"""Module for plotting photon count from two chosen pixel in real time.
Unpacks the binary data, finds the two pixels requested and plots the
number of photons registered by the two pixels. x-axis limits are given
by the slider, upper y-axis limit is set as maximum of the two counts
plus 10 percent.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.backends.backend_qt5agg import (
FigureCanvasQTAgg as FigureCanvas,
)
from matplotlib.backends.backend_qt5agg import (
NavigationToolbar2QT as NavigationToolbar,
)
from matplotlib.figure import Figure
from PyQt5.QtWidgets import QVBoxLayout, QWidget
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class PltCanvas_MZI(QWidget):
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def __init__(self, parent=None, width=7, height=4, dpi=100):
"""Creation of the figure widget.
The widget is created with the bar with options.
Parameters
----------
width : int, optional
Figure widget width, by default 7.
height : int, optional
Figure widget height, by default 4.
dpi : int, optional
Figure widget dpi, by default 100.
"""
super(PltCanvas_MZI, self).__init__(parent)
# For 'dark_background' style
plt.style.use("dark_background")
# a figure instance to plot on
self.figure = Figure(figsize=(width, height), dpi=100)
self.canvas = FigureCanvas(self.figure)
self.toolbar = NavigationToolbar(self.canvas, self)
self.ax = self.figure.add_subplot(111)
self.ax2 = self.ax.twinx()
self.figure.subplots_adjust(
left=0.15, right=0.9, top=0.945, bottom=0.12
)
# creating a Vertical Box layout
self.layout = QVBoxLayout(self)
self.layout.addWidget(self.canvas)
self.layout.addWidget(self.toolbar)
self.setLayout(self.layout)
self.setplotparameters()
# Upper ylim for the plot
self.upper_ylim = 0
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def setplotparameters(self, fontsize: int = 16):
"""Figure parameters manipulation.
Set font size, axes labels. Set the width and orientation of the
axes ticks.
"""
plt.rcParams.update({"font.size": fontsize})
self.ax.set_xlabel("Pixel (-)", fontsize=fontsize)
self.ax.set_ylabel("# of timestamps (-)", fontsize=fontsize)
self.ax.tick_params(which="both", width=2, direction="in")
self.ax.tick_params(
which="major", length=7, direction="in", labelsize=fontsize
)
self.ax.tick_params(
which="minor", length=4, direction="in", labelsize=fontsize
)
self.ax2.tick_params(
which="major", length=7, direction="in", labelsize=fontsize
)
self.ax2.tick_params(
which="minor", length=4, direction="in", labelsize=fontsize
)
self.ax.yaxis.set_ticks_position("both")
self.ax.xaxis.set_ticks_position("both")
for axis in ["top", "bottom", "left", "right"]:
self.ax.spines[axis].set_linewidth(2)
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def setPlotData_MZI(self, xdataplot, yplotdata1, yplotdata2, xLim, yLim):
"""Plot data.
Plot the provided data while following the state of the axis
limits and the switch for plotting vertical lines at positions
64, 128, and 192.
Parameters
----------
xdataplot : array
Data for the x-axis: pixel numbers.
yplotdata : array-like
Data for the y-axis: number of timestamps.
xLim : list
Limits for the x-axis.
grouping : bool, optional
Switch for plotting vertical lines at positiong 64, 128, and
192, by default False.
"""
# self.ax.cla()
self.ax.plot(xdataplot, yplotdata1, "-o", color="indianred")
self.ax2.plot(xdataplot, yplotdata2, "-o", color="teal")
self.ax.relim()
self.ax.autoscale_view()
self.setplotparameters()
self.ax.set_xlim(xLim, xdataplot[-1] + 2)
new_ylim = np.max([yplotdata1[-1], yplotdata2[-1]]) * 1.1
if new_ylim > self.upper_ylim:
self.upper_ylim = new_ylim
self.ax.set_ylim(yLim, self.upper_ylim)
self.ax2.set_ylim(yLim, self.upper_ylim)
self.ax.ticklabel_format(axis="y", style="sci", scilimits=(0, 0))
self.ax2.ticklabel_format(axis="y", style="sci", scilimits=(0, 0))
self.figure.canvas.draw()
self.figure.canvas.flush_events()
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def setPlotScale(self, scaleLin):
"""Switches plot scale between logarithmic and linear."""
if scaleLin:
self.ax.set_yscale("linear")
self.canvas.draw()
self.canvas.flush_events()
else:
self.ax.set_yscale("log")
self.canvas.draw()
self.canvas.flush_events()