class Detailed2DWidget(QWidget):
def __init__(self, x_scale_factor=1.0, y_scale_factor=1.0):
super(SRWPlot.Detailed2DWidget, self).__init__()
self.x_scale_factor = x_scale_factor
self.y_scale_factor = y_scale_factor
self.plot_canvas = ImageView(parent=self)
self.plot_canvas.setColormap({
"name": "gray",
"normalization": "linear",
"autoscale": True,
"vmin": 0,
"vmax": 0,
"colors": 256
})
self.plot_canvas.setMinimumWidth(590 * x_scale_factor)
self.plot_canvas.setMaximumWidth(590 * y_scale_factor)
self.info_box = SRWPlot.InfoBoxWidget(x_scale_factor,
y_scale_factor)
layout = QGridLayout()
layout.addWidget(self.info_box, 0, 1, 1, 1)
layout.addWidget(self.plot_canvas, 0, 0, 1, 1)
layout.setColumnMinimumWidth(0, 600 * x_scale_factor)
layout.setColumnMinimumWidth(1, 230 * x_scale_factor)
self.setLayout(layout)
def plot_2D(self,
ticket,
var_x,
var_y,
title,
xtitle,
ytitle,
xum="",
yum="",
plotting_range=None,
use_default_factor=True):
matplotlib.rcParams['axes.formatter.useoffset'] = 'False'
if use_default_factor:
factor1 = SRWPlot.get_factor(var_x)
factor2 = SRWPlot.get_factor(var_y)
else:
factor1 = 1.0
factor2 = 1.0
if plotting_range == None:
xx = ticket['bin_h']
yy = ticket['bin_v']
nbins_h = ticket['nbins_h']
nbins_v = ticket['nbins_v']
histogram = ticket['histogram']
else:
range_x = numpy.where(
numpy.logical_and(ticket['bin_h'] >= plotting_range[0],
ticket['bin_h'] <= plotting_range[1]))
range_y = numpy.where(
numpy.logical_and(ticket['bin_v'] >= plotting_range[2],
ticket['bin_v'] <= plotting_range[3]))
xx = ticket['bin_h'][range_x]
yy = ticket['bin_v'][range_y]
histogram = []
for row in ticket['histogram'][range_x]:
histogram.append(row[range_y])
nbins_h = len(xx)
nbins_v = len(yy)
if len(xx) == 0 or len(yy) == 0:
raise Exception("Nothing to plot in the given range")
xmin, xmax = xx.min(), xx.max()
ymin, ymax = yy.min(), yy.max()
origin = (xmin * factor1, ymin * factor2)
scale = (abs(
(xmax - xmin) / nbins_h) * factor1, abs(
(ymax - ymin) / nbins_v) * factor2)
# PyMCA inverts axis!!!! histogram must be calculated reversed
data_to_plot = []
for y_index in range(0, nbins_v):
x_values = []
for x_index in range(0, nbins_h):
x_values.append(histogram[x_index][y_index])
data_to_plot.append(x_values)
self.plot_canvas.setImage(numpy.array(data_to_plot),
origin=origin,
scale=scale)
if xtitle is None: xtitle = SRWPlot.get_SRW_label(var_x)
if ytitle is None: ytitle = SRWPlot.get_SRW_label(var_y)
self.plot_canvas.setGraphXLabel(xtitle)
self.plot_canvas.setGraphYLabel(ytitle)
self.plot_canvas.setGraphTitle(title)
self.plot_canvas._histoHPlot.setGraphYLabel('Frequency')
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label(
).set_color('white')
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoHPlot._backend.ax.xaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
self.plot_canvas._histoVPlot.setGraphXLabel('Frequency')
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label(
).set_color('white')
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoVPlot._backend.ax.yaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
if ticket['fwhm_h'] == None: ticket['fwhm_h'] = 0.0
if ticket['fwhm_v'] == None: ticket['fwhm_v'] = 0.0
n_patches = len(self.plot_canvas._histoHPlot._backend.ax.patches)
if (n_patches > 0):
self.plot_canvas._histoHPlot._backend.ax.patches.remove(
self.plot_canvas._histoHPlot._backend.ax.patches[n_patches
- 1])
if not ticket['fwhm_h'] == 0.0:
x_fwhm_i, x_fwhm_f = ticket['fwhm_coordinates_h']
x_fwhm_i, x_fwhm_f = x_fwhm_i * factor1, x_fwhm_f * factor1
y_fwhm = max(ticket['histogram_h']) * 0.5
self.plot_canvas._histoHPlot._backend.ax.add_patch(
FancyArrowPatch([x_fwhm_i, y_fwhm], [x_fwhm_f, y_fwhm],
arrowstyle=ArrowStyle.CurveAB(
head_width=2, head_length=4),
color='b',
linewidth=1.5))
n_patches = len(self.plot_canvas._histoVPlot._backend.ax.patches)
if (n_patches > 0):
self.plot_canvas._histoVPlot._backend.ax.patches.remove(
self.plot_canvas._histoVPlot._backend.ax.patches[n_patches
- 1])
if not ticket['fwhm_v'] == 0.0:
y_fwhm_i, y_fwhm_f = ticket['fwhm_coordinates_v']
y_fwhm_i, y_fwhm_f = y_fwhm_i * factor2, y_fwhm_f * factor2
x_fwhm = max(ticket['histogram_v']) * 0.5
self.plot_canvas._histoVPlot._backend.ax.add_patch(
FancyArrowPatch([x_fwhm, y_fwhm_i], [x_fwhm, y_fwhm_f],
arrowstyle=ArrowStyle.CurveAB(
head_width=2, head_length=4),
color='r',
linewidth=1.5))
self.plot_canvas._histoHPlot.replot()
self.plot_canvas._histoVPlot.replot()
self.plot_canvas.replot()
self.info_box.total.setText("{:.3e}".format(
decimal.Decimal(ticket['total'])))
self.info_box.fwhm_h.setText("{:5.4f}".format(ticket['fwhm_h'] *
factor1))
self.info_box.fwhm_v.setText("{:5.4f}".format(ticket['fwhm_v'] *
factor2))
self.info_box.label_h.setText("FWHM " + xum)
self.info_box.label_v.setText("FWHM " + yum)
def clear(self):
self.plot_canvas.clear()
self.plot_canvas._histoHPlot.clear()
self.plot_canvas._histoVPlot.clear()
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label(
).set_color('white')
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoHPlot._backend.ax.xaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label(
).set_color('white')
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoVPlot._backend.ax.yaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
self.plot_canvas._histoHPlot.setGraphYLabel('Frequency')
self.plot_canvas._histoVPlot.setGraphXLabel('Frequency')
self.plot_canvas._histoHPlot.replot()
self.plot_canvas._histoVPlot.replot()
self.info_box.clear()
class ImageViewWithFWHM(QWidget):
def __init__(self, x_scale_factor=1.0, y_scale_factor=1.0):
super(ImageViewWithFWHM, self).__init__()
self.plot_canvas = ImageView(parent=self)
self.set_plot_canvas_default_settings()
self.info_box = InfoBoxWidget(x_scale_factor, y_scale_factor)
layout = QGridLayout()
layout.addWidget(self.info_box, 0, 1, 1, 1)
layout.addWidget(self.plot_canvas, 0, 0, 1, 1)
layout.setColumnMinimumWidth(0, 600 * x_scale_factor)
layout.setColumnMinimumWidth(1, 230 * x_scale_factor)
self.setLayout(layout)
def get_ImageView(self):
return self.plot_canvas
def get_InfoBoxWidhet(self):
return self.info_box
def set_plot_canvas_default_settings(self):
self.get_ImageView().resetZoom()
self.get_ImageView().setXAxisAutoScale(True)
self.get_ImageView().setYAxisAutoScale(True)
self.get_ImageView().setGraphGrid(False)
self.get_ImageView().setKeepDataAspectRatio(True)
self.get_ImageView().yAxisInvertedAction.setVisible(False)
self.get_ImageView().setXAxisLogarithmic(False)
self.get_ImageView().setYAxisLogarithmic(False)
self.get_ImageView().getMaskAction().setVisible(False)
self.get_ImageView().getRoiAction().setVisible(False)
self.get_ImageView().getColormapAction().setVisible(True)
self.get_ImageView().setKeepDataAspectRatio(False)
def plot_2D(self,
histogram,
xx=None,
yy=None,
title="",
xtitle="",
ytitle="",
xum="[mm]",
yum="[mm]",
plotting_range=None,
factor1=1.0,
factor2=1.0,
colormap=None):
if xx is None:
xx = numpy.arange(histogram.shape[0])
if yy is None:
yy = numpy.arange(histogram.shape[1])
if plotting_range == None:
nbins_h = xx.size
nbins_v = yy.size
else:
range_x = numpy.where(
numpy.logical_and(xx >= plotting_range[0],
xx <= plotting_range[1]))
range_y = numpy.where(
numpy.logical_and(yy >= plotting_range[2],
yy <= plotting_range[3]))
xx = xx[range_x]
yy = yy[range_y]
nbins_h = xx.size
nbins_v = yy.size
if len(xx) == 0 or len(yy) == 0:
raise Exception("Nothing to plot in the given range")
xmin, xmax = xx.min(), xx.max()
ymin, ymax = yy.min(), yy.max()
origin = (xmin * factor1, ymin * factor2)
scale = (abs(
(xmax - xmin) / nbins_h) * factor1, abs(
(ymax - ymin) / nbins_v) * factor2)
# silx inverts axis!!!! histogram must be calculated reversed
data_to_plot = []
for y_index in range(0, nbins_v):
x_values = []
for x_index in range(0, nbins_h):
x_values.append(histogram[x_index][y_index])
data_to_plot.append(x_values)
data_to_plot = numpy.array(data_to_plot)
histogram_h = numpy.sum(data_to_plot,
axis=0) # data to plot axis are inverted
histogram_v = numpy.sum(data_to_plot, axis=1)
ticket = {}
ticket['total'] = numpy.sum(data_to_plot)
ticket['fwhm_h'], ticket['fwhm_quote_h'], ticket[
'fwhm_coordinates_h'] = get_fwhm(histogram_h, xx)
ticket['sigma_h'] = get_sigma(histogram_h, xx)
ticket['fwhm_v'], ticket['fwhm_quote_v'], ticket[
'fwhm_coordinates_v'] = get_fwhm(histogram_v, yy)
ticket['sigma_v'] = get_sigma(histogram_v, yy)
self.plot_canvas.setColormap(colormap=colormap)
self.plot_canvas.setImage(data_to_plot, origin=origin, scale=scale)
self.plot_canvas.setGraphXLabel(xtitle)
self.plot_canvas.setGraphYLabel(ytitle)
self.plot_canvas.setGraphTitle(title)
self.plot_canvas._histoHPlot.setGraphYLabel('Counts')
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label().set_color(
'white')
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoHPlot._backend.ax.xaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
self.plot_canvas._histoVPlot.setGraphXLabel('Counts')
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label().set_color(
'white')
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoVPlot._backend.ax.yaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
n_patches = len(self.plot_canvas._histoHPlot._backend.ax.patches)
if (n_patches > 0):
self.plot_canvas._histoHPlot._backend.ax.patches.remove(
self.plot_canvas._histoHPlot._backend.ax.patches[n_patches -
1])
if not ticket['fwhm_h'] == 0.0:
x_fwhm_i, x_fwhm_f = ticket['fwhm_coordinates_h']
x_fwhm_i, x_fwhm_f = x_fwhm_i * factor1, x_fwhm_f * factor1
y_fwhm = ticket['fwhm_quote_h']
self.plot_canvas._histoHPlot._backend.ax.add_patch(
FancyArrowPatch([x_fwhm_i, y_fwhm], [x_fwhm_f, y_fwhm],
arrowstyle=ArrowStyle.CurveAB(head_width=2,
head_length=4),
color='b',
linewidth=1.5))
n_patches = len(self.plot_canvas._histoVPlot._backend.ax.patches)
if (n_patches > 0):
self.plot_canvas._histoVPlot._backend.ax.patches.remove(
self.plot_canvas._histoVPlot._backend.ax.patches[n_patches -
1])
if not ticket['fwhm_v'] == 0.0:
y_fwhm_i, y_fwhm_f = ticket['fwhm_coordinates_v']
y_fwhm_i, y_fwhm_f = y_fwhm_i * factor2, y_fwhm_f * factor2
x_fwhm = ticket['fwhm_quote_v']
self.plot_canvas._histoVPlot._backend.ax.add_patch(
FancyArrowPatch([x_fwhm, y_fwhm_i], [x_fwhm, y_fwhm_f],
arrowstyle=ArrowStyle.CurveAB(head_width=2,
head_length=4),
color='r',
linewidth=1.5))
self.plot_canvas._histoHPlot.replot()
self.plot_canvas._histoVPlot.replot()
self.plot_canvas.replot()
self.info_box.total.setText("{:.3e}".format(
decimal.Decimal(ticket['total'])))
self.info_box.fwhm_h.setText("{:5.4f}".format(ticket['fwhm_h'] *
factor1))
self.info_box.fwhm_v.setText("{:5.4f}".format(ticket['fwhm_v'] *
factor2))
self.info_box.label_h.setText("FWHM " + xum)
self.info_box.label_v.setText("FWHM " + yum)
self.info_box.sigma_h.setText("{:5.4f}".format(ticket['sigma_h'] *
factor1))
self.info_box.sigma_v.setText("{:5.4f}".format(ticket['sigma_v'] *
factor2))
self.info_box.label_s_h.setText("\u03c3 " + xum)
self.info_box.label_s_v.setText("\u03c3 " + yum)
def clear(self):
self.plot_canvas.clear()
self.plot_canvas._histoHPlot.clear()
self.plot_canvas._histoVPlot.clear()
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label().set_color(
'white')
self.plot_canvas._histoHPlot._backend.ax.xaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoHPlot._backend.ax.xaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label().set_color(
'white')
self.plot_canvas._histoVPlot._backend.ax.yaxis.get_label(
).set_fontsize(1)
for label in self.plot_canvas._histoVPlot._backend.ax.yaxis.get_ticklabels(
):
label.set_color('white')
label.set_fontsize(1)
self.plot_canvas._histoHPlot.setGraphYLabel('')
self.plot_canvas._histoVPlot.setGraphXLabel('')
self.plot_canvas._histoHPlot.replot()
self.plot_canvas._histoVPlot.replot()
self.info_box.clear()