def setUp(self):
super(TestStackViewMainWindow, self).setUp()
self.stackview = StackViewMainWindow()
self.stackview.show()
self.qWaitForWindowExposed(self.stackview)
self.mystack = numpy.fromfunction(
lambda i, j, k: numpy.sin(i / 15.) + numpy.cos(j / 4.) + 2 * numpy.
sin(k / 6.), (10, 20, 30))
def plot_data3D(self, data3D, dataE, dataX, dataY, tabs_canvas_index, plot_canvas_index, title="", xtitle="", ytitle=""):
for i in range(1+self.tab[tabs_canvas_index].layout().count()):
self.tab[tabs_canvas_index].layout().removeItem(self.tab[tabs_canvas_index].layout().itemAt(i))
#self.tab[tabs_canvas_index].layout().removeItem(self.tab[tabs_canvas_index].layout().itemAt(0))
xmin = numpy.min(dataX)
xmax = numpy.max(dataX)
ymin = numpy.min(dataY)
ymax = numpy.max(dataY)
origin = (xmin, ymin)
scale = (abs((xmax-xmin)/len(dataX)), abs((ymax-ymin)/len(dataY)))
dim0_calib = (dataE[0],dataE[1]-dataE[0])
dim1_calib = (ymin, dataY[1]-dataY[0])
dim2_calib = (xmin, dataX[1]-dataX[0])
data_to_plot = numpy.swapaxes(data3D,1,2)
colormap = {"name":"temperature", "normalization":"linear", "autoscale":True, "vmin":0, "vmax":0, "colors":256}
self.plot_canvas[plot_canvas_index] = StackViewMainWindow()
self.plot_canvas[plot_canvas_index].setGraphTitle(title)
self.plot_canvas[plot_canvas_index].setLabels(["Photon Energy [eV]",ytitle,xtitle])
self.plot_canvas[plot_canvas_index].setColormap(colormap=colormap)
self.plot_canvas[plot_canvas_index].setStack(numpy.array(data_to_plot),
calibrations=[dim0_calib, dim1_calib, dim2_calib] )
self.tab[tabs_canvas_index].layout().addWidget(self.plot_canvas[plot_canvas_index])
def plot_3D(self, data3D, dataE, dataX, dataY, progressBarValue, plot_canvas_index, title, xtitle, ytitle, xum="", yum=""):
if self.plot_canvas[plot_canvas_index] is None:
self.plot_canvas[plot_canvas_index] = StackViewMainWindow()
self.tab[plot_canvas_index].layout().addWidget(self.plot_canvas[plot_canvas_index])
xmin = numpy.min(dataX)
xmax = numpy.max(dataX)
ymin = numpy.min(dataY)
ymax = numpy.max(dataY)
stepX = dataX[1]-dataX[0]
stepY = dataY[1]-dataY[0]
if len(dataE) > 1: stepE = dataE[1]-dataE[0]
else: stepE = 1.0
if stepE == 0.0: stepE = 1.0
if stepX == 0.0: stepX = 1.0
if stepY == 0.0: stepY = 1.0
dim0_calib = (dataE[0],stepE)
dim1_calib = (ymin, stepY)
dim2_calib = (xmin, stepX)
data_to_plot = numpy.swapaxes(data3D, 1, 2)
colormap = {"name":"temperature", "normalization":"linear", "autoscale":True, "vmin":0, "vmax":0, "colors":256}
self.plot_canvas[plot_canvas_index].setGraphTitle(title)
self.plot_canvas[plot_canvas_index].setLabels(["Photon Energy [eV]",ytitle,xtitle])
self.plot_canvas[plot_canvas_index].setColormap(colormap=colormap)
self.plot_canvas[plot_canvas_index].setStack(numpy.array(data_to_plot),
calibrations=[dim0_calib, dim1_calib, dim2_calib] )
def setUp(self):
super(TestStackViewMainWindow, self).setUp()
self.stackview = StackViewMainWindow()
self.stackview.show()
self.qWaitForWindowExposed(self.stackview)
self.mystack = numpy.fromfunction(
lambda i, j, k: numpy.sin(i/15.) + numpy.cos(j/4.) + 2 * numpy.sin(k/6.),
(10, 20, 30)
)
def plot_data3D(self, data3D, dataE, dataX, dataY, tabs_canvas_index, plot_canvas_index,
title="", xtitle="", ytitle="", color_limits_uniform=False):
for i in range(1+self.tab[tabs_canvas_index].layout().count()):
self.tab[tabs_canvas_index].layout().removeItem(self.tab[tabs_canvas_index].layout().itemAt(i))
xmin = numpy.min(dataX)
xmax = numpy.max(dataX)
ymin = numpy.min(dataY)
ymax = numpy.max(dataY)
stepX = dataX[1]-dataX[0]
stepY = dataY[1]-dataY[0]
if len(dataE) > 1: stepE = dataE[1]-dataE[0]
else: stepE = 1.0
if stepE == 0.0: stepE = 1.0
if stepX == 0.0: stepX = 1.0
if stepY == 0.0: stepY = 1.0
dim0_calib = (dataE[0],stepE)
dim1_calib = (ymin, stepY)
dim2_calib = (xmin, stepX)
data_to_plot = numpy.swapaxes(data3D,1,2)
if color_limits_uniform:
colormap = {"name":"temperature", "normalization":"linear", "autoscale":False, "vmin":data3D.min(), "vmax":data3D.max(), "colors":256}
else:
colormap = {"name":"temperature", "normalization":"linear", "autoscale":True, "vmin":0, "vmax":0, "colors":256}
self.plot_canvas[plot_canvas_index] = StackViewMainWindow()
self.plot_canvas[plot_canvas_index].setGraphTitle(title)
self.plot_canvas[plot_canvas_index].setLabels(["Photon Energy [eV]",ytitle,xtitle])
self.plot_canvas[plot_canvas_index].setColormap(colormap=colormap)
self.plot_canvas[plot_canvas_index].setTitleCallback(lambda idx: "Energy: %6.3f eV"%dataE[idx])
self.plot_canvas[plot_canvas_index].setStack(numpy.array(data_to_plot),
calibrations=[dim0_calib, dim1_calib, dim2_calib] )
self.tab[tabs_canvas_index].layout().addWidget(self.plot_canvas[plot_canvas_index])
class TestStackViewMainWindow(TestCaseQt):
"""Base class for tests of StackView."""
def setUp(self):
super(TestStackViewMainWindow, self).setUp()
self.stackview = StackViewMainWindow()
self.stackview.show()
self.qWaitForWindowExposed(self.stackview)
self.mystack = numpy.fromfunction(
lambda i, j, k: numpy.sin(i/15.) + numpy.cos(j/4.) + 2 * numpy.sin(k/6.),
(10, 20, 30)
)
def tearDown(self):
self.stackview.setAttribute(qt.Qt.WA_DeleteOnClose)
self.stackview.close()
del self.stackview
super(TestStackViewMainWindow, self).tearDown()
def testSetStack(self):
self.stackview.setStack(self.mystack)
self.stackview.setColormap("viridis", autoscale=True)
my_trans_stack, params = self.stackview.getStack()
self.assertEqual(my_trans_stack.shape, self.mystack.shape)
self.assertTrue(numpy.array_equal(self.mystack,
my_trans_stack))
self.assertEqual(params["colormap"]["name"],
"viridis")
def testSetStackPerspective(self):
self.stackview.setStack(self.mystack, perspective=1)
my_trans_stack, params = self.stackview.getCurrentView()
# get stack returns the transposed data, depending on the perspective
self.assertEqual(my_trans_stack.shape,
(self.mystack.shape[1], self.mystack.shape[0], self.mystack.shape[2]))
self.assertTrue(numpy.array_equal(numpy.transpose(self.mystack, axes=(1, 0, 2)),
my_trans_stack))
#
# ###########################################################################*/
"""This script is a simple example to illustrate how to use the StackView
widget.
"""
import numpy
import sys
from silx.gui import qt
# from silx.gui.plot import StackView
from silx.gui.plot.StackView import StackViewMainWindow
app = qt.QApplication(sys.argv[1:])
x, y, z = numpy.meshgrid(numpy.linspace(-10, 10, 200),
numpy.linspace(-10, 5, 150),
numpy.linspace(-5, 10, 120),
indexing="ij")
mystack = numpy.asarray(numpy.sin(x * y * z) / (x * y * z),
dtype='float32')
# sv = StackView()
sv = StackViewMainWindow()
sv.setColormap("jet", autoscale=True)
sv.setStack(mystack)
sv.setLabels(["x: -10 to 10 (200 samples)",
"y: -10 to 5 (150 samples)",
"z: -5 to 10 (120 samples)"])
sv.show()
app.exec_()
class TestStackViewMainWindow(TestCaseQt):
"""Base class for tests of StackView."""
def setUp(self):
super(TestStackViewMainWindow, self).setUp()
self.stackview = StackViewMainWindow()
self.stackview.show()
self.qWaitForWindowExposed(self.stackview)
self.mystack = numpy.fromfunction(
lambda i, j, k: numpy.sin(i / 15.) + numpy.cos(j / 4.) + 2 * numpy.
sin(k / 6.), (10, 20, 30))
def tearDown(self):
self.stackview.setAttribute(qt.Qt.WA_DeleteOnClose)
self.stackview.close()
del self.stackview
super(TestStackViewMainWindow, self).tearDown()
def testSetStack(self):
self.stackview.setStack(self.mystack)
self.stackview.setColormap("viridis", autoscale=True)
my_trans_stack, params = self.stackview.getStack()
self.assertEqual(my_trans_stack.shape, self.mystack.shape)
self.assertTrue(numpy.array_equal(self.mystack, my_trans_stack))
self.assertEqual(params["colormap"]["name"], "viridis")
def testSetStackPerspective(self):
self.stackview.setStack(self.mystack, perspective=1)
my_trans_stack, params = self.stackview.getCurrentView()
# get stack returns the transposed data, depending on the perspective
self.assertEqual(my_trans_stack.shape,
(self.mystack.shape[1], self.mystack.shape[0],
self.mystack.shape[2]))
self.assertTrue(
numpy.array_equal(numpy.transpose(self.mystack, axes=(1, 0, 2)),
my_trans_stack))
app = qt.QApplication(sys.argv[1:])
a, b, c = numpy.meshgrid(numpy.linspace(-10, 10, 200),
numpy.linspace(-10, 5, 150),
numpy.linspace(-5, 10, 120),
indexing="ij")
mystack = numpy.asarray(numpy.sin(a * b * c) / (a * b * c), dtype='float32')
# linear calibrations (a, b), x -> a + bx
dim0_calib = (-10., 20. / 200.)
dim1_calib = (-10., 15. / 150.)
dim2_calib = (-5., 15. / 120.)
# sv = StackView()
sv = StackViewMainWindow()
sv.setStack(mystack, calibrations=[dim0_calib, dim1_calib, dim2_calib])
sv.setLabels([
"dim0: -10 to 10 (200 samples)", "dim1: -10 to 5 (150 samples)",
"dim2: -5 to 10 (120 samples)"
])
sv.setColormap("jet")
sv.scaleColormapRangeToStack()
# Enable use of mask in other tools: colormap autoscale, histogram, profile
maskToolsWidget = sv.getPlotWidget().getMaskToolsDockWidget().widget()
maskToolsWidget.setItemMaskUpdated(True)
sv.show()
app.exec_()
def plot_data3D(data3D,
dataScan,
dataX,
dataY,
title="",
xtitle="",
ytitle=""):
xmin = numpy.min(dataX)
xmax = numpy.max(dataX)
ymin = numpy.min(dataY)
ymax = numpy.max(dataY)
stepX = dataX[1] - dataX[0]
stepY = dataY[1] - dataY[0]
if len(dataScan) > 1: stepScan = dataScan[1] - dataScan[0]
else: stepScan = 1.0
if stepScan == 0.0: stepScan = 1.0
if stepX == 0.0: stepX = 1.0
if stepY == 0.0: stepY = 1.0
dim0_calib = (dataScan[0], stepScan)
dim1_calib = (ymin, stepY)
dim2_calib = (xmin, stepX)
data_to_plot = numpy.swapaxes(data3D, 1, 2)
colormap = {
"name": "temperature",
"normalization": "linear",
"autoscale": True,
"vmin": 0,
"vmax": 0,
"colors": 256
}
plot_canvas = StackViewMainWindow()
plot_canvas.setGraphTitle(title)
plot_canvas.setLabels(["Scanned Variable", ytitle, xtitle])
plot_canvas.setColormap(colormap=colormap)
plot_canvas.setStack(numpy.array(data_to_plot),
calibrations=[dim0_calib, dim1_calib, dim2_calib])
plot_canvas.show()
def do_plot(self):
old_tab_index = self.tabs.currentIndex()
try:
for i in range(len(self.tab_titles)):
self.tab[i].layout().removeItem(self.tab[i].layout().itemAt(0))
except:
pass
if self.INDIVIDUAL_MODES:
self.tab_titles = [
"SPECTRUM",
"CUMULATED SPECTRUM",
"SPECTRAL DENSITY (INTENSITY)",
"SPECTRAL INTENSITY FROM MODES",
"REFERENCE ELECRON DENSITY",
"REFERENCE UNDULATOR WAVEFRONT",
"INDIVIDUAL MODES",
]
else:
self.tab_titles = [
"SPECTRUM",
"CUMULATED SPECTRUM",
"SPECTRAL DENSITY (INTENSITY)",
"REFERENCE ELECRON DENSITY",
"REFERENCE UNDULATOR WAVEFRONT",
"MODE INDEX: %d" % self.MODE_INDEX,
]
self.initialize_tabs()
if self.TYPE_PRESENTATION == 0:
myprocess = self._square_modulus
title0 = "Intensity of eigenvalues"
title1 = "Intensity of eigenvector"
if self.TYPE_PRESENTATION == 1:
myprocess = numpy.absolute
title0 = "Modulus of eigenvalues"
title1 = "Modulus of eigenvector"
elif self.TYPE_PRESENTATION == 2:
myprocess = numpy.real
title0 = "Real part of eigenvalues"
title1 = "Real part of eigenvector"
elif self.TYPE_PRESENTATION == 3:
myprocess = numpy.imag
title0 = "Imaginary part of eigenvalues"
title1 = "Imaginary part of eigenvectos"
elif self.TYPE_PRESENTATION == 4:
myprocess = numpy.angle
title0 = "Angle of eigenvalues [rad]"
title1 = "Angle of eigenvector [rad]"
if self._input_available:
x_values = numpy.arange(self.af.number_modes())
x_label = "Mode index"
y_label = "Occupation"
xx = self.af.x_coordinates()
yy = self.af.y_coordinates()
xmin = numpy.min(xx)
xmax = numpy.max(xx)
ymin = numpy.min(yy)
ymax = numpy.max(yy)
else:
raise Exception("Nothing to plot")
#
# plot spectrum
#
tab_index = 0
self.plot_canvas[tab_index] = PlotWindow(parent=None,
backend=None,
resetzoom=True,
autoScale=False,
logScale=True,
grid=True,
curveStyle=True,
colormap=False,
aspectRatio=False,
yInverted=False,
copy=True,
save=True,
print_=True,
control=False,
position=True,
roi=False,
mask=False,
fit=False)
self.tab[tab_index].layout().addWidget(self.plot_canvas[tab_index])
self.plot_canvas[tab_index].setDefaultPlotLines(True)
self.plot_canvas[tab_index].setXAxisLogarithmic(False)
self.plot_canvas[tab_index].setYAxisLogarithmic(False)
self.plot_canvas[tab_index].setGraphXLabel(x_label)
self.plot_canvas[tab_index].setGraphYLabel(y_label)
self.plot_canvas[tab_index].addCurve(x_values,
numpy.abs(
self.af.occupation_array()),
title0,
symbol='',
xlabel="X",
ylabel="Y",
replace=False) #'+', '^', ','
self.tab[tab_index].layout().addWidget(self.plot_canvas[tab_index])
#
# plot cumulated spectrum
#
tab_index += 1
self.plot_canvas[tab_index] = PlotWindow(parent=None,
backend=None,
resetzoom=True,
autoScale=False,
logScale=True,
grid=True,
curveStyle=True,
colormap=False,
aspectRatio=False,
yInverted=False,
copy=True,
save=True,
print_=True,
control=False,
position=True,
roi=False,
mask=False,
fit=False)
self.tab[tab_index].layout().addWidget(self.plot_canvas[tab_index])
self.plot_canvas[tab_index].setDefaultPlotLines(True)
self.plot_canvas[tab_index].setXAxisLogarithmic(False)
self.plot_canvas[tab_index].setYAxisLogarithmic(False)
self.plot_canvas[tab_index].setGraphXLabel(x_label)
self.plot_canvas[tab_index].setGraphYLabel("Cumulated occupation")
self.plot_canvas[tab_index].addCurve(
x_values,
self.af.cumulated_occupation_array(),
"Cumulated occupation",
symbol='',
xlabel="X",
ylabel="Y",
replace=False) #'+', '^', ','
self.plot_canvas[tab_index].setGraphYLimits(0.0, 1.0)
self.tab[tab_index].layout().addWidget(self.plot_canvas[tab_index])
#
# plot spectral density
#
tab_index += 1
image = myprocess((self.af.spectral_density()))
self.plot_data2D(image,
1e6 * self.af.x_coordinates(),
1e6 * self.af.y_coordinates(),
tab_index,
title="Spectral Density (Intensity)",
xtitle="X [um] (%d pixels)" % (image.shape[0]),
ytitle="Y [um] (%d pixels)" % (image.shape[1]))
#
# plot spectral density from modes
#
if self.INDIVIDUAL_MODES:
tab_index += 1
image = myprocess((self.af.intensity_from_modes()))
self.plot_data2D(image,
1e6 * self.af.x_coordinates(),
1e6 * self.af.y_coordinates(),
tab_index,
title="Spectral Density (Intensity)",
xtitle="X [um] (%d pixels)" % (image.shape[0]),
ytitle="Y [um] (%d pixels)" % (image.shape[1]))
#
# plot reference electron density
#
tab_index += 1
image = numpy.abs(self.af.reference_electron_density()
)**2 #TODO: Correct? it is complex...
self.plot_data2D(image,
1e6 * self.af.x_coordinates(),
1e6 * self.af.y_coordinates(),
tab_index,
title="Reference electron density",
xtitle="X [um] (%d pixels)" % (image.shape[0]),
ytitle="Y [um] (%d pixels)" % (image.shape[1]))
#
# plot reference undulator radiation
#
tab_index += 1
image = self.af.reference_undulator_radiation()[
0, :, :, 0] #TODO: Correct? is polarized?
self.plot_data2D(image,
1e6 * self.af.x_coordinates(),
1e6 * self.af.y_coordinates(),
tab_index,
title="Reference undulator radiation",
xtitle="X [um] (%d pixels)" % (image.shape[0]),
ytitle="Y [um] (%d pixels)" % (image.shape[1]))
#
# plot all modes
#
if self.INDIVIDUAL_MODES:
tab_index += 1
dim0_calib = (0, 1)
dim1_calib = (1e6 * yy[0], 1e6 * (yy[1] - yy[0]))
dim2_calib = (1e6 * xx[0], 1e6 * (xx[1] - xx[0]))
colormap = {
"name": "temperature",
"normalization": "linear",
"autoscale": True,
"vmin": 0,
"vmax": 0,
"colors": 256
}
self.plot_canvas[tab_index] = StackViewMainWindow()
self.plot_canvas[tab_index].setGraphTitle(title1)
self.plot_canvas[tab_index].setLabels([
"Mode number",
"Y index from %4.2f to %4.2f um" % (1e6 * ymin, 1e6 * ymax),
"X index from %4.2f to %4.2f um" % (1e6 * xmin, 1e6 * xmax),
])
self.plot_canvas[tab_index].setColormap(colormap=colormap)
self.plot_canvas[tab_index].setStack(
myprocess(numpy.swapaxes(self.af.modes(), 2, 1)),
calibrations=[dim0_calib, dim1_calib, dim2_calib])
self.tab[tab_index].layout().addWidget(self.plot_canvas[tab_index])
else:
tab_index += 1
image = myprocess((self.af.mode(self.MODE_INDEX)))
self.plot_data2D(image,
1e6 * self.af.x_coordinates(),
1e6 * self.af.y_coordinates(),
tab_index,
title="Mode %d" % self.MODE_INDEX,
xtitle="X [um] (%d pixels)" % (image.shape[0]),
ytitle="Y [um] (%d pixels)" % (image.shape[1]))
#
try:
self.tabs.setCurrentIndex(old_tab_index)
except:
pass
def plot_stack(mystack,what="intensity",title0="X",title1="Y",title2="Z"):
from silx.gui.plot.StackView import StackViewMainWindow
from silx.gui import qt
app = qt.QApplication(sys.argv[1:])
sv = StackViewMainWindow()
sv.setColormap("jet", autoscale=True)
if what == "intensity":
sv.setStack(numpy.absolute(mystack))
elif what == "real":
sv.setStack(numpy.real(mystack))
elif what == "imaginary":
sv.setStack(numpy.imag(mystack))
elif what == "phase":
sv.setStack(numpy.angle(mystack))
elif what == "phase_deg":
sv.setStack(numpy.angle(mystack,deg=True))
else:
raise Exception("Undefined label "+what)
sv.setLabels([title0,title1,title2])
sv.show()
app.exec_()
import numpy
import sys
from silx.gui import qt
from silx.gui.plot.StackView import StackViewMainWindow
app = qt.QApplication(sys.argv[1:])
a, b, c = numpy.meshgrid(numpy.linspace(-10, 10, 200),
numpy.linspace(-10, 5, 150),
numpy.linspace(-5, 10, 120),
indexing="ij")
mystack = numpy.asarray(numpy.sin(a * b * c) / (a * b * c),
dtype='float32')
# linear calibrations (a, b), x -> a + bx
dim0_calib = (-10., 20. / 200.)
dim1_calib = (-10., 15. / 150.)
dim2_calib = (-5., 15. / 120.)
# sv = StackView()
sv = StackViewMainWindow()
sv.setColormap("jet", autoscale=True)
sv.setStack(mystack,
calibrations=[dim0_calib, dim1_calib, dim2_calib])
sv.setLabels(["dim0: -10 to 10 (200 samples)",
"dim1: -10 to 5 (150 samples)",
"dim2: -5 to 10 (120 samples)"])
sv.show()
app.exec_()
