def __init__(self, parent, counter, modelid, active_parms, tau=None):
""" Initialize with given parameters. """
wx.Panel.__init__(self, parent=parent, id=wx.ID_ANY)
self.parent = parent
self.corr = Correlation(fit_model=modelid)
if tau is not None:
self.corr.lag_time = tau
# active_parameters:
# [0] labels
# [1] values
# [2] bool values to fit
self.corr.fit_parameters = active_parms[1]
self.corr.fit_parameters_variable = active_parms[2]
self._bgselected = None
self._bg2selected = None
self.FitKnots = 5 # number of knots for spline fit or similiars
self.weighted_fittype_id = 0 # integer (drop down item)
self.weighted_nuvar = 3 # bins for std-dev. (left and rigth)
# The weights that are plotted in the page
# This is set by the PlotAll function
self.weights_plot_fill_area = None
# A list containing page numbers that share parameters with this page.
# This parameter is defined by the global fitting tool and is saved in
# sessions.
self.GlobalParameterShare = []
# Counts number of Pages already created:
self.counter = counter
# Has inital plot been performed?
# Call PlotAll("init") to set this to true. If it is true, then
# nothing will be plotted if called with "init"
self.InitialPlot = False
# Model we are using
# Tool statistics uses this list:
self.StatisticsCheckboxes = None
# Splitter window
# Sizes
size = parent.notebook.GetSize()
tabsize = 33
size[1] = size[1] - tabsize
self.sizepanelx = 270
canvasx = size[0] - self.sizepanelx + 5
sizepanel = (self.sizepanelx, size[1])
sizecanvas = (canvasx, size[1])
self.sp = wx.SplitterWindow(self, size=size, style=wx.SP_3DSASH)
# This is necessary to prevent "Unsplit" of the SplitterWindow:
self.sp.SetMinimumPaneSize(1)
# Settings Section (left side)
#self.panelsettings = wx.Panel(self.sp, size=sizepanel)
self.panelsettings = scrolled.ScrolledPanel(self.sp, size=sizepanel)
self.panelsettings.SetupScrolling(scroll_x=False)
# Setting up Plot (correlation + chi**2)
self.spcanvas = wx.SplitterWindow(self.sp,
size=sizecanvas,
style=wx.SP_3DSASH)
# This is necessary to prevent "Unsplit" of the SplitterWindow:
self.spcanvas.SetMinimumPaneSize(1)
# y difference in pixels between Auocorrelation and Residuals
cupsizey = size[1] * 4 / 5
# Calculate initial data
self.calculate_corr()
# Draw the settings section
self.settings()
# Load default values
self.apply_parameters_reverse()
# Upper Plot for plotting of Correlation Function
self.canvascorr = plot.PlotCanvas(self.spcanvas)
self.canvascorr.logScale = (True, False)
self.canvascorr.enableZoom = True
self.PlotAll(event="init", trigger="tab_init")
self.canvascorr.SetSize((canvasx, cupsizey))
# Lower Plot for plotting of the residuals
self.canvaserr = plot.PlotCanvas(self.spcanvas)
self.canvaserr.logScale = (True, False)
self.canvaserr.enableZoom = True
self.canvaserr.SetSize((canvasx, size[1] - cupsizey))
self.spcanvas.SplitHorizontally(self.canvascorr, self.canvaserr,
cupsizey)
self.sp.SplitVertically(self.panelsettings, self.spcanvas,
self.sizepanelx)
# Bind resizing to resizing function.
wx.EVT_SIZE(self, self.OnSize)