import numpy as np
import scipy
from thllib import util
import scipy.signal
import sys
FLYNUM = int(sys.argv[1])# tested with 1393
RESAMPLE_RATE = 2000 #hz
TAU_ON = 0.01595905
TAU_OFF = 0.23594343
KERNEL_GAIN = 0.4
SNR = 1.0
DEFALULT_ISI = 0.005 #s
MAX_ISI_TIME = 0.02
fly = flb.NetFly(FLYNUM,rootpath='/media/imager/FlyDataD/FlyDB/')
fly.open_signals()
def condition_signal(sig_name,signal):
"""do some data cleaning on the signals.
For instnace the transients from b2 are week
so I need to detrend in order to remove the
contaminating baseline"""
if sig_name == 'b2':
return signal - scipy.signal.medfilt(signal,501)
if sig_name == 'iii1':
return signal - scipy.signal.medfilt(signal,501)
if sig_name == 'hg1':
return signal - scipy.signal.medfilt(signal,501)
return signal
import sys
import os
import numpy as np
from matplotlib import pyplot as plt
import neo
from neo import AxonIO
from cv_bridge import CvBridge, CvBridgeError
from thllib import flylib as flb
import rosbag
fly = flb.NetFly(1525)
abfreader = AxonIO(fly.abfpaths[0])
abffile = abfreader.read()
block = abffile[0]
segment = block.segments[0]
analogsignals = segment.analogsignals
times = np.array(analogsignals[0].times)
signal_idxs = {
'abf_electrode': 0,
'abf_wba_left_amp': 1,
'abf_wba_right_amp': 2,
'abf_sync': 3,
'abf_freq': 4,
'abf_left_hutchen': 5,
'abf_right_hutchen': 6,
'abf_led_pulse': 7,
'abf_kinefly_lmr': 8,
'abf_kinefly_left': 9,
'abf_kinefly_right': 10,
import sys
from matplotlib import pyplot as plt
from scipy import ndimage
#%matplotlib inline
#from matplotlib import pyplot as plt
flynum = int(sys.argv[1]) #1351
samp_range = 5000 # search over this range to find center point of image
search_bound = 50 # window to search for center of fly in pxls
crop = 100 #crop fly around this window
img_thresh = 240 #threshold to find the center of rotation of the fly.
cent_fun = np.mean #function to use when looking for the image center
fly = flylib.NetFly(flynum)
bag_file_name = fly.flypath + '/' + [
bf for bf in os.listdir(fly.flypath) if '.bag' in bf
][0]
inbag = rosbag.Bag(bag_file_name)
topics = inbag.get_type_and_topic_info()[1].keys()
if os.path.exists(fly.flypath + '/' + 'images.hdf5'):
os.remove(fly.flypath + '/' + 'images.hdf5')
if os.path.exists(fly.flypath + '/' + 'times.hdf5'):
os.remove(fly.flypath + '/' + 'times.hdf5')
if os.path.exists(fly.flypath + '/' + 'avepxl.hdf5'):
os.remove(fly.flypath + '/' + 'avepxl.hdf5')
images = h5py.File(fly.flypath + '/' + 'images.hdf5')
times = h5py.File(fly.flypath + '/' + 'times.hdf5')
#! /usr/bin/python2
from matplotlib import animation
import numpy as np
from matplotlib import pyplot as plt
from thllib import flylib as flb
import figurefirst as fifi
import sys
reload(fifi)
flynum = int(sys.argv[1]) #1344
fly = flb.NetFly(flynum)
fly.open_signals(['hdf5', 'txt'])
position = fly.position
velocity = fly.velocity
### make the condition blocks
#blocks = fly.order
#block_times = list()
#t = 0
#for b in blocks:
# block_times.append(t)
# if b == 'flicker_static\n':
# t+=10
# else:
# t+=30
### function to return the correct condition for a given time
def get_cond(t, blocks, block_times):
return np.array(blocks)[np.argwhere(