -4911, -4505, -4073, -3670, -3255, -2803, -2306, -1867,
-1452, -974, -482, -2, 355, 824, 1158, 1560, 2003,
2417, 2923, 3451, 3975, 4443, 4921, 5407, 5897],
[-5226, -4767, -4350, -3933, -3546, -3121, -2663, -2168, -1725,
-1308, -830, -339, 146, 459, 915, 1246, 1668, 2097,
2553, 3066, 3598, 4126, 4590, 5075, 5555, 6052]]),
'start': 708231},
'ZKawakeM72_010_b_736369': {'mouse': 'ZKawakeM72',
'odor': 'menthone',
'odor_c': 0.0015999999595806003,
'odor_t': array([ 268, 3268]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 887., 889., 883., ..., 1406., 1384., 1366.]),
'sniff_zero': array([[-5151, -4643, -4248, -3845, -3382, -2889, -2484, -2018, -1505,
-1029, -580, -86, 332, 778, 1348, 1913, 2517, 3082,
3661, 4105, 4574, 5003, 5483, 5938],
[-5014, -4492, -4135, -3715, -3234, -2742, -2353, -1876, -1359,
-893, -438, 68, 444, 922, 1496, 2061, 2666, 3235,
3782, 4242, 4718, 5150, 5635, 6092]]),
'start': 736169},
'ZKawakeM72_010_b_765409': {'mouse': 'ZKawakeM72',
'odor': '2-hydroxyacetophenone',
'odor_c': 0.005100000184029341,
'odor_t': array([ 335, 3335]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 784., 780., 777., ..., -1672., -1701., -1737.]),
'sniff_zero': array([[-5233, -4799, -4301, -3779, -3306, -2834, -2398, -1944, -1448,
-978, -499, 0, 428, 895, 1411, 1959, 2479, 2991,
3429, 3885, 4331, 4800, 5327, 5812],
[-5134, -4684, -4178, -3650, -3170, -2710, -2276, -1816, -1314,
-839, -372, 132, 539, 1018, 1547, 2097, 2618, 3135,
3575, 4021, 4461, 4939, 5464, 5950]]),
'start': 765209},
'ZKawakeM72_010_b_794134': {'mouse': 'ZKawakeM72',
'odor': 'acetophenone',
'odor_c': 0.0007900000200606883,
'odor_t': array([ 288, 3288]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 520., 524., 528., ..., -4162., -4127., -4088.]),
'sniff_zero': array([[-5120, -4614, -4119, -3664, -3204, -2669, -2134, -1650, -1170,
-613, -65, 319, 830, 1353, 1867, 2381, 2917, 3399,
3871, 4295, 4761, 5255, 5756],
[-4976, -4471, -3984, -3540, -3067, -2533, -1988, -1508, -1018,
-477, 84, 432, 970, 1494, 2009, 2523, 3068, 3550,
4022, 4434, 4911, 5402, 5873]]),
'start': 793934},
'ZKawakeM72_010_b_825320': {'mouse': 'ZKawakeM72',
'odor': 'ethyl_tiglate',
'odor_c': 0.00013000000035390258,
'odor_t': array([ 350, 3350]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 779., 763., 756., ..., 1038., 1032., 1042.]),
'sniff_zero': array([[-5188, -4691, -4176, -3610, -3106, -2609, -2104, -1549, -1018,
-489, -2, 426, 905, 1443, 1986, 2575, 3041, 3577,
4125, 4670, 5150, 5709],
[-5042, -4552, -4045, -3466, -2964, -2463, -1965, -1422, -864,
-339, 151, 540, 1052, 1578, 2137, 2725, 3185, 3736,
4277, 4826, 5302, 5870]]),
'start': 825120},
'ZKawakeM72_010_b_856267': {'mouse': 'ZKawakeM72',
'odor': 'menthone',
'odor_c': 0.0015999999595806003,
'odor_t': array([ 322, 3322]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 713., 701., 714., ..., 430., 416., 407.]),
'sniff_zero': array([[-5350, -4914, -4452, -3969, -3514, -3014, -2539, -2052, -1545,
-1038, -530, -20, 493, 1007, 1622, 2217, 2860, 3480,
4051, 4572, 5093, 5651],
[-5217, -4777, -4317, -3838, -3381, -2887, -2424, -1908, -1427,
-894, -388, 125, 640, 1144, 1769, 2370, 3015, 3645,
4210, 4730, 5248, 5811]]),
'start': 856067},
'ZKawakeM72_010_b_888004': {'mouse': 'ZKawakeM72',
'odor': 'ethyl_tiglate',
'odor_c': 0.00013000000035390258,
'odor_t': array([ 255, 3255]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 792., 797., 797., ..., -3290., -3250., -3201.]),
'sniff_zero': array([[-5209, -4723, -4266, -3812, -3327, -2829, -2393, -1971, -1504,
-1000, -545, -82, 318, 758, 1327, 1885, 2429, 2970,
3489, 3951, 4342, 4604, 4804, 5025, 5312, 5784],
[-5086, -4608, -4143, -3691, -3207, -2705, -2292, -1863, -1388,
-873, -422, 49, 414, 863, 1450, 2021, 2567, 3110,
3610, 4069, 4435, 4656, 4858, 5080, 5410, 5894]]),
'start': 887804},
'ZKawakeM72_010_b_89594': {'mouse': 'ZKawakeM72',
'odor': '2-hydroxyacetophenone',
'odor_c': 0.005100000184029341,
'odor_t': array([ 417, 3417]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 326., 320., 305., ..., -2951., -2967., -2961.]),
'sniff_zero': array([[-5382, -4752, -4117, -3518, -2992, -2467, -1848, -1244, -626,
-1, 308, 838, 1326, 1833, 2406, 2996, 3614, 4183,
4653, 5255, 5891],
[-5239, -4601, -3971, -3373, -2848, -2325, -1700, -1092, -465,
160, 385, 957, 1417, 1951, 2557, 3152, 3770, 4325,
4795, 5402, 6045]]),
'start': 89394},
'ZKawakeM72_010_b_921451': {'mouse': 'ZKawakeM72',
'odor': '2-hydroxyacetophenone',
'odor_c': 0.005100000184029341,
'odor_t': array([ 267, 3267]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 76., 135., 151., ..., 1957., 2090., 2230.]),
'sniff_zero': array([[-5244, -4753, -4308, -3876, -3415, -2947, -2570, -2236, -1981,
-1846, -1555, -1365, -1027, -773, -619, -479, -361, -252,
-132, -7, 134, 294, 433, 887, 1417, 1625, 1767,
2000, 2168, 2519, 2963, 3194, 3460, 3703, 3982, 4201,
4359, 4713, 4855, 5072, 5274, 5397, 5527, 5653, 5786,
5917],
[-5123, -4629, -4187, -3757, -3305, -2844, -2469, -2135, -1931,
-1798, -1506, -1323, -989, -728, -581, -435, -318, -210,
-92, 35, 176, 332, 475, 952, 1480, 1684, 1808,
2047, 2215, 2576, 3074, 3249, 3508, 3761, 4064, 4266,
4426, 4759, 4929, 5138, 5335, 5445, 5577, 5699, 5832,
5966]]),
'start': 921251},
'ZKawakeM72_010_b_950612': {'mouse': 'ZKawakeM72',
'odor': 'acetophenone',
'odor_c': 0.0007900000200606883,
'odor_t': array([ 275, 3275]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ -74., -87., -86., ..., 234., 246., 266.]),
'sniff_zero': array([[-5010, -4885, -4764, -4653, -4537, -3978, -3850, -3712, -3548,
-3401, -3266, -3157, -3054, -2938, -2829, -2703, -2587, -2486,
-2369, -2259, -2145, -2031, -1900, -1785, -1666, -1540, -1409,
-1271, -1153, -1024, -884, -740, -603, -470, -345, -233,
-120, -2, 116, 239, 353, 499, 622, 747, 869,
1010, 1141, 1707, 1907, 2045, 2162, 2274, 2406, 2527,
2638, 2748, 2867, 2989, 3120, 3247, 3400, 3525, 3673,
3790, 3911, 4033, 4150, 4262, 4388, 4522, 4634, 4738,
4880, 4999, 5128, 5241, 5356, 5485, 5601, 5713, 5834,
5952],
[-4968, -4846, -4721, -4608, -4497, -3923, -3802, -3667, -3502,
-3357, -3222, -3114, -3010, -2895, -2789, -2659, -2545, -2445,
-2324, -2217, -2103, -1988, -1854, -1743, -1624, -1496, -1366,
-1230, -1110, -978, -841, -696, -557, -427, -305, -191,
-77, 42, 159, 282, 394, 544, 664, 788, 910,
1053, 1179, 1764, 1975, 2087, 2208, 2317, 2449, 2571,
2682, 2790, 2907, 3032, 3164, 3289, 3444, 3570, 3715,
3831, 3951, 4075, 4195, 4305, 4428, 4563, 4678, 4781,
4919, 5039, 5168, 5286, 5400, 5527, 5643, 5751, 5875,
5994]]),
'start': 950412},
'ZKawakeM72_010_b_979474': {'mouse': 'ZKawakeM72',
'odor': 'ethyl_tiglate',
'odor_c': 0.00013000000035390258,
'odor_t': array([ 338, 3338]),
'rec': 'b',
'rec_id': 'ZKawakeM72_010_b',
'sess': 10,
'sniff_flow': array([ 560., 558., 556., ..., -3161., -3152., -3150.]),
'sniff_zero': array([[-5298, -4802, -4321, -3850, -3371, -2880, -2396, -1930, -1456,
-988, -499, 0, 377, 865, 1363, 1902, 2444, 2989,
3524, 4039, 4475, 4941, 5429, 5872],
[-5172, -4682, -4205, -3722, -3242, -2755, -2267, -1804, -1327,
-863, -380, 121, 454, 978, 1483, 2029, 2578, 3125,
3667, 4173, 4613, 5075, 5562, 6003]]),
'start': 979274}}
In [201]:
for stim in all_odors.itervalues():
print stim
print '--'
for value in (stim.responses.itervalues()):
print value.rec['meta'] ['u_id'] + ' - ' + value.rec['meta'] ['id']
<analysis.stimulus.Stimulus instance at 0x7fa535025c20>
--
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
KPawakeM72_016_018 - KPawakeM72_016_a_018
KPawakeM72_016_016 - KPawakeM72_016_a_016
ZKawakeM72_013_011 - ZKawakeM72_013_e_011
ZKawakeM72_013_010 - ZKawakeM72_013_e_010
ZKawakeM72_012_001 - ZKawakeM72_012_a_001
ZKawakeM72_012_002 - ZKawakeM72_012_a_002
KPawakeM72_014_012 - KPawakeM72_014_b_012
ZKawakeM72_011_001 - ZKawakeM72_011_d_001
ZKawakeM72_005_001 - ZKawakeM72_005_a_001
ZKawakeM72_010_001 - ZKawakeM72_010_b_001
<analysis.stimulus.Stimulus instance at 0x7fa534482758>
--
ZKawakeM72_013_010 - ZKawakeM72_013_f_010
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
KPawakeM72_014_012 - KPawakeM72_014_b_012
KPawakeM72_016_018 - KPawakeM72_016_a_018
KPawakeM72_016_016 - KPawakeM72_016_a_016
ZKawakeM72_004_001 - ZKawakeM72_004_i_001
ZKawakeM72_004_002 - ZKawakeM72_004_i_002
<analysis.stimulus.Stimulus instance at 0x7fa525d48830>
--
ZKawakeM72_027_004 - ZKawakeM72_027_d_004
KPawakeM72_817_001 - KPawakeM72_817_f_001
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
ZKawakeM72_020_014 - ZKawakeM72_020_f_014
KPawakeM72_016_016 - KPawakeM72_016_a_016
KPawakeM72_019_002 - KPawakeM72_019_b_002
KPawakeM72_021_001 - KPawakeM72_021_b_001
ZKawakeM72_012_001 - ZKawakeM72_012_a_001
ZKawakeM72_005_001 - ZKawakeM72_005_a_001
ZKawakeM72_012_002 - ZKawakeM72_012_a_002
KPawakeM72_014_012 - KPawakeM72_014_b_012
ZKawakeM72_011_001 - ZKawakeM72_011_d_001
ZKawakeM72_029_002 - ZKawakeM72_029_a_002
KPawakeM72_019_002 - KPawakeM72_019_d_002
ZKawakeM72_020_001 - ZKawakeM72_020_d_001
KPawakeM72_023_005 - KPawakeM72_023_a_005
KPawakeM72_016_018 - KPawakeM72_016_a_018
ZKawakeM72_004_001 - ZKawakeM72_004_h_001
ZKawakeM72_013_011 - ZKawakeM72_013_e_011
ZKawakeM72_013_010 - ZKawakeM72_013_e_010
ZKawakeM72_020_001 - ZKawakeM72_020_g_001
ZKawakeM72_020_001 - ZKawakeM72_020_e_001
ZKawakeM72_015_001 - ZKawakeM72_015_d_001
ZKawakeM72_022_001 - ZKawakeM72_022_d_001
ZKawakeM72_020_001 - ZKawakeM72_020_c_001
ZKawakeM72_004_002 - ZKawakeM72_004_h_002
ZKawakeM72_010_001 - ZKawakeM72_010_b_001
<analysis.stimulus.Stimulus instance at 0x7fa533b49fc8>
--
ZKawakeM72_027_004 - ZKawakeM72_027_d_004
KPawakeM72_817_001 - KPawakeM72_817_f_001
KPawakeM72_023_005 - KPawakeM72_023_a_005
KPawakeM72_024_002 - KPawakeM72_024_c_002
KPawakeM72_019_002 - KPawakeM72_019_b_002
KPawakeM72_021_001 - KPawakeM72_021_b_001
ZKawakeM72_020_001 - ZKawakeM72_020_g_001
KPawakeM72_021_001 - KPawakeM72_021_a_001
ZKawakeM72_015_001 - ZKawakeM72_015_d_001
ZKawakeM72_020_001 - ZKawakeM72_020_d_001
ZKawakeM72_029_002 - ZKawakeM72_029_a_002
<analysis.stimulus.Stimulus instance at 0x7fa5336419e0>
--
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
KPawakeM72_016_018 - KPawakeM72_016_a_018
KPawakeM72_016_016 - KPawakeM72_016_a_016
ZKawakeM72_013_011 - ZKawakeM72_013_e_011
ZKawakeM72_013_010 - ZKawakeM72_013_e_010
ZKawakeM72_012_001 - ZKawakeM72_012_a_001
ZKawakeM72_004_001 - ZKawakeM72_004_h_001
ZKawakeM72_012_002 - ZKawakeM72_012_a_002
KPawakeM72_014_012 - KPawakeM72_014_b_012
ZKawakeM72_011_001 - ZKawakeM72_011_d_001
ZKawakeM72_005_001 - ZKawakeM72_005_a_001
ZKawakeM72_004_002 - ZKawakeM72_004_h_002
ZKawakeM72_010_001 - ZKawakeM72_010_b_001
<analysis.stimulus.Stimulus instance at 0x7fa5353dcb90>
--
ZKawakeM72_013_010 - ZKawakeM72_013_f_010
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
KPawakeM72_014_012 - KPawakeM72_014_b_012
KPawakeM72_016_018 - KPawakeM72_016_a_018
KPawakeM72_016_016 - KPawakeM72_016_a_016
ZKawakeM72_004_001 - ZKawakeM72_004_i_001
ZKawakeM72_004_002 - ZKawakeM72_004_i_002
ZKawakeM72_010_001 - ZKawakeM72_010_c_001
<analysis.stimulus.Stimulus instance at 0x7fa5357ec200>
--
ZKawakeM72_027_004 - ZKawakeM72_027_d_004
KPawakeM72_817_001 - KPawakeM72_817_f_001
KPawakeM72_023_005 - KPawakeM72_023_a_005
ZKawakeM72_020_001 - ZKawakeM72_020_g_001
KPawakeM72_024_002 - KPawakeM72_024_c_002
KPawakeM72_019_002 - KPawakeM72_019_b_002
ZKawakeM72_020_001 - ZKawakeM72_020_d_001
KPawakeM72_021_001 - KPawakeM72_021_b_001
<analysis.stimulus.Stimulus instance at 0x7fa535950cf8>
--
KPawakeM72_019_002 - KPawakeM72_019_d_002
KPawakeM72_021_001 - KPawakeM72_021_a_001
ZKawakeM72_020_001 - ZKawakeM72_020_e_001
KPawakeM72_023_005 - KPawakeM72_023_a_005
ZKawakeM72_027_004 - ZKawakeM72_027_e_004
ZKawakeM72_022_001 - ZKawakeM72_022_d_001
ZKawakeM72_020_001 - ZKawakeM72_020_c_001
KPawakeM72_024_002 - KPawakeM72_024_b_002
KPawakeM72_024_001 - KPawakeM72_024_a_001
<analysis.stimulus.Stimulus instance at 0x7fa530b43b48>
--
KPawakeM72_817_001 - KPawakeM72_817_f_001
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
KPawakeM72_016_018 - KPawakeM72_016_a_018
KPawakeM72_016_016 - KPawakeM72_016_a_016
KPawakeM72_019_002 - KPawakeM72_019_b_002
KPawakeM72_021_001 - KPawakeM72_021_b_001
KPawakeM72_024_001 - KPawakeM72_024_a_001
ZKawakeM72_012_001 - ZKawakeM72_012_a_001
ZKawakeM72_005_001 - ZKawakeM72_005_a_001
KPawakeM72_021_001 - KPawakeM72_021_a_001
ZKawakeM72_012_002 - ZKawakeM72_012_a_002
KPawakeM72_014_012 - KPawakeM72_014_b_012
ZKawakeM72_011_001 - ZKawakeM72_011_d_001
KPawakeM72_024_002 - KPawakeM72_024_b_002
ZKawakeM72_020_001 - ZKawakeM72_020_g_001
KPawakeM72_019_002 - KPawakeM72_019_d_002
ZKawakeM72_020_001 - ZKawakeM72_020_d_001
KPawakeM72_023_005 - KPawakeM72_023_a_005
ZKawakeM72_004_001 - ZKawakeM72_004_i_001
ZKawakeM72_004_002 - ZKawakeM72_004_i_002
ZKawakeM72_004_001 - ZKawakeM72_004_h_001
ZKawakeM72_013_011 - ZKawakeM72_013_e_011
ZKawakeM72_013_010 - ZKawakeM72_013_e_010
ZKawakeM72_013_010 - ZKawakeM72_013_f_010
ZKawakeM72_027_004 - ZKawakeM72_027_e_004
ZKawakeM72_020_001 - ZKawakeM72_020_e_001
ZKawakeM72_015_001 - ZKawakeM72_015_d_001
ZKawakeM72_022_001 - ZKawakeM72_022_d_001
ZKawakeM72_020_001 - ZKawakeM72_020_c_001
ZKawakeM72_004_002 - ZKawakeM72_004_h_002
ZKawakeM72_010_001 - ZKawakeM72_010_b_001
<analysis.stimulus.Stimulus instance at 0x7fa534c2da70>
--
ZKawakeM72_027_004 - ZKawakeM72_027_e_004
KPawakeM72_021_001 - KPawakeM72_021_a_001
ZKawakeM72_020_001 - ZKawakeM72_020_e_001
KPawakeM72_023_005 - KPawakeM72_023_a_005
KPawakeM72_024_002 - KPawakeM72_024_b_002
ZKawakeM72_004_001 - ZKawakeM72_004_h_001
ZKawakeM72_020_001 - ZKawakeM72_020_c_001
ZKawakeM72_004_002 - ZKawakeM72_004_h_002
KPawakeM72_024_001 - KPawakeM72_024_a_001
<analysis.stimulus.Stimulus instance at 0x7fa525cd4a28>
--
ZKawakeM72_013_010 - ZKawakeM72_013_f_010
ZKawakeM72_006_001 - ZKawakeM72_006_a_001
KPawakeM72_014_012 - KPawakeM72_014_b_012
KPawakeM72_016_018 - KPawakeM72_016_a_018
KPawakeM72_016_016 - KPawakeM72_016_a_016
ZKawakeM72_004_001 - ZKawakeM72_004_i_001
ZKawakeM72_004_002 - ZKawakeM72_004_i_002
In [5]:
import statsmodels.robust.scale as stat
import scipy.stats as stat2
def merge_responses(responses):
new_responses = {}
cells_set = set([value.rec['meta']['u_id'] for value in responses.itervalues()])
print cells_set
#for every cell in the set find and merge all the responsive records
for u_id in cells_set:
#get the list of cells with that u_id
this_set = {u_id : [r for r in responses.itervalues() if r.rec['meta']['u_id']==u_id]}
new_responses.update(this_set)
return new_responses
t_post = 400
warped = False
def make_raster(cell_response, t_pre=200, t_post=t_post, warped=warped):
raster = cell_response[0].make_raster(t_pre=t_pre, t_post=t_post, warped=warped)
base_raster = cell_response[0].baseline.make_raster(t_pre=t_pre, t_post=t_post, warped=warped)
for r in cell_response[1:]:
raster = np.vstack((raster, r.make_raster(t_pre=t_pre, t_post=t_post, warped=warped)))
base_raster = np.vstack((base_raster, r.baseline.make_raster(t_pre=t_pre, t_post=t_post, warped=warped)))
return raster, base_raster
def get_sniff_parameters(cell_response):
nr = len(cell_response)
stim_stat = np.zeros(nr + 1, dtype=[('id', '|S32'),
('inh_min','i4'), ('inh_max', 'i4'), ('inh_median', 'i4'),
('inh_mean', 'i4'), ('inh_sd', 'i4'), ('inh_mad', 'i4'),
('exh_min','i4'), ('exh_max', 'i4'), ('exh_median', 'i4'),
('exh_mean', 'i4'), ('exh_sd', 'i4'), ('exh_mad', 'i4'),
('n','i4')
]
)
for i, cr in zip(range(nr), cell_response):
sniff = np.sort(cr.baseline.sniff_data, order=['inh_len', 't_0'])
print i
stim_stat[i]['id'] = cr.rec['meta']['id']
stim_stat[i]['n'] = sniff.shape[0]
stim_stat[i]['inh_min'] = np.nanmin(sniff['inh_len'])
stim_stat[i]['inh_max'] = np.nanmax(sniff['inh_len'])
stim_stat[i]['inh_median'] = int(np.nanmedian(sniff['inh_len']))
stim_stat[i]['inh_mean'] = int(np.nanmean(sniff['inh_len']))
stim_stat[i]['inh_sd'] = int(np.nanstd(sniff['inh_len']))
stim_stat[i]['inh_mad'] = int(stat.mad(sniff['inh_len']))
stim_stat[i]['exh_min'] = np.nanmin(sniff['exh_len'])
stim_stat[i]['exh_max'] = np.nanmax(sniff['exh_len'])
stim_stat[i]['exh_median'] = int(np.nanmedian(sniff['exh_len']))
stim_stat[i]['exh_mean'] = int(np.nanmean(sniff['exh_len']))
stim_stat[i]['exh_sd'] = int(np.nanstd(sniff['exh_len']))
stim_stat[i]['exh_mad'] = int(stat.mad(sniff['exh_len'], c=1))
stim_stat[nr]['id'] = 'all'
stim_stat[nr]['inh_min'] = np.min(stim_stat[0:-1]['inh_min'])
stim_stat[nr]['exh_min'] = np.min(stim_stat[0:-1]['exh_min'])
stim_stat[nr]['inh_max'] = np.min(stim_stat[0:-1]['inh_max'])
stim_stat[nr]['exh_max'] = np.min(stim_stat[0:-1]['exh_max'])
stim_stat[nr]['inh_median'] = int(np.mean(stim_stat[0:-1]['inh_median']))
stim_stat[nr]['exh_median'] = int(np.mean(stim_stat[0:-1]['exh_median']))
stim_stat[nr]['inh_mean'] = int(np.mean(stim_stat[0:-1]['inh_mean']))
stim_stat[nr]['exh_mean'] = int(np.mean(stim_stat[0:-1]['exh_mean']))
stim_stat[nr]['inh_sd'] = int(np.mean(stim_stat[0:-1]['inh_sd']))
stim_stat[nr]['exh_sd'] = int(np.mean(stim_stat[0:-1]['exh_sd']))
stim_stat[nr]['inh_mad'] = int(np.mean(stim_stat[0:-1]['inh_mad']))
stim_stat[nr]['exh_mad'] = int(np.mean(stim_stat[0:-1]['exh_mad']))
return stim_stat
def is_good_sniff(one_sniff, sniff_stats):
if one_sniff is None:
inh_max = sniff_stats[-1]['inh_median'] + 1.5*sniff_stats[-1]['inh_sd']
exh_max = sniff_stats[-1]['exh_median'] + 1.5*sniff_stats[-1]['exh_sd']
return inh_max, exh_max
inh_min = sniff_stats[-1]['inh_median'] - 1.5*sniff_stats[-1]['inh_sd']
inh_max = sniff_stats[-1]['inh_median'] + 1.5*sniff_stats[-1]['inh_sd']
is_good = True
if one_sniff['inh_len'] < inh_min or one_sniff['inh_len'] > inh_max:
is_good = False
else:
exh_min = sniff_stats[-1]['exh_median'] - 1.5*sniff_stats[-1]['exh_sd']
exh_max = sniff_stats[-1]['exh_median'] + 1.5*sniff_stats[-1]['exh_sd']
if one_sniff['exh_len'] < exh_min or one_sniff['exh_len'] > exh_max:
is_good = True
return is_good
cell_responses = merge_responses(stim.responses)
sniff_par = get_sniff_parameters(cell_responses['ZKawakeM72_013_010'])
set(['ZKawakeM72_013_011', 'ZKawakeM72_013_010'])
0
1
In [6]:
stim = all_odor_responses['litral']['2-hydroxy_high']
cell_responses['ZKawakeM72_013_010']
Out[6]:
[<analysis.stimulus.Response instance at 0x7fb8e9cfa200>,
<analysis.stimulus.Response instance at 0x7fb8e9cfa4d0>]
In [392]:
print sniff_par['inh_median']
print sniff_par['exh_median']
[179 148 163]
[347 325 336]
In [463]:
print sniff[2500]['inh_len']
print sniff[2500]['exh_len']
is_good_sniff(sniff[2500], sniff_par)
214
391
59.5
266.5
129.0
543.0
391
Out[463]:
True
In [457]:
sniff_par[-1]['exh_sd']
Out[457]:
138
In [401]:
sniff = np.sort(cr.baseline.sniff_data, order=['inh_len', 't_0'])
print np.mean(sniff['inh_len'])
stat.mad(sniff['inh_len'])
125.237698713
Out[401]:
219.4251283388291
In [281]:
rast3, base3 = make_raster(cell_responses['ZKawakeM72_013_010'])
plot_raster(rast3)
plot_raster(rast3, bin_size=10)
plot_raster(base3)
plot_raster(base3, bin_size=10)
Out[281]:
([<matplotlib.lines.Line2D at 0x7fa52459bf90>],
<matplotlib.axes._axes.Axes at 0x7fa52b012f10>)
In [278]:
r2 = cell_responses['ZKawakeM72_013_010'][0]
r2.baseline.make_raster()
Out[278]:
array([[ 0., 0., 0., ..., 0., 0., 0.],
[ 0., 0., 0., ..., 0., 0., 0.],
[ 0., 0., 0., ..., 0., 0., 0.],
...,
[ 0., 0., 0., ..., 0., 0., 0.],
[ 0., 0., 0., ..., 0., 0., 0.],
[ 0., 0., 0., ..., 1., 0., 0.]])
In [319]:
for i, cr in zip(range(2), stim.responses.itervalues()):
print i
print cr.rec['meta']['id']
0
KPawakeM72_817_f_001
1
ZKawakeM72_006_a_001
In [310]:
sniff = np.sort(cr.baseline.sniff_data, order=['inh_len', 't_0'])
int(np.nanstd(sniff['inh_len']))
Out[310]:
71
In [308]:
stim_stat = np.zeros(2, dtype=[('rec', '|S32'), ('x', 'i4')])
stim_stat['x']
Out[308]:
array([0, 0], dtype=int32)
In [317]:
stim.responses
Out[317]:
{'KPawakeM72_014_b_012': <analysis.stimulus.Response instance at 0x7fa50048fb48>,
'KPawakeM72_016_a_016': <analysis.stimulus.Response instance at 0x7fa530b43830>,
'KPawakeM72_016_a_018': <analysis.stimulus.Response instance at 0x7fa530b43758>,
'KPawakeM72_019_b_002': <analysis.stimulus.Response instance at 0x7fa530b43488>,
'KPawakeM72_019_d_002': <analysis.stimulus.Response instance at 0x7fa4fe3ae2d8>,
'KPawakeM72_021_a_001': <analysis.stimulus.Response instance at 0x7fa50048f5a8>,
'KPawakeM72_021_b_001': <analysis.stimulus.Response instance at 0x7fa530b43560>,
'KPawakeM72_023_a_005': <analysis.stimulus.Response instance at 0x7fa4f9abfe60>,
'KPawakeM72_024_a_001': <analysis.stimulus.Response instance at 0x7fa530b43320>,
'KPawakeM72_024_b_002': <analysis.stimulus.Response instance at 0x7fa50048f368>,
'KPawakeM72_817_f_001': <analysis.stimulus.Response instance at 0x7fa530b43f38>,
'ZKawakeM72_004_h_001': <analysis.stimulus.Response instance at 0x7fa535025878>,
'ZKawakeM72_004_h_002': <analysis.stimulus.Response instance at 0x7fa5350253b0>,
'ZKawakeM72_004_i_001': <analysis.stimulus.Response instance at 0x7fa535fa93b0>,
'ZKawakeM72_004_i_002': <analysis.stimulus.Response instance at 0x7fa535fa9e60>,
'ZKawakeM72_005_a_001': <analysis.stimulus.Response instance at 0x7fa530b43b00>,
'ZKawakeM72_006_a_001': <analysis.stimulus.Response instance at 0x7fa530b43a28>,
'ZKawakeM72_010_b_001': <analysis.stimulus.Response instance at 0x7fa535025a70>,
'ZKawakeM72_011_d_001': <analysis.stimulus.Response instance at 0x7fa50048f998>,
'ZKawakeM72_012_a_001': <analysis.stimulus.Response instance at 0x7fa530b43128>,
'ZKawakeM72_012_a_002': <analysis.stimulus.Response instance at 0x7fa50048f098>,
'ZKawakeM72_013_e_010': <analysis.stimulus.Response instance at 0x7fa535fa9638>,
'ZKawakeM72_013_e_011': <analysis.stimulus.Response instance at 0x7fa535fa9cb0>,
'ZKawakeM72_013_f_010': <analysis.stimulus.Response instance at 0x7fa535fa9710>,
'ZKawakeM72_015_d_001': <analysis.stimulus.Response instance at 0x7fa535fa9a70>,
'ZKawakeM72_020_c_001': <analysis.stimulus.Response instance at 0x7fa535025200>,
'ZKawakeM72_020_d_001': <analysis.stimulus.Response instance at 0x7fa4fe3aec68>,
'ZKawakeM72_020_e_001': <analysis.stimulus.Response instance at 0x7fa535fa9e18>,
'ZKawakeM72_020_g_001': <analysis.stimulus.Response instance at 0x7fa4fe3ae248>,
'ZKawakeM72_022_d_001': <analysis.stimulus.Response instance at 0x7fa50048fbd8>,
'ZKawakeM72_027_e_004': <analysis.stimulus.Response instance at 0x7fa535fa99e0>}
In [468]:
a=[]
len(a)==0
Out[468]:
True
In [475]:
aux_sniff = np.zeros(1, dtype=[('inh_len', 'i4'), ('exh_len', 'i4')])
In [477]:
aux_sniff[0]['inh_len']
Out[477]:
0
In [ ]:
Content source: zekearneodo/ephys-tools
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