def buildCategories(self):
multiclass_exp = self.buildMulticlassClassifier()
train = self.multiclass_model.datasets.train_instances
test = self.multiclass_model.datasets.test_instances
all_instances = copy.deepcopy(test)
all_instances.union(train)
if test.numInstances() > 0:
predicted_families = self.multiclass_model.testing_monitoring.getPredictedLabels()
all_families = list(predicted_families) + train.families
predicted_proba = self.multiclass_model.testing_monitoring.getAllPredictedProba()
for family in train.families:
probas = [int(family == s) for s in self.multiclass_model.class_labels]
predicted_proba = np.vstack((predicted_proba, np.array(probas)))
else:
all_families = self.annotated_instances.families
predicted_proba = None
for family in self.annotated_instances.families:
probas = [int(family == s) for s in self.multiclass_model.class_labels]
if predicted_proba is None:
predicted_proba = np.array(probas)
else:
predicted_proba = np.vstack((predicted_proba, np.array(probas)))
labels_values = list(self.multiclass_model.class_labels)
assigned_categories = [labels_values.index(x) for x in all_families]
self.categories = Categories(multiclass_exp,
all_instances,
assigned_categories,
predicted_proba,
self.label,
self.multiclass_model.class_labels)
def setCategories(self, all_instances, assigned_categories, predicted_proba):
self.categories = Categories(self.iteration,
all_instances,
assigned_categories,
predicted_proba,
self.label,
self.multiclass_model.class_labels)
def get_category_by_id(self, cat_id): if cat_id == None: return None Category = Categories(self.db) category = Category.find_by_id(cat_id) if not category: return None return category
def __init__(self, nTrial, nStim):
self.nTrial = nTrial
self.nStim = nStim
self.categs = Categories(nTrial, nStim)
self.stims = self.categs.encDF
# self.trials = data.TrialHandler(self.stims,
# 1,
# method='sequential')
self.poslist = []
def __init__(self,nTrial,nStim):
'''
Parameters
----------
nTrial: number of runs for a subject
nStim: number of new images used in each phase in a trial
'''
self.log = logging.LogFile(f='imTaskLogFile')
self.nTrial = nTrial
self.nStim = nStim
self.categs = Categories(nTrial,nStim)
self.encDict = self.categs.encDF.to_dict(orient="index")
self.recDict = self.categs.recDF.to_dict(orient="index")
self.stimpos = {'0':(-250.0, 250.0),
'1':(250.0, 250.0),
'2':(250.0, -250.0),
'3':(-250.0, -250.0)}
self.outputlist = []
self.encInstStartText = '''\
Memorize the following images and
their location on screen.
Press space to start.\
'''.format()
self.recInstStartText = '''\
A series of {x} images will appear.
Indicate if shown image corresponds to a previously seen image
and in which quadrant it has appeared earlier.
Press SPACE to start\
'''.format(x=self.nStim+1)
self.recInstText1 = '''\
Have you seen this picture before?
If yes, press "y". If not, press "n".\
'''.format()
self.recInstText2 = '''\
Where have you seen it?
Press 0, 1, 2 or 3 to answer\
'''.format()
self.recInstPosText = '''\
Where have you seen it?
0 = upper-left, 1 = upper-right
2 = lower-left, 3 = lower-right\
'''.format()
self.ansSaveText = 'Answer saved!'
self.endText = 'Thank you for your time, goodbye!'
def __init__(self, whichTrial, nTrial, nStim):
self.whichTrial = whichTrial
self.nTrial = nTrial
self.nStim = nStim
self.categs = Categories(nTrial, nStim)
self.encDict = self.categs.encDF.to_dict(orient="index")
self.thisEncTrial = self.encDict[self.whichTrial]
self.recDict = self.categs.recDF.to_dict(orient="index")
self.thisRecTrial = self.recDict[self.whichTrial]
self.thisTrialTarg = self.categs.Targs[self.whichTrial]
self.encStimlist = []
self.answerlist = []
self.stimpos = {
'0': (-250.0, 250.0),
'1': (250.0, 250.0),
'2': (250.0, -250.0),
'3': (-250.0, -250.0)
}
self.targetPos = self.getTargPos()
self.encInstStartText = '''\
Memorize the following images and
their location on screen.
Press space to start.\
'''.format()
self.recInstStartText = '''\
A series of {x} images will appear.
Indicate if shown image corresponds to a previously seen image
and in which quadrant it has appeared earlier.
Press SPACE to start\
'''.format(x=self.nStim + 1)
self.recInstText1 = '''\
Have you seen this picture before?
If yes, press "y". If not, press "n".\
'''.format()
self.recInstText2 = '''\
Where have you seen it?
Press 0, 1, 2 or 3 to answer\
'''.format()
self.recInstPosText = '''\
Where have you seen it?
0 = upper-left, 1 = upper-right
2 = lower-left, 3 = lower-right\
'''.format()
self.ansSaveText = 'Answer saved!'
self.endText = 'Thank you for your time, goodbye!'
def get_or_create_category_by_name(self, cat_name, gender=None, parent=None): if cat_name == None: return None if gender != None: gender = gender["id"] if parent != None: parent = parent["id"] Category = Categories(self.db) category = Category.find_by_name_and_gender(cat_name.strip(), gender) if not category: category = Category.save(cat_name.strip(), gender=gender, category=parent) if not category: return None return category
def adminMenu():
print(" ~~ Administration MAIN MENUE ~~\n\n")
print(" 1- Manage Categories")
print(" 2- Manage Products")
print(" 3- Manage Customers\n")
manageGRP = input("Please choose your option [1-3] >>")
# admin select manage categories
if manageGRP[:1] == '1':
clear()
Category = Categories()
Category.main()
# admin select manage Products
elif manageGRP[:1] == '2':
clear()
product = Products()
product.main()
# admin select manage Customers
elif manageGRP[:1] == '3':
clear()
# Category = Categories()
# Category.main()
else:
print("Invalid Option")
def __init__(self,nTrial,nStim):
self.nTrial = nTrial
self.nStim = nStim
self.categs = Categories(nTrial,nStim)
self.encResults = pd.read_csv(os.getcwd()+'\\stimDF.csv')
self.stims = self.categs.recDF
self.TargStims = self.categs.Targs
self.stimpos = {'0':np.array((-250.0, 250.0)),
'1':np.array((250.0, 250.0)),
'2':np.array((250.0, -250.0)),
'3':np.array((-250.0, -250.0))}
self.instStartText = '''\
... A series of {x} images will appear.
... Indicate if shown image corresponds to a previously seen image
... and in which quadrant it has appeared earlier.
... Press SPACE to start\
'''.format(x=len(self.stims)+1)
self.inst1Text = '''\
... Have you seen this picture before?
... If yes, press "y". If not, press "n".\
'''.format()
self.inst2Text = '''\
... Where have you seen it?
... Press 0, 1, 2 or 3 to answer\
'''.format()
self.instPosText = '''\
... Where have you seen it?
... 0 = upper-left, 1 = upper-right
... 2 = lower-left, 3 = lower-right\
'''.format()
self.ansSaveText = 'Answer saved!'
def __init__(self):
self.trials = data.TrialHandler(Categories(2, 5).trialslist,
1,
method='sequential')
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 22 00:37:31 2019
@author: Francois
"""
from psychopy import core
from psychopy import data
from psychopy import event
from psychopy import visual
from Categories import Categories
from randSign import randSign
trials = data.TrialHandler(Categories(2, 8).trialslist, 1, method='sequential')
def runtask(trials):
win = visual.Window(size=(1000, 1000), color=(0, 0, 0), units='pix')
eachTrial = 0
while eachTrial <= len(trials.trialList) - 1:
def encodingphase(
win
): # Shows stimuli in each trial list in "trials"(also list)
#stimpos = [(250.0, 250.0),(-250.0, -250.0),(250.0, -250.0),(-250.0, -250.0)] #Possibly replacing randSign()
instructionStart = visual.TextStim(
win,
text=
'Memorize the following images and their location on screen. Press space to start.'
def main(self):
product = Products()
self.clear()
print(" ***** Manage Products *****\n\n")
print(" 1- Add a new product")
print(" 2- Edit existing product")
print(" 3- Remove existing product\n")
productOperation = input("Please choose your option [1-3] >>")
if productOperation[:1] == '1':
category = Categories()
self.clear()
# Retrive real state data from database
print("Options:")
print(
"\n\n1- Choose a category from the existing categories to add your product to")
print("\n2- Add a new category to connect your product to")
option = input("\nPlease make a selection [1-2] >>")
if category.ValidateUserInputAsNumber(option):
option = int(option)
if(option == 1 or option == 2):
if(option == 1):
self.clear()
SQLStatment = category.selectStatment(
"*", "categories", "")
cursor = self.executeSQLStatment(SQLStatment)
rows = cursor.fetchall()
cursor.close()
print(
"-------------------------------------------------------------:")
print(
"---------------------- Categories List ----------------------")
#ProductCategory = Category()
if(rows):
counter = 0
for row in rows:
print(f"{counter+1} - {row[1]} ")
counter += 1
categoryNo = input(
"\n\nPlease enter a valid category from the list above>>")
if category.ValidateUserInputAsNumber(categoryNo):
categoryNo = int(categoryNo)
if(categoryNo > 0 and categoryNo <= counter and categoryNo is not None):
rowIndex = int(categoryNo)-1
category_id = int(rows[rowIndex][0])
print("\n\n ***New Product Information:***")
productName = input(
"Please enter the product name >> ")
productDescription = input(
"Please enter the product description >> ")
productPrice = input(
"Please enter the product price >> ")
self.addNewProduct(
category_id, productName, productDescription, productPrice)
else:
categoryName = input(
"Please enter the Category name that you want to add >>")
rows = category.addNewCategory(categoryName)
category_id = rows.fetchone()[0]
print("\n\n ***New Product Information:***")
productName = input(
"Please enter the product name >> ")
productDescription = input(
"Please enter the product description >> ")
productPrice = input(
"Please enter the product price >> ")
self.addNewProduct(
category_id, productName, productDescription, productPrice)
else:
print("invalid option")
elif productOperation[:1] == '2':
# self.EditProduct("Edit")
# self.editExistingProduct(
print("\n\n- Search Products by Name -")
productName = input(
"Please enter a keyword to search for Product Name >> ")
whereStatment = f"LOWER(product_name) like '%{productName}%' "
self.editExistingProduct(whereStatment)
elif productOperation[:1] == '3':
self.searchMainMenu("Delete")
else:
print("Invalid entry\n")
