import crime_data.constants
import crime_data.crime_data.fxns as crime_data_fxns
import tensor_scan.tensor_scan.fxns as tensor_scan_fxns
import python_utils.python_utils.utils as utils
import itertools
import numpy as np
import pdb
import functools
"""
scratch data_iterable
"""
data_id_iterable = crime_data_fxns.AllHouseBurglaryIterable()
cat_fs = [\
utils.categorical_f(crime_data_fxns.house_break_f('location_of_entry'), [utils.equals_bin('Door: Front'), utils.equals_bin('Window: Ground'), utils.equals_bin('Door: Rear')]),\
utils.categorical_f(crime_data_fxns.house_break_f('categorization'), [utils.equals_bin('Professional'), utils.equals_bin('Unprofessional'), utils.equals_bin('Attempt')]),\
]
int_cat_fs = [utils.int_f_from_categorical_f(cat_f) for cat_f in cat_fs]
int_cat_fs_set_iterable = utils.get_powerset_iterator(int_cat_fs)
x_f_iterable = itertools.starmap(utils.series_f, int_cat_fs_set_iterable)
location_f = crime_data_fxns.house_break_f('latlng')
time_f = crime_data_fxns.house_break_f('date_num')
in_pattern_f = crime_data_fxns.in_pattern_f()
scratch_data_iterable = itertools.imap(lambda x_f: map(lambda id: tensor_scan_fxns.datum(id, time_f(id), location_f(id), x_f(id), in_pattern_f(id)), data_id_iterable), x_f_iterable)
"""
scratch pattern_finder_iterable
"""
num_lat_iterable = [5, 10, 15, 20, 30]
import crime_data.constants
import pdb
import tensor_scan.tensor_scan.fxns as tensor_scan_fxns
import crime_data.crime_data.fxns as crime_data_fxns
import python_utils.python_utils.utils as utils
import itertools
import numpy as np
"""
scratch data
"""
location_f = crime_data_fxns.house_break_f('latlng')
year_f = crime_data_fxns.house_break_f('year')
data_id_iterable = list(itertools.ifilter(lambda id: year_f(id) >= 2003 and year_f(id) <= 2005 and location_f(id) in utils.latlng_grid_region(crime_data.constants.cambridge_min_lat, crime_data.constants.cambridge_max_lat, crime_data.constants.cambridge_min_lng, crime_data.constants.cambridge_max_lng), crime_data_fxns.AllHouseBurglaryIterable()))
#data_id_iterable = list(itertools.ifilter(lambda id: location_f(id) in utils.latlng_grid_region(crime_data.constants.cambridge_min_lat, crime_data.constants.cambridge_max_lat, crime_data.constants.cambridge_min_lng, crime_data.constants.cambridge_max_lng), crime_data_fxns.AllHouseBurglaryIterable()))
cat_fs = [\
utils.categorical_f(crime_data_fxns.house_break_f('location_of_entry'), [utils.equals_bin('Door: Front'), utils.equals_bin('Window: Ground'), utils.equals_bin('Door: Rear')]),\
utils.categorical_f(crime_data_fxns.house_break_f('means_of_entry'), [utils.equals_bin('Pried'), utils.equals_bin('Unlocked'), utils.equals_bin('Shoved/Forced'), utils.equals_bin('Broke')]),\
# utils.categorical_f(crime_data_fxns.house_break_f('categorization'), [utils.equals_bin('Professional'), utils.equals_bin('Unprofessional'), utils.equals_bin('Attempt')]),\
]
int_cat_fs = [utils.int_f_from_categorical_f(cat_f) for cat_f in cat_fs]
x_f = utils.series_f(*int_cat_fs)
#x_f = utils.series_f(utils.hard_code_f(0))
time_f = crime_data_fxns.house_break_f('date_num')
in_pattern_f = crime_data_fxns.in_pattern_f()
pattern_f = crime_data_fxns.house_break_f('pattern')
scratch_data = [tensor_scan_fxns.datum(id, time_f(id), location_f(id), x_f(id), in_pattern_f(id), pattern_f(id)) for id in data_id_iterable]