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#!/usr/bin/env python
'''
mcplot script for testing the ifit interface.
'''
import argparse
import logging
import os
import sys
import numpy as np
import pyqtgraph as pg
sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..'))
from mccodelib import pqtgfrontend
from mccodelib import plotgraph
'''
Local plotting functions
'''
def plot_iData_1D(data, plt, log=False, legend=True, icolormap=0, verbose=True, legend_fontsize=10):
''' create a plotItem and populate it with data, Data1D '''
# data
#x = np.array(data.axesvals).astype(np.float)
x = data.axesvals[0]
y = data.signal
e = data.error
if log:
nonzeros=[]
zeros=[]
for i in range(len(y)):
if y[i]>0:
nonzeros.append(i)
else:
zeros.append(i)
if len(nonzeros)>0:
y[zeros] = np.min(y[nonzeros])/10
plt.setLogMode(y=True)
else:
plt.setLogMode(y=False)
else:
plt.setLogMode(y=False)
plt.setXRange(np.min(x), np.max(x), padding=0)
# labels
#plt.setLabels(title=" ",bottom=data.xlabel, left=data.ylabel)
# how to add labels with html styling:
#plt.titleLabel.item.setHtml('<span style="font-size:5pt; text-align:center;color:#FFFFFF">data.component <br>hest</span>')
#axis_style = {'color': '#FFF', 'font-size': '5pt'}
#plt.setLabel(axis='left', text=data.ylabel, **axis_style)
#plt.setLabel(axis='bottom', text=data.xlabel, **axis_style)
# error bars
beam = 0
if len(x) > 1:
beam = (x[1]-x[0])*0.5
# TODO: Find solution for adding errorbars in the log case
if not log:
err = pg.ErrorBarItem(x=x, y=y, height=e, beam=beam)
plt.addItem(err)
# plots data
plt.plot(x, y)
plt.setMenuEnabled(False)
vb = plt.getViewBox()
return vb
def plot_iData_2D(data, plt, log=False, legend=True, icolormap=0, verbose=True, legend_fontsize=10):
''' create a layout and populate a plotItem with data Data2D, adding a color bar '''
# data
img = pg.ImageItem()
dataset = np.array(data.signal)
x = data.axesvals[0]
y = data.axesvals[1]
dataset = np.transpose(dataset)
img.setImage(dataset)
# scale(x,y) is in %, translate(x,y) is in the original units
dx = (np.max(x) - np.min(x))/len(x)
dy = (np.max(y) - np.min(y))/len(y)
img.scale(dx,dy)
# Calculate translation in original pixel units
img.translate(np.min(x)/dx, np.min(y)/dy)
# color map (by lookup table)
pos_min = np.min(dataset)
pos_max = np.max(dataset)
# color map
cm = np.array([[ 0, 0, 143, 255], [ 0, 0, 159, 255], [ 0, 0, 175, 255], [ 0, 0, 191, 255], [ 0, 0, 207, 255], [ 0, 0, 223, 255], [ 0, 0, 239, 255], [ 0, 0, 255, 255], [ 0, 16, 255, 255], [ 0, 32, 255, 255], [ 0, 48, 255, 255], [ 0, 64, 255, 255], [ 0, 80, 255, 255], [ 0, 96, 255, 255], [ 0, 112, 255, 255], [ 0, 128, 255, 255], [ 0, 143, 255, 255], [ 0, 159, 255, 255], [ 0, 175, 255, 255], [ 0, 191, 255, 255], [ 0, 207, 255, 255], [ 0, 223, 255, 255], [ 0, 239, 255, 255], [ 0, 255, 255, 255], [ 16, 255, 239, 255], [ 32, 255, 223, 255], [ 48, 255, 207, 255], [ 64, 255, 191, 255], [ 80, 255, 175, 255], [ 96, 255, 159, 255], [112, 255, 143, 255], [128, 255, 128, 255], [143, 255, 112, 255], [159, 255, 96, 255], [175, 255, 80, 255], [191, 255, 64, 255], [207, 255, 48, 255], [223, 255, 32, 255], [239, 255, 16, 255], [255, 255, 0, 255], [255, 239, 0, 255], [255, 223, 0, 255], [255, 207, 0, 255], [255, 191, 0, 255], [255, 175, 0, 255], [255, 159, 0, 255], [255, 143, 0, 255], [255, 128, 0, 255], [255, 112, 0, 255], [255, 96, 0, 255], [255, 80, 0, 255], [255, 64, 0, 255], [255, 48, 0, 255], [255, 32, 0, 255], [255, 16, 0, 255], [255, 0, 0, 255], [239, 0, 0, 255], [223, 0, 0, 255], [207, 0, 0, 255], [191, 0, 0, 255], [175, 0, 0, 255], [159, 0, 0, 255], [143, 0, 0, 255], [128, 0, 0, 255]], dtype=np.ubyte)
pos = pos_min + (pos_max - pos_min) * np.arange(len(cm))/(len(cm)-1)
colormap = pg.ColorMap(pos, cm)
lut = colormap.getLookupTable(pos_min, pos_max, 256)
img.setLookupTable(lut)
plt.setMenuEnabled(False)
plt.addItem(img)
# Set the x and y ranges correctly
plt.getViewBox().setXRange(np.min(x), np.max(x), padding=0)
plt.getViewBox().setYRange(np.min(y), np.max(y), padding=0)
return plt.getViewBox()
def plot(node, i, plt, opts):
'''
plug-in function used by plotter ui called PyQtGraphFrontend
node : plot node containing data
i : index of said data in node
opts : dict containing options such as --> log, legend, icolormap, verbose, legend_fontsize
'''
if type(node) == plotgraph.PNSingle and i != 0:
raise Exception("inconsistent plot request, idx=%s" % str(i))
data = node.getdata_idx(i)
plotfunc = None
if len(data.axesvals) == 1:
plotfunc = plot_iData_1D
elif len(data.axesvals) == 2:
plotfunc = plot_iData_2D
else:
raise Exception("three- or higher dimensional plotting not supported on this device")
view_box = plotfunc(data, plt, log=opts['log'], legend=opts['legend'], icolormap=opts['icolormap'], verbose=opts['verbose'], legend_fontsize=opts['fontsize'])
return view_box, plt
'''
iFit interface classes
'''
class IDataShadow:
def __init__(self, signal, error, monitor, axesvals):
self.signal = signal
self.error = error
self.monitor = monitor
self.axesvals = axesvals
class IFuncShadow:
def __init__(self, definition):
self.definition = definition
class IFitInterfaceOfficial:
'''
The lowest level above matlab, with special functions for getting
data out of iFit objects of type iData and iFunc.
'''
def __init__(self):
import matlab.engine # official mathworks impl
self.eng = matlab.engine.start_matlab('-nodesktop -nosplash', async=False)
self.eng.eval("addpath(genpath('/home/jaga/source/REPO_ifit'))")
def get_idata(self, varname):
''' load axes, signal and error from an ifit idata object '''
ndims = self.eng.eval('ndims(%s)' % varname)
ndims = int(ndims)
signal = None
error = None
axes_names = self.eng.eval('%s.Axes' % varname, nargout=1) # NOTE: len(axes_names) == ndims
axesvals = []
if not ndims == len(axes_names):
# TODO: handle this case seperately, in which ifit has not found any axes in the data
raise Exception("ifit could not find axes")
# get signal
if ndims == 1:
xvals = np.array(self.eng.eval('a.%s' % axes_names[0])[0]).astype(np.float)
axesvals.append(xvals)
signal = np.array(self.eng.eval('%s.Signal' % varname, nargout=1)).astype(np.float)
signal = np.reshape(signal, (1, len(signal)))[0].tolist()
error = np.array(self.eng.eval('%s.Error' % varname, nargout=1)).astype(np.float)
error = np.reshape(error, (1, len(error)))[0]
# TODO: what about monitor?
#monitor = np.array(self.eng.eval('%s.Monitor' % varname, nargout=1))
#monitor = np.reshape(monitor, (1, len(monitor)))[0]
#monitor = None
elif ndims == 2:
xvals = np.array(self.eng.eval('a.%s' % axes_names[0])[0]).astype(np.float)
yvals = np.array(self.eng.eval('a.%s' % axes_names[1])[0]).astype(np.float)
axesvals.append(xvals)
axesvals.append(yvals)
signal = np.array(self.eng.eval('%s.Signal' % varname, nargout=1)).astype(np.float)
error = np.array(self.eng.eval('%s.Error' % varname, nargout=1)).astype(np.float)
else:
for i in range(ndims):
ivals = np.array(self.eng.eval('a.%s' % axes_names[i])[0]).astype(np.float)
axesvals.append(ivals)
signal = np.array(self.eng.eval('%s.Signal' % varname, nargout=1)).astype(np.float)
error = np.array(self.eng.eval('%s.Error' % varname, nargout=1)).astype(np.float)
return IDataShadow(signal, error, None, axesvals)
def get_ifunc(self, varname):
definition = self.eng.eval('%s.Signal' % varname, nargout=1)
return IFuncShadow(definition)
def get(self, varname):
something = self.eng.eval('%s' % varname, nargout=1)
return something
def assign(self, varname, expression):
self.eng.eval("%s = %s" % (varname, expression), nargout=0)
def eval(self, expression):
self.eng.eval("" % expression, nargout=1)
class IFitInterface:
'''
The lowest level above matlab, with special functions for getting
data out of iFit objects of type iData and iFunc.
'''
def __init__(self):
import matlab_ef # Emmanuel Farhi's matlab interface
self.eng = matlab_ef.Matlab()
def get_idata(self, varname):
signal = np.array(self.eng.get('%s.Signal' % varname))
error = np.array(self.eng.get('%s.Error' % varname))
monitor = None # np.array(self.eng.eval('%s.Monitor' % varname))
axes_names = self.eng.get('%s.Axes' % varname)
firstaxes_vals = np.array(self.eng.get('a.%s' % axes_names))
return IDataShadow(signal, error, monitor, firstaxes_vals)
def get_ifunc(self, varname):
definition = self.eng.get('%s.Signal' % varname)
return IFuncShadow(definition)
def get(self, varname):
something = self.eng.get('%s' % varname)
return something
def assign(self, varname, expression):
self.eng.eval("%s = %s" % (varname, expression))
def eval(self, expression):
self.eng.eval("" % expression)
'''
Local script classes
'''
class IFitLoaderSimple:
'''
loads 1D data from ifit and transforms this into a plotgraph.
'''
def __init__(self, datafile):
''' '''
#import matlab_ef # Emmanuel Farhi's matlab interface
self.datafile = datafile[0]
self.plot_graph = None
#self.interface = IFitInterface()
self.interface = IFitInterfaceOfficial()
if not os.path.exists(self.datafile):
raise Exception("requested file to load does not exist")
def load(self):
i = self.interface
i.assign('a', 'load(iData, \'%s\')' % self.datafile)
#i.assign('a', 'load(iData, [ ifitpath \'Data/sv1850.scn\' ])')
#i.assign('a', 'load(iData, \'\/home\/jaga\/source\/McCode\/tools\/Python\/mcplot\/fitlab\/100706.dat\')')
#ap = eng.eval('a.Signal', nargout=1)
iData = i.get_idata('a')
graph = plotgraph.PNSingle(plotgraph.DataHandle(load_fct=None, data=iData))
return graph
def main(args):
''' load data from iFit interface and send it to the pyqtgraph frontend '''
logging.basicConfig(level=logging.INFO)
# ensure keyboardinterrupt ctr-c
import signal
signal.signal(signal.SIGINT, signal.SIG_DFL)
try:
# load data
loader = IFitLoaderSimple(datafile=args.datafile)
graph = loader.load()
# run pqtg frontend
plotter = pqtgfrontend.McPyqtgraphPlotter(graph, sourcedir='/nosourcedir/', plot_func=plot, invcanvas=False)
plotter.runplot()
except KeyboardInterrupt:
print('keyboard interrupt')
except Exception as e:
print('mcplot error: %s' % e.__str__())
raise e
if __name__ == '__main__':
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('datafile', nargs='*', help='file to plot')
args = parser.parse_args()
main(args)
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