Beispiel #1
0
def main():

    args, kwargs = _parse_args(sys.argv[1:])

    if args.profiler or args.line_profiler:
        from phy.utils.testing import _enable_profiler, _profile
        prof = _enable_profiler(args.line_profiler)
    else:
        prof = None

    import phy
    if args.debug:
        phy.debug()

    if args.cluster_ids:
        cluster_ids = list(map(int, args.cluster_ids.split(',')))
    else:
        cluster_ids = None

    if args.command == 'cluster-manual':
        cmd = ('run_manual(args.file, clustering=args.clustering, '
               'interactive=args.ipython, cluster_ids=cluster_ids)')
    elif args.command == 'cluster-auto':
        cmd = ('run_auto(args.file, clustering=args.clustering, '
               'interactive=args.ipython, **kwargs)')
    elif args.command == 'describe':
        cmd = 'describe(args.file)'
    else:
        raise NotImplementedError()

    if not prof:
        exec_(cmd, globals(), locals())
    else:
        _profile(prof, cmd, globals(), locals())
Beispiel #2
0
def main(args=None):
    p = ParserCreator()
    if args is None:
        args = sys.argv[1:]
    elif isinstance(args, string_types):
        args = args.split(' ')
    args = p.parse(args)
    if args is None:
        return

    if args.profiler or args.line_profiler:
        from phy.utils.testing import _enable_profiler, _profile
        prof = _enable_profiler(args.line_profiler)
    else:
        prof = None

    import phy
    if args.debug:
        phy.debug()

    # Hide the traceback.
    if args.hide_traceback:
        def exception_handler(exception_type, exception, traceback):
            print("{}: {}".format(exception_type.__name__, exception))

        sys.excepthook = exception_handler

    # Activate IPython debugger.
    if args.pdb:
        from IPython.core import ultratb
        sys.excepthook = ultratb.FormattedTB(mode='Verbose',
                                             color_scheme='Linux',
                                             call_pdb=1,
                                             )

    func = args.func
    if func is None:
        p.parser.print_help()
        return

    out = func(args)
    if not out:
        return
    cmd, ns = out
    if not cmd:
        return
    requires_qt = ns.pop('requires_qt', False)
    requires_vispy = ns.pop('requires_vispy', False)

    # Default variables in namespace.
    ns.update(phy=phy, path=args.file)
    if 'session' in ns:
        ns['model'] = ns['session'].model

    # Interactive mode with IPython.
    if args.ipython:
        print("\nStarting IPython...")
        from IPython import start_ipython
        args_ipy = ["-i", "-c='{}'".format(cmd)]
        if requires_qt or requires_vispy:
            # Activate Qt event loop integration with Qt.
            args_ipy += ["--gui=qt"]
        start_ipython(args_ipy, user_ns=ns)
    else:
        if not prof:
            exec_(cmd, {}, ns)
        else:
            _profile(prof, cmd, {}, ns)

        if requires_qt:
            # Launch the Qt app.
            from phy.gui import run_qt_app
            run_qt_app()
        elif requires_vispy:
            # Launch the VisPy Qt app.
            from vispy.app import use_app, run
            use_app('pyqt4')
            run()
Beispiel #3
0
import os.path as op
import shutil
from pprint import pprint
from timeit import default_timer

import h5py
import numpy as np
from numpy.testing import assert_allclose as ac

import phy
from phy.cluster.manual.store import DiskStore
from phy.io.h5 import open_h5
from phy.cluster.manual._utils import _spikes_per_cluster
from phy.utils.array import _index_of

phy.debug()

_store_path = '_store'
n_spikes = 2000000
n_channels = 300
n_clusters = 500


# Generate the dataset.
def _gen_arr():
    arr = np.random.rand(n_spikes, n_channels).astype(np.float32)
    with open_h5('test', 'w') as f:
        f.write('/test', arr)


def _gen_spike_clusters():
Beispiel #4
0
def main(args=None):
    p = ParserCreator()
    if args is None:
        args = sys.argv[1:]
    elif isinstance(args, string_types):
        args = args.split(' ')
    args = p.parse(args)
    if args is None:
        return

    if args.profiler or args.line_profiler:
        from phy.utils.testing import _enable_profiler, _profile
        prof = _enable_profiler(args.line_profiler)
    else:
        prof = None

    import phy
    if args.debug:
        phy.debug()

    # Hide the traceback.
    if args.hide_traceback:

        def exception_handler(exception_type, exception, traceback):
            print("{}: {}".format(exception_type.__name__, exception))

        sys.excepthook = exception_handler

    # Activate IPython debugger.
    if args.pdb:
        from IPython.core import ultratb
        sys.excepthook = ultratb.FormattedTB(
            mode='Verbose',
            color_scheme='Linux',
            call_pdb=1,
        )

    func = args.func
    if func is None:
        p.parser.print_help()
        return

    out = func(args)
    if not out:
        return
    cmd, ns = out
    if not cmd:
        return
    requires_qt = ns.pop('requires_qt', False)
    requires_vispy = ns.pop('requires_vispy', False)

    # Default variables in namespace.
    ns.update(phy=phy, path=args.file)
    if 'session' in ns:
        ns['model'] = ns['session'].model

    # Interactive mode with IPython.
    if args.ipython:
        print("\nStarting IPython...")
        from IPython import start_ipython
        args_ipy = ["-i", "-c='{}'".format(cmd)]
        if requires_qt or requires_vispy:
            # Activate Qt event loop integration with Qt.
            args_ipy += ["--gui=qt"]
        start_ipython(args_ipy, user_ns=ns)
    else:
        if not prof:
            exec_(cmd, {}, ns)
        else:
            _profile(prof, cmd, {}, ns)

        if requires_qt:
            # Launch the Qt app.
            from phy.gui import run_qt_app
            run_qt_app()
        elif requires_vispy:
            # Launch the VisPy Qt app.
            from vispy.app import use_app, run
            use_app('pyqt4')
            run()
import shutil
from pprint import pprint
from timeit import default_timer


import h5py
import numpy as np
from numpy.testing import assert_allclose as ac

import phy
from phy.cluster.manual.store import DiskStore
from phy.io.h5 import open_h5
from phy.cluster.manual._utils import _spikes_per_cluster
from phy.utils.array import _index_of

phy.debug()

_store_path = '_store'
n_spikes = 2000000
n_channels = 300
n_clusters = 500


# Generate the dataset.
def _gen_arr():
    arr = np.random.rand(n_spikes, n_channels).astype(np.float32)
    with open_h5('test', 'w') as f:
        f.write('/test', arr)


def _gen_spike_clusters():