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controller.py
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controller.py
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import csv
from model import encode
from perceptron import Perceptron
class Controller:
def __init__(self, view, model):
self.view = view
self.model = model
# setting actions of view buttons
view.set_command("read", self.read)
view.set_command("train", self.train)
view.set_command("test", self.test)
view.set_command("classify", self.classify)
# reading csv files
def read(self):
try:
path = self.view.entries["trainpath"].get()
with open(path) as f:
reader = csv.reader(f, delimiter=';')
self.model.set_trainset(list(reader))
# Conversion of number type columns to float
for train in self.model.trainset:
self.model.add_class(train[-1])
for i in range(len(train) - 1):
train[i] = float(train[i])
# Set colors based on class name
self.model.set_train_colors([encode(row[-1]) for row in self.model.trainset])
path = self.view.entries["testpath"].get()
with open(path) as f:
reader = csv.reader(f, delimiter=';')
self.model.set_testset(list(reader))
# Conversion of number type columns to float
for test in self.model.testset:
self.model.get_category_by_name(test[-1]).increase_size()
for i in range(len(test) - 1):
test[i] = float(test[i])
# Set colors based on class name
self.model.set_test_colors([encode(row[-1]) for row in self.model.testset])
# Set dimensions of data in model
self.model.set_dimensions()
# UI feedback
self.view.get_entry("trainpath").config({"background": "pale green"})
self.view.get_entry("testpath").config({"background": "pale green"})
self.view.set_button_normal("train")
except FileNotFoundError:
# UI feedback
self.view.get_entry("trainpath").config({"background": "tomato"})
self.view.get_entry("testpath").config({"background": "tomato"})
def train(self):
alpha = float(self.view.get_entry("alpha").get())
self.model.set_perceptron(Perceptron(self.model, alpha))
self.view.set_button_normal("test")
self.view.set_button_normal("classify")
self.view.graphs.show_graphs(self.model.trainset, self.model.dimensions, self.model.train_colors,
self.model.perceptron, "train")
def test(self):
self.model.reset_scores()
self.view.graphs.show_graphs(self.model.testset, self.model.dimensions, self.model.test_colors,
self.model.perceptron, "test")
def classify(self):
data = self.view.get_entry("data").get().split(';')
data = [float(d) for d in data]
guess,_ = self.model.perceptron.classify(data)
self.view.get_label("guess").config(text="Classification result: " + guess)