def __init__(self, fmf_dir, savedir, fly_id, plot_overlays=False):
if (savedir[-1] == '/'):
savedir = savedir[:-1]
if not os.path.exists(savedir + '/temp_png'):
os.makedirs(savedir + '/temp_png')
self._savedir = savedir
if (fmf_dir[-1] == '/'):
self._fmf_dir = fmf_dir[:-1]
else:
self._fmf_dir = fmf_dir
self._zoomfmf = FMF.FlyMovie(self._fmf_dir)
self._plot_overlays = plot_overlays
self._expdir = fmf_dir.rsplit('/', 2)[0]
self._bag = utilities.match_fmf_and_bag(self._fmf_dir,
(self._expdir + '/BAGS'))
#self._wide = utilities.match_wide_to_zoom(self._fmf_dir, (self._expdir + '/'))
self._handle, __, ___ = utilities.parse_fmftime(self._fmf_dir)
self._data, self._Tzero = self.get_data()
self._image_height, self._image_width = self._zoomfmf.get_frame(
0)[0].shape
def sync_jaaba_with_ros(FMF_DIR, BAGS, JAABA):
print "Processing: ", FMF_DIR
JAABA_CSV = FMF_DIR + '/registered_trx.csv'
FLY_ID, FMF_TIME, GROUP = parse_fmftime(FMF_DIR)
BAG_FILE = utilities.match_fmf_and_bag(FMF_DIR, BAGS)
WIDE_FMF = utilities.match_wide_to_zoom(FMF_DIR, JAABA)
jaaba_data = pd.read_csv(JAABA_CSV, sep=',', names=['Timestamp','Length','Width','Theta','Left','Right'], index_col=False)
jaaba_data[['Length','Width','Left','Right']] = jaaba_data[['Length','Width','Left','Right']].astype(np.float64)
jaaba_data = utilities.convert_timestamps(jaaba_data)
# ALIGN LASER STATE DATA
jaaba_data['Laser1_state'] = binarize_laser_data(BAG_FILE, 'laser1')['Laser_state'].asof(jaaba_data.index).fillna(value=0) #YAY!
jaaba_data['Laser2_state'] = binarize_laser_data(BAG_FILE, 'laser2')['Laser_state'].asof(jaaba_data.index).fillna(value=0)
# COMPUTE AND ALIGN DISTANCE TO NEAREST TARGET
targets = target_detector.TargetDetector(WIDE_FMF, FMF_DIR)
targets.plot_targets_on_background()
jaaba_data['dtarget'] = targets.get_dist_to_nearest_target(BAG_FILE)['dtarget'].asof(jaaba_data.index).fillna(value=0)
jaaba_data['Timestamp'] = jaaba_data.index #silly pandas bug for subtracting from datetimeindex...
jaaba_data['synced_time'] = jaaba_data['Timestamp'] - jaaba_data['Timestamp'][jaaba_data[jaaba_data['Laser2_state'] > 0].index[0]]
jaaba_data['maxWingAngle'] = get_absmax(jaaba_data[['Left','Right']])
return jaaba_data
def __init__(self, fmf_dir, savedir, fly_id, plot_overlays=False):
if (savedir[-1] == '/' ):
savedir = savedir[:-1]
if not os.path.exists(savedir + '/temp_png'):
os.makedirs(savedir + '/temp_png')
self._savedir = savedir
if (fmf_dir[-1] == '/'):
self._fmf_dir = fmf_dir[:-1]
else:
self._fmf_dir = fmf_dir
self._zoomfmf = FMF.FlyMovie(self._fmf_dir)
self._plot_overlays = plot_overlays
self._expdir = fmf_dir.rsplit('/', 2)[0]
self._bag = utilities.match_fmf_and_bag(self._fmf_dir, (self._expdir + '/BAGS'))
#self._wide = utilities.match_wide_to_zoom(self._fmf_dir, (self._expdir + '/'))
self._handle, __, ___ = utilities.parse_fmftime(self._fmf_dir)
self._data, self._Tzero = self.get_data()
self._image_height, self._image_width = self._zoomfmf.get_frame(0)[0].shape
def get_stims_from_bag(self, FMF_DIR, BAGS, EXPDIR):
print "Processing: ", FMF_DIR
#JAABA_CSV = FMF_DIR + '/registered_trx.csv'
FLY_ID, FMF_TIME, GROUP = utilities.parse_fmftime(FMF_DIR)
BAG_FILE = utilities.match_fmf_and_bag(FMF_DIR, BAGS)
WIDE_FMF = utilities.match_wide_to_zoom(FMF_DIR, EXPDIR)
#jaaba_data = pd.read_csv(JAABA_CSV, sep=',', names=['Timestamp','Length','Width','Theta','Left','Right'], index_col=False)
#jaaba_data[['Length','Width','Left','Right']] = jaaba_data[['Length','Width','Left','Right']].astype(np.float64)
# ALIGN LASER STATE DATA
jaaba_data = DataFrame(index=self._zoomfmf.get_all_timestamps())
jaaba_data['Timestamp'] = self._zoomfmf.get_all_timestamps()
jaaba_data = utilities.convert_timestamps(jaaba_data)
jaaba_data['Laser1_state'] = utilities.binarize_laser_data(
BAG_FILE, 2).resample('10ms', how='max')['Laser_state'].asof(
jaaba_data.index).fillna(value=0) #YAY!
jaaba_data['Laser2_state'] = utilities.binarize_laser_data(
BAG_FILE, 4).resample('10ms', how='max')['Laser_state'].asof(
jaaba_data.index).fillna(value=0)
"""
# COMPUTE AND ALIGN DISTANCE TO NEAREST TARGET
targets = target_detector.TargetDetector(WIDE_FMF, FMF_DIR)
targets.plot_targets_on_background()
jaaba_data['dtarget'] = targets.get_dist_to_nearest_target(BAG_FILE)['dtarget'].asof(jaaba_data.index).fillna(value=0)
"""
jaaba_data[
'Timestamp'] = jaaba_data.index #silly pandas bug for subtracting from datetimeindex...
try:
jaaba_data['synced_time'] = jaaba_data[
'Timestamp'] - jaaba_data.Timestamp[
(jaaba_data.Laser2_state +
jaaba_data.Laser1_state) > 0].index[0]
except:
print "WARNING: Cannot synchronize by stimulus. Setting T0 to frame0. "
jaaba_data['synced_time'] = jaaba_data[
'Timestamp'] - jaaba_data.Timestamp.index[0]
"""
#DISCARD BOGUS WING ANGLE VALUES:
jaaba_data['Left'][jaaba_data['Left'] < -2.09 ]= np.nan #2.09 for 120degrees
jaaba_data['Right'][jaaba_data['Right'] > 2.09] = np.nan
jaaba_data['maxWingAngle'] = jaaba_data[['Left','Right']].abs().max(axis=1)
"""
return jaaba_data
def sync_jaaba_with_ros(FMF_DIR, BAGS, JAABA):
print "Processing: ", FMF_DIR
JAABA_CSV = FMF_DIR + '/registered_trx.csv'
FLY_ID, FMF_TIME, GROUP = parse_fmftime(FMF_DIR)
BAG_FILE = utilities.match_fmf_and_bag(FMF_DIR, BAGS)
WIDE_FMF = utilities.match_wide_to_zoom(FMF_DIR, JAABA)
jaaba_data = pd.read_csv(
JAABA_CSV,
sep=',',
names=['Timestamp', 'Length', 'Width', 'Theta', 'Left', 'Right'],
index_col=False)
jaaba_data[['Length', 'Width', 'Left',
'Right']] = jaaba_data[['Length', 'Width', 'Left',
'Right']].astype(np.float64)
jaaba_data = utilities.convert_timestamps(jaaba_data)
# ALIGN LASER STATE DATA
jaaba_data['Laser1_state'] = binarize_laser_data(
BAG_FILE,
'laser1')['Laser_state'].asof(jaaba_data.index).fillna(value=0) #YAY!
jaaba_data['Laser2_state'] = binarize_laser_data(
BAG_FILE,
'laser2')['Laser_state'].asof(jaaba_data.index).fillna(value=0)
# COMPUTE AND ALIGN DISTANCE TO NEAREST TARGET
targets = target_detector.TargetDetector(WIDE_FMF, FMF_DIR)
targets.plot_targets_on_background()
print targets.get_targets()
jaaba_data['dtarget'] = targets.get_dist_to_nearest_target(
BAG_FILE)['dtarget'].asof(jaaba_data.index).fillna(value=0)
jaaba_data[
'Timestamp'] = jaaba_data.index #silly pandas bug for subtracting from datetimeindex...
jaaba_data['synced_time'] = jaaba_data['Timestamp'] - jaaba_data[
'Timestamp'][jaaba_data[jaaba_data['Laser2_state'] > 0].index[0]]
#DISCARD BOGUS WING ANGLE VALUES:
jaaba_data['Left'][
jaaba_data['Left'] < -2.3] = np.nan #2.09 for 120degrees
jaaba_data['Right'][jaaba_data['Right'] > 2.3] = np.nan
jaaba_data['maxWingAngle'] = get_absmax(jaaba_data[['Left', 'Right']])
return jaaba_data
def __init__(self, fmf_dir, savedir, fly_id, plot_overlays=False):
if (savedir[-1] == '/'):
savedir = savedir[:-1]
if not os.path.exists(savedir + '/temp_png'):
os.makedirs(savedir + '/temp_png')
self._savedir = savedir
if (fmf_dir[-1] == '/'):
self._fmf_dir = fmf_dir[:-1]
else:
self._fmf_dir = fmf_dir
self._plot_overlays = plot_overlays
self._expdir = fmf_dir.rsplit('/', 1)[0]
self._bag = utilities.match_fmf_and_bag(self._fmf_dir,
(self._expdir + '/BAGS'))
self._wide = utilities.match_wide_to_zoom(self._fmf_dir,
(self._expdir + '/'))
self._widefmf = FMF.FlyMovie(self._wide)
self._handle, __, ___ = utilities.parse_fmftime(self._fmf_dir)
self._zoomfmf, self._data, self._Tzero = self.get_data()
if self._data.Laser0_state.mean(
) >= 0.5: #SOME EXPERIMENTS ARE DONE WITH lASER0 OFF.
if self._data.Laser0_state.mean(
) <= 0.99: #SOME BAGFILES HAVE A FEW MSGS BEFORE LASER CONFIG
self.ILLUMINATED_WITH_LASER0 = 1
else:
self.ILLUMINATED_WITH_LASER0 = 0
else:
self.ILLUMINATED_WITH_LASER0 = 0
self._image_height, self._image_width = self._zoomfmf.get_frame(
0)[0].shape
def get_stims_from_bag(self, FMF_DIR, BAGS, EXPDIR):
print "Processing: ", FMF_DIR
#JAABA_CSV = FMF_DIR + '/registered_trx.csv'
FLY_ID, FMF_TIME, GROUP = utilities.parse_fmftime(FMF_DIR)
BAG_FILE = utilities.match_fmf_and_bag(FMF_DIR, BAGS)
WIDE_FMF = utilities.match_wide_to_zoom(FMF_DIR, EXPDIR)
#jaaba_data = pd.read_csv(JAABA_CSV, sep=',', names=['Timestamp','Length','Width','Theta','Left','Right'], index_col=False)
#jaaba_data[['Length','Width','Left','Right']] = jaaba_data[['Length','Width','Left','Right']].astype(np.float64)
# ALIGN LASER STATE DATA
jaaba_data = DataFrame(index=self._zoomfmf.get_all_timestamps())
jaaba_data['Timestamp'] = self._zoomfmf.get_all_timestamps()
jaaba_data = utilities.convert_timestamps(jaaba_data)
jaaba_data['Laser1_state'] = utilities.binarize_laser_data(BAG_FILE, 2).resample('10ms', how='max')['Laser_state'].asof(jaaba_data.index).fillna(value=0) #YAY!
jaaba_data['Laser2_state'] = utilities.binarize_laser_data(BAG_FILE, 4).resample('10ms', how='max')['Laser_state'].asof(jaaba_data.index).fillna(value=0)
"""
# COMPUTE AND ALIGN DISTANCE TO NEAREST TARGET
targets = target_detector.TargetDetector(WIDE_FMF, FMF_DIR)
targets.plot_targets_on_background()
jaaba_data['dtarget'] = targets.get_dist_to_nearest_target(BAG_FILE)['dtarget'].asof(jaaba_data.index).fillna(value=0)
"""
jaaba_data['Timestamp'] = jaaba_data.index #silly pandas bug for subtracting from datetimeindex...
try:
jaaba_data['synced_time'] = jaaba_data['Timestamp'] - jaaba_data.Timestamp[(jaaba_data.Laser2_state + jaaba_data.Laser1_state) > 0].index[0]
except:
print "WARNING: Cannot synchronize by stimulus. Setting T0 to frame0. "
jaaba_data['synced_time'] = jaaba_data['Timestamp'] - jaaba_data.Timestamp.index[0]
"""
#DISCARD BOGUS WING ANGLE VALUES:
jaaba_data['Left'][jaaba_data['Left'] < -2.09 ]= np.nan #2.09 for 120degrees
jaaba_data['Right'][jaaba_data['Right'] > 2.09] = np.nan
jaaba_data['maxWingAngle'] = jaaba_data[['Left','Right']].abs().max(axis=1)
"""
return jaaba_data
def sync_jaaba_with_ros(self, FMF_DIR, BAGS, JAABA):
print "Processing: ", FMF_DIR
JAABA_CSV = FMF_DIR + '/registered_trx.csv'
FLY_ID, FMF_TIME, GROUP = utilities.parse_fmftime(FMF_DIR)
BAG_FILE = utilities.match_fmf_and_bag(FMF_DIR, BAGS)
WIDE_FMF = utilities.match_wide_to_zoom(FMF_DIR, JAABA)
jaaba_data = pd.read_csv(
JAABA_CSV,
sep=',',
names=['Timestamp', 'Length', 'Width', 'Theta', 'Left', 'Right'],
index_col=False)
jaaba_data[['Length', 'Width', 'Left', 'Right'
]] = jaaba_data[['Length', 'Width', 'Left',
'Right']].astype(np.float64)
jaaba_data = utilities.convert_timestamps(jaaba_data)
# ALIGN LASER STATE DATA
laser_states = utilities.get_laser_states(BAG_FILE)
try:
jaaba_data['Laser0_state'] = laser_states['Laser0_state'].asof(
jaaba_data.index).fillna(value=0)
jaaba_data['Laser1_state'] = laser_states['Laser1_state'].asof(
jaaba_data.index).fillna(value=0) #YAY!
jaaba_data['Laser2_state'] = laser_states['Laser2_state'].asof(
jaaba_data.index).fillna(value=0)
except:
print "\t ERROR: problem interpreting laser current values."
jaaba_data['Laser0_state'] = 0
jaaba_data['Laser2_state'] = 0
jaaba_data['Laser1_state'] = 0
# COMPUTE AND ALIGN DISTANCE TO NEAREST TARGET
targets = target_detector.TargetDetector(WIDE_FMF, FMF_DIR)
targets.plot_targets_on_background()
jaaba_data['dtarget'] = targets.get_dist_to_nearest_target(
BAG_FILE)['dtarget'].asof(jaaba_data.index).fillna(value=0)
jaaba_data[
'Timestamp'] = jaaba_data.index #silly pandas bug for subtracting from datetimeindex...
try:
jaaba_data['synced_time'] = jaaba_data[
'Timestamp'] - jaaba_data.Timestamp[
(jaaba_data.Laser2_state +
jaaba_data.Laser1_state) > 0].index[0]
except:
print "WARNING: Cannot synchronize by stimulus. Setting T0 to frame0. "
jaaba_data['synced_time'] = jaaba_data[
'Timestamp'] - jaaba_data.Timestamp.index[0]
#DISCARD BOGUS WING ANGLE VALUES:
jaaba_data['Left'][
jaaba_data['Left'] < -2.09] = np.nan #2.09 for 120degrees
jaaba_data['Right'][jaaba_data['Right'] > 2.09] = np.nan
jaaba_data['maxWingAngle'] = jaaba_data[['Left',
'Right']].abs().max(axis=1)
return jaaba_data
import flymad_jaaba.utilities as utilities import flymad_jaaba.target_detector as target_detector import matplotlib.pyplot as plt fmf_file = '/media/DBATH_5/150107/DB201-GP-costim_wide_20150107_174101.fmf' bagdir = '/media/DBATH_5/150107/BAGS' tempdir = '/groups/dickson/home/bathd/Desktop/150119' bag_file = utilities.match_fmf_and_bag(fmf_file, bagdir) targs = target_detector.TargetDetector(fmf_file, tempdir) targs.plot_trajectory_on_background(bag_file) positions = utilities.get_positions_from_bag(bag_file) distances = targs.get_dist_to_nearest_target(bag_file) plt.plot(distances) plt.show() plt.plot(positions.fly_x, positions.fly_y)#, alpha=distances.values) plt.show()
