fixed Data import

data/data.py

@@ -0,0 +1,68 @@
+# -*- encoding: utf8 -*-
+from PyQt4.QtGui import QColor
+import numpy as np
+import pyqtgraph as pg
+
+from BDSMathlib import FitFunctionCreator
+
+class Data:
+    def __init__(self, frequency=np.zeros(1), die_real=np.zeros(1), die_imag=np.zeros(1)):
+        self.frequency = frequency
+        self.epsilon = die_real + 1j * die_imag
+        self.frequency_fit = frequency[:]
+        self.epsilon_fit = die_real[:]*0 + 1j * die_imag[:]*0
+        myPen_imag = pg.mkPen(width=3, color=(255,255,127))
+        myPen_real = pg.mkPen(width=3, color=(51,255,127))
+
+        self.data_curve_imag = pg.PlotDataItem(x=[np.nan], y=[np.nan],pen=QColor(0,0,0,0), symbol='o',
+                                          symbolBrush=(255,127,0,127))
+        self.data_curve_real = pg.PlotDataItem(x=[np.nan], y=[np.nan],pen=QColor(0,0,0,0), symbol='s',
+                                          symbolBrush=(119,202,92,127))
+        self.fitted_curve_imag = pg.PlotDataItem(x=[np.nan], y=[np.nan], pen=myPen_imag)
+        self.fitted_curve_real = pg.PlotDataItem(x=[np.nan], y=[np.nan], pen=myPen_real)
+        self.length = len(frequency)
+        self.meta = dict()
+        self.fit_limits = [frequency.min(), frequency.max(), die_imag.min(), die_imag.max()]
+
+        self.fit_param = None
+        self.fit_funcs = None # list of fit functions
+        self.hide_funcs = None # remove these func from the data
+
+    def set_fit(self, param, funcs):
+        self.fit_funcs = funcs
+        self.hide_funcs = []
+        self.fit_param = param
+        fit_real, fit_imag = FitFunctionCreator().fitfcn(param, self.frequency_fit, *funcs)
+        self.epsilon_fit = fit_real+1j*fit_imag
+
+    def set_data(self,f,e_real,e_imag):
+        self.frequency = f
+        self.frequency_fit = f[:]
+        self.epsilon = e_real + 1j*e_imag
+        self.epsilon_fit  =  0*e_real + 1j*e_imag*0
+        self.fit_limits = [f.min(), f.max(), e_imag.min(), e_imag.max()]
+        self.data_curve_imag.setData(f,e_imag)
+        self.data_curve_real.setData(f,e_real)
+
+    def set_fit_xlimits(self, xmin, xmax):
+        self.fit_limits[0] = xmin
+        self.fit_limits[1] = xmax
+        self.frequency_fit = self.frequency[(self.frequency <= xmax) & (self.frequency >= xmin)]
+
+    def set_fit_ylimits(self, ymin, ymax):
+        self.fit_limits[2] = ymin
+        self.fit_limits[3] = ymax
+
+    def get_data(self):
+        #mask = np.ones(len(self.frequency), dtype='bool')
+        mask = (self.frequency > self.fit_limits[0]) & (self.frequency < self.fit_limits[1])
+        #mask &= (self.epsilon.imag > self.fit_limits[2]) & (self.epsilon.imag < self.fit_limits[3])
+        return self.frequency[mask], self.epsilon[mask]
+
+    def remove_curves(self):
+        print "remove data_curve"
+        #if self.data_curve is not None: self.data_curve.remove()
+        print "remove fitted_curve"
+        #if self.fitted_curve is not None: self.fitted_curve.remove()
+
+