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fix: исправлены предупреждения Codacy

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This commit is contained in:
Maxim Slipenko 2024-02-11 18:23:59 +03:00
parent 5b6597463c
commit 91acacfb5c
1 changed files with 17 additions and 14 deletions
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29
statapp/distribution_window.py
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@ -20,7 +20,7 @@ class DistributionWindow(QDialog):
self.comboBox = QComboBox()
self.comboBox.addItems(self.values)
self.comboBox.currentIndexChanged.connect(self.on_change)
self.comboBox.currentIndexChanged.connect(self.onChange)
self.sc = self.getSc(data[:, 0])
self.layout.addWidget(self.comboBox)
@ -29,7 +29,7 @@ class DistributionWindow(QDialog):
self.layout.addLayout(self.l)
def on_change(self):
def onChange(self):
while ((child := self.l.takeAt(0)) != None):
child.widget().deleteLater()
self.sc = self.getSc(self.data[:, self.comboBox.currentIndex()])
@ -43,16 +43,19 @@ class UniformDistributionWindow(DistributionWindow):
def getSc(self, points):
sc = MplCanvas(self, width=5, height=4, dpi=100)
points = np.sort(points)
unique_points = np.array([points[0]] + [pt for pt, next_pt in zip(points[:-1], points[1:]) if pt != next_pt])
differences = np.diff(unique_points)
inverse_differences = 1 / differences
for i, (start, end) in enumerate(zip(unique_points[:-1], unique_points[1:])):
sc.axes.hlines(inverse_differences[i], start, end, colors='r', linestyles='solid')
points = np.array(
[points[0]] +
[pt for pt, next_pt in zip(points[:-1], points[1:]) if pt != next_pt]
)
differences = np.diff(points)
inverseDifferences = 1 / differences
for i, (start, end) in enumerate(zip(points[:-1], points[1:])):
sc.axes.hlines(inverseDifferences[i], start, end, colors='r', linestyles='solid')
return sc
def normal_density(x, mu, sigma_squared):
return 1 / np.sqrt(2 * np.pi * sigma_squared) * np.exp(-(x - mu)**2 / (2 * sigma_squared))
def normalDensity(x, mu, sigmaSquared):
return 1 / np.sqrt(2 * np.pi * sigmaSquared) * np.exp(-(x - mu) ** 2 / (2 * sigmaSquared))
class NormalDistributionWindow(DistributionWindow):
@ -63,8 +66,8 @@ class NormalDistributionWindow(DistributionWindow):
sc = MplCanvas(self, width=5, height=4, dpi=100)
points = np.sort(points)
mu = np.mean(points)
sigma_squared = np.var(points)
y_values = normal_density(points, mu, sigma_squared)
sigmaSquared = np.var(points)
y_values = normalDensity(points, mu, sigmaSquared)
sc.axes.plot(points, y_values)
@ -79,7 +82,7 @@ class ExponentialDistributionWindow(DistributionWindow):
sc = MplCanvas(self, width=5, height=4, dpi=100)
points = np.sort(points)
mu = np.mean(points)
lambda_param = 1 / mu
y_values = lambda_param * np.exp(-lambda_param * points)
lambdaParam = 1 / mu
y_values = lambdaParam * np.exp(-lambdaParam * points)
sc.axes.plot(points, y_values)
return sc