forked from SeyitOzanOzdil/PIVA
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Distributions.py
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Distributions.py
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# -*- coding: utf-8 -*-
import numpy as np
from scipy import stats
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QTAgg as NavigationToolbar
from matplotlib.figure import Figure
from PyQt4 import QtCore, QtGui
#alpha global tanimlanabilir
# NOTE: PROBABILITY HESAPLARINDA UPPER TAIL SONUCU = 1-LOWER TAIL SONUCU
#---NORMAL DISTRIBUTION
#Normal Quantiles
#Olasiliklar dizisini (0-1 arasinda olmali), mean ve standart sapmayi parametre olarak aliyor
def NormalQuantilesLowerTail(probs, mean, std):
if len(probs)>0 and std>0:
outputStr = ""
yArray = []
for prob in probs:
outputStr += str(prob)
if prob>0 and prob<1:
rv = stats.norm(loc = mean, scale = std)
y = rv.ppf(prob)
y = "{0:.5f}".format(y)
yArray.append(y)
else:
yArray.append("NaN")
if len(probs) >1 and probs.index(prob) < len(probs) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", mean: " + str(mean) + ", standart sapma: " + str(std)
return outputStr, yArray
elif std <= 0 :
return False, "Standart sapma 0'dan kucuk olamaz."
else:
return False, "Gecerli olasilik degeri girilmelidir."
#Normal Probabilities
def NormalProbabilitiesLowerTail(variables, mean, std):
if len(variables) >0 and std>0:
outputStr = ""
areas = []
for var in variables:
outputStr += str(var)
rv= stats.norm(loc = mean, scale = std)
area = rv.cdf(var)
area = "{0:.5f}".format(area)
areas.append(area)
if len(variables) >1 and variables.index(var) < len(variables) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", mean: " + str(mean) + ", standart sapma: " + str(std)
return outputStr, areas
elif std <= 0:
return False, "Standart sapma 0'dan kucuk olamaz."
else:
return False, "Hesaplama icin gecerli deger(ler) verilmelidir."
#Plot Normal Distribution
#mean ve standart sapmayi parametre olarak aliyor.
def PlotNormalDistributionDensityFunction(mean, std):
if std>0:
#gruplanacak fonk icinde
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
axes.clear()
#ortak olmayan kisim
q = 0.0005 #lower or upper tail olasiligi
sequance = stats.norm.isf(q)
x = np.linspace(-std*sequance, std*sequance, 100) #100 rasgele degisken
gaussian = stats.norm(loc = mean, scale = std) #mean ve std'ye gore normal dagilim
y = gaussian.pdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Standart sapma 0'dan kucuk olamaz."
#mean ve standart sapmayi parametre olarak aliyor.
def PlotNormalDistributionDistributionFunction(mean, std):
if std>0:
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
axes.clear()
q = 0.0005 #lower or upper tail olasiligi
sequance = stats.norm.isf(q)
x = np.linspace(-sequance*3, sequance*3, 100) #100 rasgele degisken
gaussian = stats.norm(loc = mean, scale = std) #mean ve std'ye gore normal da??l?m
y = gaussian.cdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Standart sapma 0'dan kucuk olamaz."
#---/NORMAL DISTRIBUTION
#---T DISTRIBUTION
#olasiliklar dizisi ve degrees of freedom parametresi aliyor
def TQuantilesLowerTail(probs, df):
if len(probs)>0 and df>0:
outputStr = ""
yArray = []
for prob in probs:
outputStr += str(prob)
if prob> 0 and prob<1:
rv = stats.t(df, loc = 0, scale = 1)
y = rv.ppf(prob)
y = "{0:.5f}".format(y)
yArray.append(y)
else:
yArray.append("NaN")
if len(probs) >1 and probs.index(prob) < len(probs) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", serbestlik derecesi: " + str(df)
return outputStr, yArray
elif df<=0:
return False, "Serbestlik derecesi 0'dan kucuk olamaz."
else:
return False, "Gecerli olasilik degeri girilmelidir."
def TProbabilitiesLowerTail(values, df):
if len(values)>0 and df>0:
outputStr = ""
areas = []
for val in values:
outputStr += str(val)
rv= stats.t(df, loc = 0, scale = 1) #default loc ve scale degerleri
area = rv.cdf(val)
area = "{0:.5f}".format(area)
areas.append(area)
if len(values) >1 and values.index(val) < len(values) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", serbestlik derecesi: " + str(df)
return outputStr, areas
elif df <= 0:
return False, "Standart sapma 0'dan kucuk olamaz."
else:
return False, "Hesaplama icin gecerli degerler girilmelidir."
# df = degrees of freedom parametresi aliyor
def PlotTDistributionDensityFunction(df):
if df>0:
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
axes.clear()
alpha = 0.0005 #R'da o sekilde alinmis, burada da ayni olmasi icin bu deger verildi
sequance = stats.t.isf(alpha, df)
x = np.linspace(-sequance, sequance, 100) #100 adet veri default verildi
rv = stats.t(df)
y = rv.pdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Serbestlik derecesi 0'dan kucuk olamaz."
# df = degrees of freedom parametresi aliyor
def PlotTDistributionDistributionFunction(df):
if df>0:
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
axes.clear()
alpha = 0.0005 #R'da o sekilde alinmis, burada da ayni olmas? icin bu deger verildi
sequance = stats.t.isf(alpha, df)
x = np.linspace(-sequance, sequance, 100) #100 adet veri default verildi
rv = stats.t(df)
y = rv.cdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Serbestlik derecesi 0'dan kucuk olamaz."
#---/T DISTRIBUTION
#---CHI-SQUARED DISTRIBUTION
# df = degrees of freedom parametresi aliyor
def Chi2QuantilesLowerTail(probs, df):
if len(probs)>0 and df>0:
outputStr = ""
yArray = []
for prob in probs:
outputStr += str(prob)
if prob> 0 and prob<1:
rv = stats.chi2(df, loc = 0, scale = 1)
y = rv.ppf(prob)
y = "{0:.5f}".format(y)
yArray.append(y)
else:
yArray.append("NaN")
if len(probs) >1 and probs.index(prob) < len(probs) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", serbestlik derecesi: " + str(df)
return outputStr, yArray
elif df<=0:
return False, "Standart sapma 0'dan kucuk olamaz."
else:
return False, "Gecerli olasilik degeri girilmelidir."
def Chi2ProbabilitiesLowerTail(values, df):
if len(values)>0 and df>0:
outputStr = ""
areas = []
for val in values:
outputStr += str(val)
rv = stats.chi2(df, loc=0, scale=1)
area = rv.cdf(val)
area = "{0:.5f}".format(area)
areas.append(area)
if len(values) >1 and values.index(val) < len(values) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", serbestlik derecesi: " + str(df)
return outputStr, areas
elif df<=0:
return False, "Standart sapma 0'dan kucuk olamaz."
else:
return False, "Gecerli olasilik degeri girilmelidir."
def PlotChi2DistributionDensityFunction(df):
if df>0:
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
axes.clear()
alpha = 0.0005
sequence = stats.chi2.isf(alpha, df)
x = np.linspace(-sequence, sequence, 1000)
rv = stats.chi2(df)
y = rv.pdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Serbestlik derecesi 0'dan kucuk olamaz."
def PlotChi2DistributionDistributionFunction(df):
if df>0:
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
alpha = 0.0005
sequence = stats.chi2.isf(alpha, df)
x = np.linspace(-sequence, sequence, 1000)
rv = stats.chi2(df)
y = rv.cdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Serbestlik derecesi 0'dan kucuk olamaz."
#---/CHI-SQUARED DISTRIBUTION
#---F DISTRIBUTION
#dfn = degrees of freedom numerator, dfd = degrees of freedom denominator
def FQuantilesLowerTail(probs,dfn,dfd):
if len(probs)>0 and dfn>0 and dfd>0:
outputStr = ""
yArray = []
for prob in probs:
outputStr += str(prob)
if prob> 0 and prob<1:
rv = stats.f(dfn,dfd, loc = 0, scale = 1)
y = rv.ppf(prob)
y = "{0:.5f}".format(y)
yArray.append(y)
else:
yArray.append("NaN")
if len(probs) >1 and probs.index(prob) < len(probs) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", serbestlik derecesi (pay): " + str(dfn) + ", serbestlik derecesi (payda): " + str(dfd)
return outputStr, yArray
elif dfn<=0 or dfd <=0:
return False, "Serbestlik dereceleri 0'dan kucuk olamaz."
else:
return False, "Gecerli olasilik degeri girilmelidir."
def FProbabilitiesLowerTail(values, dfn, dfd):
if len(values)>0 and dfn>0 and dfd>0:
outputStr = ""
areas = []
for val in values:
outputStr += str(val)
rv = stats.f(dfn, dfd, loc = 0, scale=1)
area = rv.cdf(val)
area = "{0:.5f}".format(area)
areas.append(area)
if len(values) >1 and values.index(val) < len(values) - 1 :
outputStr += ", "
else:
outputStr += ""
outputStr += ", serbestlik derecesi (pay): " + str(dfn) + ", serbestlik derecesi (payda): " + str(dfd)
return outputStr, areas
elif dfn<=0 or dfd<=0:
return False, "Serbestlik dereceleri 0'dan kucuk olamaz."
else:
return False, "Hesaplama icin gecerli degerler girilmelidir."
def PlotFDistributionDensityFunction(dfn, dfd):
if dfn>0 and dfd>0:
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
alpha = 0.0005
sequence = stats.f.isf(alpha, dfn, dfd)
x = np.linspace(-sequence, sequence, 1000)
rv = stats.f(dfn, dfd)
y = rv.pdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Serbestlik derecesi 0'dan kucuk olamaz."
#dfn = degrees of freedom numerator, dfd = degrees of freedom denominator
def PlotFDistributionDistributionFunction(dfn, dfd):
if dfn>0 and dfd>0:
main_frame = QtGui.QWidget()
dpi = 100
fig = Figure((5.0, 4.0), dpi=dpi)
canvas = FigureCanvas(fig)
canvas.setParent(main_frame)
axes = fig.add_subplot(111)
mpl_toolbar = NavigationToolbar(canvas, main_frame)
hbox = QtGui.QHBoxLayout()
vbox = QtGui.QVBoxLayout()
vbox.addWidget(canvas)
vbox.addWidget(mpl_toolbar)
vbox.addLayout(hbox)
main_frame.setLayout(vbox)
alpha = 0.0005
sequence = stats.f.isf(alpha, dfn, dfd)
x = np.linspace(-sequence, sequence, 1000)
rv = stats.f(dfn, dfd)
y = rv.cdf(x)
axes.plot(x,y)
canvas.draw()
return main_frame
else:
return False, "Serbestlik derecesi 0'dan kucuk olamaz."
#---/F DISTRIBUTION