71 lines
2.8 KiB
Python
71 lines
2.8 KiB
Python
# -*- encoding: utf8 -*-
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from PyQt4.QtGui import QColor
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import numpy as np
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import pyqtgraph as pg
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from Mathlib import FitFunctionCreator
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class Data:
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def __init__(self, frequency=np.zeros(1), die_real=np.zeros(1), die_imag=np.zeros(1)):
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self.frequency = frequency
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self.epsilon = die_real + 1j * die_imag
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self.frequency_fit = frequency[:]
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self.epsilon_fit = die_real[:]*0 + 1j * die_imag[:]*0
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myPen_imag = pg.mkPen(width=3, color=(255,255,127))
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myPen_real = pg.mkPen(width=3, color=(51,255,127))
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self.data_curve_imag = pg.PlotDataItem(x=[np.nan], y=[np.nan],pen=QColor(0,0,0,0), symbol='o',
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symbolBrush=(255,127,0,127))
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self.data_curve_real = pg.PlotDataItem(x=[np.nan], y=[np.nan],pen=QColor(0,0,0,0), symbol='s',
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symbolBrush=(119,202,92,127))
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self.fitted_curve_imag = pg.PlotDataItem(x=[np.nan], y=[np.nan], pen=myPen_imag)
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self.fitted_curve_real = pg.PlotDataItem(x=[np.nan], y=[np.nan], pen=myPen_real)
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self.length = len(frequency)
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self.meta = dict()
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self.fit_limits = [frequency.min(), frequency.max(), die_imag.min(), die_imag.max()]
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self.fit_param = None
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self.fit_funcs = None # list of fit functions
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self.hide_funcs = None # remove these func from the data
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def set_fit(self, param, funcs):
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self.fit_funcs = funcs
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self.hide_funcs = []
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self.fit_param = param
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fit_real, fit_imag = FitFunctionCreator().fitfcn(param, self.frequency_fit, *funcs)
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self.epsilon_fit = fit_real + 1j*fit_imag
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def set_data(self,f,e_real,e_imag):
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self.frequency = f
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self.frequency_fit = f[:]
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self.epsilon = e_real + 1j*e_imag
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self.epsilon_fit = 0*e_real + 1j*e_imag*0
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self.fit_limits = [f.min(), f.max(), e_imag.min(), e_imag.max()]
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self.data_curve_imag.setData(f,e_imag)
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self.data_curve_real.setData(f,e_real)
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def set_fit_xlimits(self, xmin, xmax):
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self.fit_limits[0] = xmin
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self.fit_limits[1] = xmax
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self.frequency_fit = self.frequency[(self.frequency <= xmax) & (self.frequency >= xmin)]
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def set_fit_ylimits(self, ymin, ymax):
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self.fit_limits[2] = ymin
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self.fit_limits[3] = ymax
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def get_data(self):
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#mask = np.ones(len(self.frequency), dtype='bool')
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mask = (self.frequency > self.fit_limits[0]) & (self.frequency < self.fit_limits[1])
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#mask &= (self.epsilon.imag > self.fit_limits[2]) & (self.epsilon.imag < self.fit_limits[3])
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return self.frequency[mask], self.epsilon[mask]
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def remove_curves(self):
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print "remove data_curve"
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#if self.data_curve is not None: self.data_curve.remove()
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print "remove fitted_curve"
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#if self.fitted_curve is not None: self.fitted_curve.remove()
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