def __init__(self, data, callbacks=None, name = '', is_subset = False,
is_copy=False, map_log_to_debug=False, **params):
self.name = name
if callbacks is None:
callbacks = {}
self.callbacks = callbacks
self.data = data
self.cluster_hashes = set()
self.is_subset = is_subset
self.is_copy = is_copy
self.map_log_to_debug = map_log_to_debug
# user parameters
show_params = name=='' and not is_subset and not is_copy
self.params = params
actual_params = default_parameters.copy()
for k, v in iteritems(params):
if k not in default_parameters:
raise ValueError("There is no parameter "+k)
actual_params[k] = v
for k, v in iteritems(actual_params):
setattr(self, k, v)
if show_params:
self.log('info', '%s = %s' % (k, v), suffix='initial_parameters')
self.all_params = actual_params #dictionary of parameters
def __init__(self,
data,
callbacks=None,
name='',
is_subset=False,
is_copy=False,
map_log_to_debug=False,
**params):
self.name = name
if callbacks is None:
callbacks = {}
self.callbacks = callbacks
self.data = data
self.cluster_hashes = set()
self.is_subset = is_subset
self.is_copy = is_copy
self.map_log_to_debug = map_log_to_debug
# user parameters
show_params = name == '' and not is_subset and not is_copy
self.params = params
actual_params = default_parameters.copy()
for k, v in iteritems(params):
if k not in default_parameters:
raise ValueError("There is no parameter " + k)
actual_params[k] = v
for k, v in iteritems(actual_params):
setattr(self, k, v)
if show_params:
self.log('info',
'%s = %s' % (k, v),
suffix='initial_parameters')
self.all_params = actual_params #dictionary of parameters
#before running this script import pickle import numpy as np import matplotlib.pyplot as plt import sorting from supercluster import * from klustakwik2 import * import imp # lets you reload modules using e.g.imp.reload(sorting) from IPython import embed import time from emcat import KK from default_parameters import default_parameters import testing_cat as tc script_params = default_parameters.copy() #script_params.update( # run_monitoring_server=False, # debug=True, # ) personal_homedir = '/Users/shabnamkadir/clustering/' picklefile = personal_homedir + 'global_superclustering/global_code/synthetic_cat.p' pkl_file = open(picklefile,'rb') mixture = pickle.load(pkl_file) pkl_file.close() #Get initial clustering for testing initpicklefile = personal_homedir + 'global_superclustering/global_code/init_synthetic_cat_4.p' initpkl_file = open(initpicklefile,'rb') initclust = pickle.load(initpkl_file)
#before running this script import pickle import numpy as np import matplotlib.pyplot as plt import sorting from supercluster import * from klustakwik2 import * import imp # lets you reload modules using e.g.imp.reload(sorting) from IPython import embed import time from emcat import KK from default_parameters import default_parameters import testing_cat as tc script_params = default_parameters.copy() #script_params.update( # run_monitoring_server=False, # debug=True, # ) personal_homedir = '/home/alex/Documents/' picklefile = personal_homedir + 'global_superclustering/Project/source/synthetic_cat.p' pkl_file = open(picklefile, 'rb') mixture = pickle.load(pkl_file) pkl_file.close() #embed() mixture_dict = mixture[0] num_starting_clusters = 4 #produces an initial random clustering with 4 starting clusters. num_spikes = mixture_dict['superclusters'].shape[0] initclust = tc.generate_random_initial_clustering(num_starting_clusters,
