def spawn_pandas(port=5005, freq_max=101):
tex_size = (1024, 1024)
freqs = np.arange(freq_max)
input_textures = {
'freq': {},
'blank': textures.BlankTexXY(texture_size=tex_size)
}
for f in freqs:
input_textures['freq'][f] = textures.GratingGrayTexXY(
texture_size=tex_size, spatial_frequency=f)
stimulation = stimuli.ClosedLoopStimChoice(textures=input_textures,
gui=True)
sub = utils.Subscriber(topic="stim", port=port)
monitor = utils.MonitorDataPass(sub)
stimulation.run()
duration = 7
stat_time = 18
df.loc[:, 'stationary_time'] = stat_time
df.loc[:, 'duration'] = duration
return df
svepath = 'temp1.txt'
tex_size = (1024, 1024)
freqs = np.arange(101)
input_textures = {'freq': {}, 'blank': textures.BlankTexXY(texture_size=tex_size)}
for f in freqs:
input_textures['freq'][f] = textures.GratingGrayTexXY(texture_size=tex_size, spatial_frequency=f)
def stims(port="5005"):
stimulation = stimuli.ClosedLoopStimChoice(textures=input_textures, save_path=svepath)
sub = utils.Subscriber(topic="stim", port=port)
monitor = utils.MonitorDataPass(sub)
stimulation.run()
if __name__ == '__main__':
port1 = utils.port_provider()
stims_proc = mp.Process(target=stims, args=(port1,))
sequencer = mp.Process(target=utils.sequence_runner, args=(create_prot(), port1))
from pandastim import stimuli, textures
import pandas as pd
save_path = None
# df = pd.read_hdf(r'C:\Soft_Kitty\Anaconda3\envs\clean_pstim\Lib\site-packages\pandastim\experiments\imaging.hdf')
df = pd.read_hdf(r'D:\autumnal_luzps_no_tex.hdf')
df = df.loc[1:]
df.loc[:, 'texture_0'] = textures.GratingGrayTexXY(texture_size=(1024, 1024),
spatial_frequency=60)
df.loc[:, 'texture_1'] = textures.GratingGrayTexXY(texture_size=(1024, 1024),
spatial_frequency=60)
df.loc[:, 'stationary_time'] = df.stat_time.values
# df.loc[:, 'duration'] = df.duration.values + df.stationary_time.values
df = pd.concat([df] * 10)
df.reset_index(inplace=True)
stims = stimuli.OpenLoopStimulus(df)
stims.run()
from pandastim import textures, stimuli
# this loads in your default parameters
p = r'C:\Users\matt_analysis\Documents\def_pstim_params.txt'
with open(p) as json_file:
pstim_params = json.load(json_file)
# make a cute little stim dict
t_size = (512, 512)
fwd = {
'stim_type': 's',
'velocity': 0.02,
'angle': 0,
'stationary_time': 1,
'duration': 3,
'texture': textures.GratingGrayTexXY(texture_size=t_size,
spatial_frequency=20)
}
right = {
'stim_type':
'b',
'velocity': [0.02, -0.02],
'angle': [90, 25],
'duration': [5, 2],
'texture': [
textures.GratingGrayTexXY(texture_size=t_size, spatial_frequency=20),
textures.GratingGrayTexXY(texture_size=t_size, spatial_frequency=20)
]
}
left = {
'stim_type': 's',
'velocity': 0.02,