Python Trajectory.v_auto_load方法代码示例

# 需要导入模块: from pypet import Trajectory [as 别名]
# 或者: from pypet.Trajectory import v_auto_load [as 别名]
    def test_wildcard_search(self):

        traj = Trajectory(name='Testwildcard', filename=make_temp_dir('wilcard.hdf5'),
                          add_time=True)

        traj.f_add_parameter('expl', 2)
        traj.f_explore({'expl':[1,2,3,4]})

        traj.f_add_result('wc2test.$.hhh', 333)
        traj.f_add_leaf('results.wctest.run_00000000.jjj', 42)
        traj.f_add_result('results.wctest.run_00000001.jjj', 43)
        traj.f_add_result('results.wctest.%s.jjj' % traj.f_wildcard('$', -1), 43)

        traj.v_crun = 1

        self.assertTrue(traj.results.wctest['$'].jjj==43)
        self.assertTrue(traj.results.wc2test.crun.hhh==333)

        traj.f_store()

        get_root_logger().info('Removing child1')

        traj.f_remove_child('results', recursive=True)

        get_root_logger().info('Doing auto-load')
        traj.v_auto_load = True

        self.assertTrue(traj.results.wctest['$'].jjj==43)
        self.assertTrue(traj.results.wc2test.crun.hhh==333)

        get_root_logger().info('Removing child2')

        traj.f_remove_child('results', recursive=True)

        get_root_logger().info('auto-loading')
        traj.v_auto_load = True

        self.assertTrue(traj.results.wctest[-1].jjj==43)
        self.assertTrue(traj.results.wc2test[-1].hhh==333)

        get_root_logger().info('Removing child3')
        traj.f_remove_child('results', recursive=True)

        get_root_logger().info('auto-loading')
        traj.v_auto_load = True

        self.assertTrue(traj.results.wctest[1].jjj==43)
        self.assertTrue(traj.results.wc2test[-1].hhh==333)

        get_root_logger().info('Done with wildcard test')

# 需要导入模块: from pypet import Trajectory [as 别名]
# 或者: from pypet.Trajectory import v_auto_load [as 别名]
    def test_get_default(self):


        traj = Trajectory(name='Testgetdefault', filename=make_temp_dir('autoload.hdf5'))

        traj.v_auto_load = True

        traj.f_add_result('I.am.$.a.mean.resu', 42, comment='Test')

        val = traj.f_get_default('jjjjjjjjjj', 555)
        self.assertTrue(val==555)

        traj.f_store()

        traj.f_remove_child('results', recursive=True)




        val = traj.f_get_default('res.I.am.crun.a.mean.answ', 444, auto_load=True)

        self.assertTrue(val==444)

        val = traj.f_get_default('res.I.am.crun.a.mean.resu', auto_load=True, fast_access=True)

        self.assertTrue(val==42)

        with self.assertRaises(Exception):
            traj.kdsfdsf

# 需要导入模块: from pypet import Trajectory [as 别名]
# 或者: from pypet.Trajectory import v_auto_load [as 别名]
    def test_auto_load(self):


        traj = Trajectory(name='Testautoload', filename=make_temp_dir('autoload.hdf5'))

        traj.v_auto_load = True

        traj.f_add_result('I.am.$.a.mean.resu', 42, comment='Test')

        traj.f_add_derived_parameter('ffa', 42)

        traj.f_store()

        ffa=traj.f_get('ffa')
        ffa.f_unlock()
        ffa.f_empty()

        self.assertTrue(ffa.f_is_empty())

        traj.f_remove_child('results', recursive=True)

        # check auto load
        val = traj.res.I.am.crun.a.mean.resu

        self.assertTrue(val==42)

        val = traj.ffa

        self.assertTrue(val==42)

        with self.assertRaises(pex.DataNotInStorageError):
            traj.kdsfdsf

# 需要导入模块: from pypet import Trajectory [as 别名]
# 或者: from pypet.Trajectory import v_auto_load [as 别名]
    def test_migrations(self):

        traj = Trajectory(name='Testmigrate', filename=make_temp_dir('migrate.hdf5'))

        traj.f_add_result('I.am.a.mean.resu', 42, comment='Test')
        traj.f_add_derived_parameter('ffa', 42)

        traj.f_store()

        new_file = make_temp_dir('migrate2.hdf5')
        traj.f_migrate(filename=new_file)

        traj.f_store()

        new_traj = Trajectory()

        new_traj.f_migrate(new_name=traj.v_name, filename=new_file, in_store=True)

        new_traj.v_auto_load=True

        self.assertTrue(new_traj.results.I.am.a.mean.resu == 42)

# 需要导入模块: from pypet import Trajectory [as 别名]
# 或者: from pypet.Trajectory import v_auto_load [as 别名]
    def test_storage_and_loading(self):
        filename = make_temp_dir('linktest.hdf5')
        traj = Trajectory(filename=filename)

        traj.f_add_parameter_group('test')
        traj.f_add_parameter_group('test2')
        res= traj.f_add_result('kk', 42)

        traj.par.f_add_link('gg', res)

        traj.f_add_link('hh', res)
        traj.f_add_link('jj', traj.par)
        traj.f_add_link('ii', res)

        traj.test.f_add_link('circle1' , traj.test2)
        traj.test2.f_add_link('circle2' , traj.test)
        traj.test.f_add_link('circle2' , traj.test.circle1.circle2)

        traj.f_add_parameter_group('test.ab.bc.cd')
        traj.cd.f_add_link(traj.test)
        traj.test.f_add_link(traj.cd)

        traj.f_store()

        traj2 = Trajectory(filename=filename)
        traj2.f_load(name=traj.v_name, load_data=2)

        self.assertTrue(traj.kk == traj2.gg, '%s != %s' % (traj.kk, traj2.gg))
        self.assertTrue(traj.cd.test is traj.test)

        self.assertTrue(len(traj._linked_by), len(traj2._linked_by))
        self.compare_trajectories(traj, traj2)

        self.assertTrue('jj' in traj2._nn_interface._links_count)
        traj2.f_remove_child('jj')
        self.assertTrue('jj' not in traj2._nn_interface._links_count)
        traj2.f_remove_child('hh')
        traj2.f_remove_child('ii')



        traj2.f_remove_child('parameters', recursive=True)

        traj2.v_auto_load = True

        group = traj2.par.test2.circle2

        self.assertTrue(group is traj2.test)

        retest = traj2.test.circle1

        self.assertTrue(retest is traj2.test2)

        self.assertTrue(traj2.test.circle2 is traj2.test)

        self.assertTrue(traj2.hh == traj2.res.kk)

        traj2.v_auto_load = False
        traj2.f_load_child('jj')
        self.assertTrue(traj2.jj is traj2.par)
        traj2.f_load(load_data=2)
        self.assertTrue(traj2.ii == traj2.res.kk)

# 需要导入模块: from pypet import Trajectory [as 别名]
# 或者: from pypet.Trajectory import v_auto_load [as 别名]
def main():

    # This time we don't need an environment since we just going to look
    # at data in the trajectory
    traj = Trajectory('FiringRate', add_time=False)

    # Let's load the trajectory from the file
    # Only load the parameters, we will load the results on the fly as we need them
    filename = os.path.join('hdf5', 'FiringRate.hdf5')
    traj.f_load(load_parameters=2, load_derived_parameters=0, load_results=0,
                load_other_data=0, filename=filename)

    # We'll simply use auto loading so all data will be loaded when needed.
    traj.v_auto_load = True

    rates_frame = traj.res.summary.firing_rates.rates_frame
    # Here we load the data automatically on the fly

    plt.figure()
    plt.subplot(2,1,1)
    #Let's iterate through the columns and plot the different firing rates :
    for tau_ref, I_col in rates_frame.iteritems():
        plt.plot(I_col.index, I_col, label='Avg. Rate for tau_ref=%s' % str(tau_ref))

    # Label the plot
    plt.xlabel('I')
    plt.ylabel('f[Hz]')
    plt.title('Firing as a function of input current `I`')
    plt.legend(loc='best')

    # Also let's plot an example run, how about run 13 ?
    example_run = 13

    traj.v_idx = example_run # We make the trajectory behave as a single run container.
    # This short statement has two major effects:
    # a) all explored parameters are set to the value of run 13,
    # b) if there are tree nodes with names other than the current run aka `run_00000013`
    # they are simply ignored, if we use the `$` sign or the `crun` statement,
    # these are translated into `run_00000013`.

    # Get the example data
    example_I = traj.I
    example_tau_ref = traj.tau_ref
    example_V = traj.results.neuron.crun.V # Here crun stands for run_00000013

    # We need the time step...
    dt = traj.dt
    # ...to create an x-axis for the plot
    dt_array = [irun * dt for irun in range(len(example_V))]

    # And plot the development of V over time,
    # Since this is rather repetitive, we only
    # plot the first eighth of it.
    plt.subplot(2,1,2)
    plt.plot(dt_array, example_V)
    plt.xlim((0, dt*len(example_V)/8))

    # Label the axis
    plt.xlabel('t[ms]')
    plt.ylabel('V')
    plt.title('Example of development of V for I=%s, tau_ref=%s in run %d' %
              (str(example_I), str(example_tau_ref), traj.v_idx))

    # And let's take a look at it
    plt.show()

    # Finally revoke the `traj.v_idx=13` statement and set everything back to normal.
    # Since our analysis is done here, we could skip that, but it is always a good idea
    # to do that.
    traj.f_restore_default()