def validation_test_features(self, data_set):
output_list = []
for item in data_set:
label = item[0]
input = str(item[1])
local_feat_dict = {}
discovered_features = []
discovered_features.extend(self.features_suffixes(input))
discovered_features.extend(self.features_words(input))
discovered_features.extend(self.features_special(input))
for f in discovered_features:
if f in self.feature_dict: # if feature in global feat dict
if f not in local_feat_dict:
local_feat_dict[f] = 1
else:
local_feat_dict[f] += 1
data_point = Data_Point()
if label != '':
data_point.true_label_index = self.label_dict[label]
data_point.features_dict = local_feat_dict
output_list.append(data_point)
return output_list
def move(self, Data_Point):
t0 = self.drone.location()
max_Location = Data_Point.get_Location()
max_Signal = Data_Point.get_Signal()
direction_of_travel = [
max_Location[0] - t0[0], max_Location[1] - t0[1],
max_Location[2] - t0[2]
]
print(
"\n\nDrone will move in %s --> %s direction and it is in %s location relative to its starting position"
% (Data_Point.id, direction_of_travel, self.drone.location()))
self.drone.moveFr(direction_of_travel[0] * 2)
self.drone.moveRi(direction_of_travel[1] * 2)
self.drone.moveUp(direction_of_travel[2] * 2)
while (Signal(self.drone).calcSS() > max_Signal):
max_Signal = Signal(self.drone).calcSS()
self.drone.moveFr(direction_of_travel[0])
self.drone.moveRi(direction_of_travel[1])
self.drone.moveUp(direction_of_travel[2])
self.drone.moveFr(direction_of_travel[0] * -1)
self.drone.moveRi(direction_of_travel[1] * -1)
self.drone.moveUp(direction_of_travel[2] * -1)
def validation_test_features(self, data_set):
output_list = []
for item in data_set: # for each item...
# get data
label = item[0]
input = str(item[1])
local_feat_dict = {} # local dict to store features for each item
input_list = list(input) # convert string to list of characters
# find all n-grams of the string
for i in range(0, len(input_list) - self.N + 1):
s = input_list[i]
if s == ' ':
continue
for j in range(1, self.N):
if input_list[
j] == ' ': # stop when whitespace encountered
break
s = s + '' + input_list[i + j]
if s in self.feature_dict:
if s not in local_feat_dict:
local_feat_dict[s] = 1
else:
local_feat_dict[s] += 1
data_point = Data_Point()
if label != '':
data_point.true_label_index = self.label_dict[label]
data_point.features_dict = local_feat_dict
output_list.append(data_point)
return output_list
def find_features_and_labels(self):
data = self.data
# vars
global_feat_dict = {}
global_feat_index = 0
label_dict = {}
label_index = 0
for item in data: # for each item...
# get data
label = item[0]
input = str(item[1])
local_feat_dict = {} # local dict to store features for each item
input_list = list(input) # convert string to list of characters
# find all n-grams of the string
for i in range(0, len(input_list) - self.N + 1):
s = input_list[i]
if s == ' ':
continue
for j in range(1, self.N):
if input_list[
j] == ' ': # stop when whitespace encountered
break
s = s + '' + input_list[i + j]
if s not in local_feat_dict:
local_feat_dict[s] = 1
else:
local_feat_dict[s] += 1
if s not in global_feat_dict:
global_feat_dict[s] = global_feat_index
global_feat_index += 1
if label not in label_dict:
label_dict[label] = label_index
label_index += 1
data_point = Data_Point()
data_point.true_label_index = label_dict[label]
data_point.features_dict = local_feat_dict
self.data_points_list.append(data_point)
self.feature_dict = global_feat_dict
self.label_dict = label_dict
def find_features_and_labels(self):
"""
"""
data = self.data
char_dict = {}
char_index = 0
label_dict = {
} # stores label and their corresponding index (i.e. drugs:0, company:1, ...)
label_count = 0
# parse each character into a set
for item in data:
input = str(item[1])
input = re.sub(r'[^\w]', '', input) # remove spaces
input_l = list(input)
label = str(item[0])
input_char_dict = {}
data_point = Data_Point()
for c in input_l:
if c not in input_char_dict:
input_char_dict[c] = 1 # add char to 'local' char dict
else:
input_char_dict[c] += 1
if c not in char_dict:
char_dict[
c] = char_index # add character to 'global' char dict
char_index += 1
if label not in label_dict.keys():
label_dict[label] = label_count # also add to label dict
label_count += 1
data_point.true_label_index = label_dict[
label] # TODO changed label to label_index
data_point.features_dict = input_char_dict
self.data_points_list.append(data_point)
self.feature_dict = char_dict
self.label_dict = label_dict
def find_features_and_labels(self):
data = self.data
global_feat_dict = {}
global_feat_index = 0
label_dict = {}
label_index = 0
for item in data:
label = item[0]
input = str(item[1])
local_feat_dict = {}
discovered_features = []
discovered_features.extend(self.features_suffixes(input))
discovered_features.extend(self.features_words(input))
discovered_features.extend(self.features_special(input))
for f in discovered_features:
if f not in local_feat_dict:
local_feat_dict[f] = 1
else:
local_feat_dict[f] += 1
if f not in global_feat_dict:
global_feat_dict[f] = global_feat_index
global_feat_index += 1
if label not in label_dict:
label_dict[label] = label_index
label_index += 1
data_point = Data_Point()
data_point.true_label_index = label_dict[label]
data_point.features_dict = local_feat_dict
self.data_points_list.append(data_point)
self.feature_dict = global_feat_dict
self.label_dict = label_dict
def validation_test_features(self, data_set):
output_list = []
for item in data_set:
input = str(item[1])
input = re.sub(r'[^\w]', '', input) # remove spaces
input_l = list(input)
label = str(item[0])
input_char_dict = {}
data_point = Data_Point()
for c in input_l:
if c in self.feature_dict:
if c not in input_char_dict:
input_char_dict[c] = 1
else:
input_char_dict[c] += 1
data_point.features_dict = input_char_dict
if label != '':
data_point.true_label_index = self.label_dict[label]
output_list.append(data_point)
return output_list
def Box_mission(self):
box_plots = []
box_plots.append(
Data_Point("T0", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveFr(self.length_of_box / 2)
box_plots.append(
Data_Point("T1", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveRi((self.length_of_box / 2) * -1)
box_plots.append(
Data_Point("T2", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveFr((self.length_of_box / 2) * -1)
box_plots.append(
Data_Point("T3", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveFr((self.length_of_box / 2) * -1)
box_plots.append(
Data_Point("T4", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveRi(self.length_of_box / 2)
box_plots.append(
Data_Point("T5", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveRi(self.length_of_box / 2)
box_plots.append(
Data_Point("T6", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveFr(self.length_of_box / 2)
box_plots.append(
Data_Point("T7", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveFr(self.length_of_box / 2)
box_plots.append(
Data_Point("T8", self.drone.x, self.drone.y, self.drone.z,
Signal(self.drone).calcSS()))
self.drone.moveRi((self.length_of_box / 2) * -1)
self.drone.moveFr((self.length_of_box / 2) * -1)
return box_plots
def __combine_data_points_list(self, data_point_list1, data_point_list2):
"""
combines 2 models' data_points_list's item parameters.
"""
output_list = []
# combine data point attributes
for i in range(0, len(data_point_list1)):
data_point = Data_Point()
local_features_1 = data_point_list1[i].features_dict
local_features_2 = data_point_list2[i].features_dict
# populate local_features with {feature: count}
for key1, val1 in local_features_1.items():
data_point.features_dict[key1] = val1
for key2, val2 in local_features_2.items():
if key2 not in data_point.features_dict:
data_point.features_dict[key2] = val2
data_point.true_label_index = data_point_list1[i].true_label_index
data_point.index = i
output_list.append(data_point)
return output_list