Python perform_analysis_and_visualization 예제들

예제 #1

                    data_store)
            if withPGN and withFeedback_CxPGN:
                model.connectors['V1EffConnectionPGN'].store_connections(
                    data_store)

    data_store.save()
# or only load pickled data
else:
    setup_logging()
    data_store = PickledDataStore(load=True,
                                  parameters=ParameterSet({
                                      'root_directory':
                                      'ThalamoCorticalModel_data_____',
                                      'store_stimuli':
                                      False
                                  }),
                                  replace=True)
    logger.info('Loaded data store')
    data_store.save()

# Analysis and Plotting
if mpi_comm.rank == MPI_ROOT:
    # perform_analysis_test( data_store )
    # perform_analysis_and_visualization( data_store, 'luminance', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'contrast', withPGN, withV1 )
    perform_analysis_and_visualization(data_store, 'spatial_frequency',
                                       withPGN, withV1)
    # perform_analysis_and_visualization( data_store, 'temporal_frequency', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'size', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'orientation', withPGN, withV1 )

예제 #2

파일: run_analysis_lum.py 프로젝트: antolikjan/mozaik-contrib

# -*- coding: utf-8 -*-
"""
"""
import matplotlib
matplotlib.use('Agg')
import sys
from mozaik.controller import setup_logging
import mozaik
from mozaik.storage.datastore import Hdf5DataStore,PickledDataStore
from analysis_and_visualization import perform_analysis_and_visualization
from parameters import ParameterSet

from mozaik.controller import Global
Global.root_directory = sys.argv[1]+'/'

setup_logging()
data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':sys.argv[1],'store_stimuli' : False}),replace=True)
perform_analysis_and_visualization(data_store,gratings=False,cort_stim=True,nat_stim=False,tp=1,scale=True)

예제 #3

파일: run.py 프로젝트: JoelChavas/mozaik-contrib

try:
    from mpi4py import MPI
except ImportError:
    MPI = None
if MPI:
    mpi_comm = MPI.COMM_WORLD
MPI_ROOT = 0

logger = mozaik.getMozaikLogger()

if True:
    data_store,model = run_workflow('FFI',PushPullCCModel,create_experiments)
    model.connectors['V1L4ExcL4ExcConnection'].store_connections(data_store)    
    model.connectors['V1L4ExcL4InhConnection'].store_connections(data_store)    
    model.connectors['V1L4InhL4ExcConnection'].store_connections(data_store)    
    model.connectors['V1L4InhL4InhConnection'].store_connections(data_store)    
    model.connectors['V1AffConnectionOn'].store_connections(data_store)    
    model.connectors['V1AffConnectionOff'].store_connections(data_store)    
    model.connectors['V1AffInhConnectionOn'].store_connections(data_store)    
    model.connectors['V1AffInhConnectionOff'].store_connections(data_store)    
    data_store.save()
    
else: 
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'FFI_test_____', 'store_stimuli' : False}),replace=True)
    logger.info('Loaded data store')
    data_store.save()

if mpi_comm.rank == MPI_ROOT:
    perform_analysis_and_visualization(data_store)

예제 #4

파일: run_spontaneous.py 프로젝트: dguarino/T2

            # model.connectors['V1L4InhL4ExcConnection'].store_connections(data_store)    
            # model.connectors['V1L4InhL4InhConnection'].store_connections(data_store)    
            # model.connectors['V1L4ExcL4ExcConnectionRand'].store_connections(data_store)    
            # model.connectors['V1L4ExcL4InhConnectionRand'].store_connections(data_store)    
            # model.connectors['V1L4InhL4ExcConnectionRand'].store_connections(data_store)    
            # model.connectors['V1L4InhL4InhConnectionRand'].store_connections(data_store)
            if withFeedback_CxLGN:
                model.connectors['V1EffConnectionOn'].store_connections(data_store)    
                model.connectors['V1EffConnectionOff'].store_connections(data_store)    
            if withPGN and withFeedback_CxPGN:
                model.connectors['V1EffConnectionPGN'].store_connections(data_store)    

    data_store.save()
# or only load pickled data
else:
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'ThalamoCorticalModel_data_spontaneous_____', 'store_stimuli' : False}),replace=True)
    logger.info('Loaded data store')
    data_store.save()

# Analysis and Plotting
if mpi_comm.rank == MPI_ROOT:
    # perform_analysis_test( data_store )
    perform_analysis_and_visualization( data_store, 'subcortical_conn', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'luminance', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'contrast', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'spatial_frequency', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'temporal_frequency', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'size', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'orientation', withPGN, withV1 )

예제 #5

파일: run_temporal_V1.py 프로젝트: dguarino/T2

            model.connectors['V1AffInhConnectionOn'].store_connections(data_store)    
            model.connectors['V1AffInhConnectionOff'].store_connections(data_store)    
            model.connectors['V1L4ExcL4ExcConnection'].store_connections(data_store)    
            model.connectors['V1L4ExcL4InhConnection'].store_connections(data_store)    
            model.connectors['V1L4InhL4ExcConnection'].store_connections(data_store)    
            model.connectors['V1L4InhL4InhConnection'].store_connections(data_store)    
            model.connectors['V1L4ExcL4ExcConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4ExcL4InhConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4InhL4ExcConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4InhL4InhConnectionRand'].store_connections(data_store)
            if withFeedback_CxLGN:
                model.connectors['V1EffConnectionOn'].store_connections(data_store)    
                model.connectors['V1EffConnectionOff'].store_connections(data_store)    
            if withPGN and withFeedback_CxPGN:
                model.connectors['V1EffConnectionPGN'].store_connections(data_store)    

    data_store.save()
# or only load pickled data
else:
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'ThalamoCorticalModel_data_temporal_V1_____', 'store_stimuli' : False}),replace=True)
    logger.info('Loaded data store')
    data_store.save()

# Analysis and Plotting
if mpi_comm.rank == MPI_ROOT:
    # perform_analysis_and_visualization( data_store, 'luminance', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'contrast', withPGN, withV1 )
    # perform_analysis_and_visualization( data_store, 'spatial_frequency', withPGN, withV1 )
    perform_analysis_and_visualization( data_store, 'temporal_frequency', withPGN, withV1 )

예제 #6

파일: run_old.py 프로젝트: apdavison/mozaik-contrib

# -*- coding: utf-8 -*-
"""

"""
import matplotlib
matplotlib.use('Agg')
from mpi4py import MPI 
from pyNN import nest
import sys
import mozaik.controller
from mozaik.controller import run_workflow, setup_logging
import mozaik
from experiments import create_experiments,create_experiments_bar,create_experiments_short,create_experiments_old,create_experiments_old_short
from model import SelfSustainedPushPull
from mozaik.storage.datastore import Hdf5DataStore,PickledDataStore
from analysis_and_visualization import perform_analysis_and_visualization
from parameters import ParameterSet


mpi_comm = MPI.COMM_WORLD

data_store,model = run_workflow('MorganTaylorModel',SelfSustainedPushPull,create_experiments_old)
data_store.save() 

if mpi_comm.rank == 0:
   print "Starting visualization" 
   perform_analysis_and_visualization(data_store,gratings=True,bars=False,nat_movies=True)

예제 #7

"""
import matplotlib
matplotlib.use('Agg')
from mpi4py import MPI 
from pyNN import nest
import sys
import mozaik.controller
from mozaik.controller import run_workflow, setup_logging
import mozaik
from experiments import create_experiments,create_experiments_bar,create_experiments_short,create_experiments_old
from model import SelfSustainedPushPull
from mozaik.storage.datastore import Hdf5DataStore,PickledDataStore
from analysis_and_visualization import perform_analysis_and_visualization
from parameters import ParameterSet


mpi_comm = MPI.COMM_WORLD

if True:
    data_store,model = run_workflow('MorganTaylorModel',SelfSustainedPushPull,create_experiments)
    data_store.save() 
else: 
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'MorganTaylorModel_visual_space_update=1ms_RF_resolution=1ms','store_stimuli' : False}),replace=True)

if mpi_comm.rank == 0:
   print "Starting visualization" 
   perform_analysis_and_visualization(data_store,gratings=True,bars=True)
#   data_store.save() 

예제 #8

파일: run_analysis_and_visualization.py 프로젝트: dguarino/T2

from analysis_and_visualization import perform_analysis_and_visualization_radius
from parameters import ParameterSet

from mozaik.controller import Global
Global.root_directory = sys.argv[1]+'/'


withPGN = True  # 
withV1 = True  # False for open-loop


setup_logging()
data_store = PickledDataStore(load=True, parameters=ParameterSet({'root_directory':sys.argv[1],'store_stimuli' : False}),replace=True)

# perform_analysis_and_visualization( data_store, 'spatial_frequency', withPGN, withV1 )
perform_analysis_and_visualization( data_store, 'size', withPGN, withV1 )

# # Simple Analysis (just one group)
# perform_analysis_and_visualization( data_store, 'cortical_map', withPGN, withV1 )
# perform_analysis_and_visualization_radius( data_store, 'size_radius', [[.0],[.0],[.0]], [.0,.5], withPGN, withV1 )
# perform_analysis_and_visualization_radius( data_store, 'size_radius', [[1.6],[.0],[.0]], [.0,.5], withPGN, withV1 )

# # Several Grouping Analysis
# import numpy
# step = .2
# for i in numpy.arange(step, 1.+step, step):
#     print i
#     perform_analysis_and_visualization_radius( data_store, 'size_radius', [[.0],[.0],[.0]], [i-step,i], withPGN, withV1 )
#     # perform_analysis_and_visualization_radius( data_store, 'size_radius', [[1.6],[.0],[.0]], [i-step,i], withPGN, withV1 )

예제 #9

if MPI:
    mpi_comm = MPI.COMM_WORLD
MPI_ROOT = 0

logger = mozaik.getMozaikLogger()


# Manage what is executed
# a set of variable here to manage the type of experiment and whether the pgn, cortex are there or not.
withPGN = True  # 
withV1 = True  # open-loop
withFeedback_CxPGN = True # closed loop
withFeedback_CxLGN = True # closed loop

# Model execution
if True:
    data_store,model = run_workflow('ThalamoCorticalModel', ThalamoCorticalModel, create_experiments_contrast )
    data_store.save()
# or only load pickled data
else:
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'ThalamoCorticalModel_data_contrast_closed_____', 'store_stimuli' : False}),replace=True)
    logger.info('Loaded data store')

    # Analysis and Plotting
    if mpi_comm.rank == MPI_ROOT:
        # perform_analysis_and_visualization( data_store, 'luminance', withPGN, withV1 )
        perform_analysis_and_visualization( data_store, 'contrast', withPGN, withV1 )

    data_store.save()

예제 #10

withV1 = False  # open-loop
withFeedback_CxPGN = False  # closed loop
withFeedback_CxLGN = False  # closed loop

# Model execution
if True:
    data_store, model = run_workflow('ThalamoCorticalModel',
                                     ThalamoCorticalModel,
                                     create_experiments_luminance)
    data_store.save()
# or only load pickled data
else:
    setup_logging()
    # data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'Deliverable/ThalamoCorticalModel_data_luminance_open_____', 'store_stimuli' : False}),replace=True)
    data_store = PickledDataStore(
        load=True,
        parameters=ParameterSet({
            'root_directory': 'ThalamoCorticalModel_data_luminance_open_____',
            'store_stimuli': False
        }),
        replace=True)
    logger.info('Loaded data store')

# Analysis and Plotting
if mpi_comm.rank == MPI_ROOT:
    # perform_analysis_test( data_store )
    perform_analysis_and_visualization(data_store, 'luminance', withPGN,
                                       withV1)

    data_store.save()

예제 #11

                                     create_experiments_size_nonoverlapping)
    data_store.save()

# or only load pickled data
else:
    setup_logging()
    data_store = PickledDataStore(
        load=True,
        parameters=ParameterSet({
            'root_directory':
            'ThalamoCorticalModel_data_size_closed_nonoverlapping_____',
            'store_stimuli': False
        }),
        replace=True)
    # data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'Deliverable/ThalamoCorticalModel_data_size_closed_____', 'store_stimuli' : False}),replace=True)
    # data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'Deliverable/ThalamoCorticalModel_data_size_feedforward_____', 'store_stimuli' : False}),replace=True)
    logger.info('Loaded data store')

    # Analysis and Plotting
    if mpi_comm.rank == MPI_ROOT:
        # perform_analysis_test( data_store )
        perform_analysis_and_visualization(data_store, 'size', withPGN, withV1)
        # perform_analysis_and_visualization( data_store, 'feedforward', withPGN, withV1 )

        # import numpy
        # step = .2
        # for i in numpy.arange(step, 3.+step, step):
        #     perform_analysis_and_visualization_radius( data_store, 'size_radius', [i-step,i], withPGN, withV1 )

    data_store.save()

예제 #12

파일: run_old_short.py 프로젝트: antolikjan/mozaik-contrib

"""
import matplotlib
matplotlib.use('Agg')
from mpi4py import MPI 
from pyNN import nest
import sys
import mozaik.controller
from mozaik.controller import run_workflow, setup_logging
import mozaik
from experiments import create_experiments,create_experiments_bar,create_experiments_short,create_experiments_old,create_experiments_old_short
from model import SelfSustainedPushPull
from mozaik.storage.datastore import Hdf5DataStore,PickledDataStore
from analysis_and_visualization import perform_analysis_and_visualization
from parameters import ParameterSet


mpi_comm = MPI.COMM_WORLD

if True:
    data_store,model = run_workflow('MorganTaylorModel',SelfSustainedPushPull,create_experiments_old_short)
    data_store.save() 
else: 
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'MorganTaylorModel_visual_space_update=1ms_RF_resolution=1ms','store_stimuli' : False}),replace=True)

if mpi_comm.rank == 0:
   print "Starting visualization" 
   perform_analysis_and_visualization(data_store,gratings=True,bars=False,nat_movies=True)
#   data_store.save() 

예제 #13

파일: run_analysis_sharpness.py 프로젝트: apdavison/mozaik-contrib

"""
"""
import matplotlib
matplotlib.use('Agg')
import sys
from mozaik.controller import setup_logging
import mozaik
from mozaik.storage.datastore import Hdf5DataStore, PickledDataStore
from analysis_and_visualization import perform_analysis_and_visualization
from parameters import ParameterSet

from mozaik.controller import Global
Global.root_directory = sys.argv[1] + '/'

setup_logging()
data_store = PickledDataStore(load=True,
                              parameters=ParameterSet({
                                  'root_directory':
                                  sys.argv[1],
                                  'store_stimuli':
                                  False
                              }),
                              replace=True)
perform_analysis_and_visualization(data_store,
                                   gratings=False,
                                   cort_stim=True,
                                   nat_stim=False,
                                   tp=1,
                                   scale=False,
                                   sharpness=True)

예제 #14

from parameters import ParameterSet

#mpi_comm = MPI.COMM_WORLD
logger = mozaik.getMozaikLogger()
simulation_name = "VogelsAbbott2005"
simulation_run_name, _, _, _, modified_parameters = parse_workflow_args()

if True:
    data_store,model = run_workflow(simulation_name,VogelsAbbott,create_experiments)
    model.connectors['ExcExcConnection'].store_connections(data_store)    
else: 
    setup_logging()
    data_store = PickledDataStore(
        load=True,
        parameters=ParameterSet(
            {
                "root_directory": result_directory_name(
                    simulation_run_name, simulation_name, modified_parameters
                ),
                "store_stimuli": False,
            }
        ),
        replace=True,
    )
    logger.info('Loaded data store')

#if mpi_comm.rank == 0:
print("Starting visualization")
perform_analysis_and_visualization(data_store)
data_store.save() 

예제 #15

파일: run_contrast.py 프로젝트: dguarino/T2

            model.connectors['V1AffConnectionOff'].store_connections(data_store)    
            model.connectors['V1AffInhConnectionOn'].store_connections(data_store)    
            model.connectors['V1AffInhConnectionOff'].store_connections(data_store)    
            model.connectors['V1L4ExcL4ExcConnection'].store_connections(data_store)    
            model.connectors['V1L4ExcL4InhConnection'].store_connections(data_store)    
            model.connectors['V1L4InhL4ExcConnection'].store_connections(data_store)    
            model.connectors['V1L4InhL4InhConnection'].store_connections(data_store)    
            model.connectors['V1L4ExcL4ExcConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4ExcL4InhConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4InhL4ExcConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4InhL4InhConnectionRand'].store_connections(data_store)
            if withFeedback_CxLGN:
                model.connectors['V1EffConnectionOn'].store_connections(data_store)    
                model.connectors['V1EffConnectionOff'].store_connections(data_store)    
            if withPGN and withFeedback_CxPGN:
                model.connectors['V1EffConnectionPGN'].store_connections(data_store)    

    data_store.save()
# or only load pickled data
else:
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'ThalamoCorticalModel_data_contrast_____', 'store_stimuli' : False}),replace=True)
    logger.info('Loaded data store')
    data_store.save()

# Analysis and Plotting
if mpi_comm.rank == MPI_ROOT:
    # perform_analysis_test( data_store )
    # perform_analysis_and_visualization( data_store, 'luminance', withPGN, withV1 )
    perform_analysis_and_visualization( data_store, 'contrast', withPGN, withV1 )

예제 #16

파일: run_cs_exc_lum_or.py 프로젝트: antolikjan/mozaik-contrib

"""
import matplotlib
matplotlib.use('Agg')

from mpi4py import MPI
#from pyNN import nest
import sys
import mozaik.controller
from mozaik.controller import run_workflow, setup_logging
import mozaik
from experiments import create_experiments_cortical_stimulation_or_exc_LumBased
from model import SelfSustainedPushPull
from mozaik.storage.datastore import Hdf5DataStore, PickledDataStore
from analysis_and_visualization import perform_analysis_and_visualization
from parameters import ParameterSet

mpi_comm = MPI.COMM_WORLD

data_store, model = run_workflow(
    'CorticalStimulationModel', SelfSustainedPushPull,
    create_experiments_cortical_stimulation_or_exc_LumBased)
data_store.save()

if mpi_comm.rank == 0:
    print "Starting visualization"
    perform_analysis_and_visualization(data_store,
                                       gratings=False,
                                       cort_stim=True,
                                       nat_stim=False,
                                       tp=1)

예제 #17

파일: run_luminance.py 프로젝트: dguarino/T2

            model.connectors['V1AffConnectionOff'].store_connections(data_store)    
            model.connectors['V1AffInhConnectionOn'].store_connections(data_store)    
            model.connectors['V1AffInhConnectionOff'].store_connections(data_store)    
            model.connectors['V1L4ExcL4ExcConnection'].store_connections(data_store)    
            model.connectors['V1L4ExcL4InhConnection'].store_connections(data_store)    
            model.connectors['V1L4InhL4ExcConnection'].store_connections(data_store)    
            model.connectors['V1L4InhL4InhConnection'].store_connections(data_store)    
            model.connectors['V1L4ExcL4ExcConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4ExcL4InhConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4InhL4ExcConnectionRand'].store_connections(data_store)    
            model.connectors['V1L4InhL4InhConnectionRand'].store_connections(data_store)
            if withFeedback_CxLGN:
                model.connectors['V1EffConnectionOn'].store_connections(data_store)    
                model.connectors['V1EffConnectionOff'].store_connections(data_store)    
            if withPGN and withFeedback_CxPGN:
                model.connectors['V1EffConnectionPGN'].store_connections(data_store)    

    data_store.save()
# or only load pickled data
else:
    setup_logging()
    data_store = PickledDataStore(load=True,parameters=ParameterSet({'root_directory':'ThalamoCorticalModel_data_luminance_____', 'store_stimuli' : False}),replace=True)
    logger.info('Loaded data store')
    data_store.save()


# Analysis and Plotting
if mpi_comm.rank == MPI_ROOT:
    # perform_analysis_test( data_store )
    perform_analysis_and_visualization( data_store, 'luminance', withPGN, withV1 )