Examples — PlotPy 2.7 Manual (original) (raw)

Using PlotWidget¶

The following example shows how to use the PlotWidget class to create a simple plot with a curve and a filtering tool. In this example, the plot manager (see PlotManager) is not used, at least not directly: the plot manager is integrated in the PlotWidget class.

import numpy as np import scipy.ndimage as spi import scipy.signal as sps from guidata.configtools import get_icon from guidata.qthelpers import qt_app_context from qtpy import QtWidgets as QW

import plotpy.config # Loading icons # noqa: F401 from plotpy.builder import make

class FilterTestWidget(QW.QWidget): """ Filter testing widget parent: parent widget (QWidget) x, y: NumPy arrays func: function object (the signal filter to be tested) """

def __init__(self, parent, x, y, func):
    QW.QWidget.__init__(self, parent)
    self.setMinimumSize(320, 200)
    self.x = x
    self.y = y
    self.func = func
    # ---plotpy curve item attribute:
    self.curve_item = None
    # ---

def setup_widget(self, title):
    # ---Create the plot widget:
    plotwidget = make.widget(self, type="curve")
    self.curve_item = make.curve([], [], color="b")
    plotwidget.plot.add_item(self.curve_item)
    plotwidget.plot.set_antialiasing(True)
    # ---

    button = QW.QPushButton("Test filter: {}".format(title))
    button.clicked.connect(self.process_data)
    vlayout = QW.QVBoxLayout()
    vlayout.addWidget(plotwidget)
    vlayout.addWidget(button)
    self.setLayout(vlayout)

    self.update_curve()

def process_data(self):
    self.y = self.func(self.y)
    self.update_curve()

def update_curve(self):
    # ---Update curve
    self.curve_item.set_data(self.x, self.y)
    self.curve_item.plot().replot()
    # ---

class WindowTest(QW.QWidget): def init(self): QW.QWidget.init(self) self.setWindowTitle("Signal filtering (plotpy)") self.setWindowIcon(get_icon("plotpy.svg")) hlayout = QW.QHBoxLayout() self.setLayout(hlayout)

def add_plot(self, x, y, func, title):
    widget = FilterTestWidget(self, x, y, func)
    widget.setup_widget(title)
    self.layout().addWidget(widget)

def test_filter1(): """Testing this simple Qt/plotpy example""" x = np.linspace(-10, 10, 500) y = np.random.rand(len(x)) + 5 * np.sin(2 * x**2) / x with qt_app_context(exec_loop=True): win = WindowTest() win.add_plot(x, y, lambda x: spi.gaussian_filter1d(x, 1.0), "Gaussian") win.add_plot(x, y, sps.wiener, "Wiener") win.show()

if name == "main": test_filter1()

Using a plot manager¶

Even if this simple example does not justify the use of the PlotManager(this is an unnecessary complication here), it shows how to use it. In more complex applications, using the PlotManager allows to design highly versatile graphical user interfaces.

import numpy as np import scipy.ndimage as spi import scipy.signal as sps from guidata.configtools import get_icon from guidata.qthelpers import qt_app_context, win32_fix_title_bar_background from qtpy import QtWidgets as QW

import plotpy.config # Loading icons # noqa: F401 from plotpy.builder import make from plotpy.plot import BasePlot, BasePlotOptions from plotpy.plot.manager import PlotManager

class FilterTestWidget(QW.QWidget): """ Filter testing widget parent: parent widget (QWidget) x, y: NumPy arrays func: function object (the signal filter to be tested) """

def __init__(self, parent, x, y, func):
    QW.QWidget.__init__(self, parent)
    self.setMinimumSize(320, 200)
    self.x = x
    self.y = y
    self.func = func
    # ---plotpy related attributes:
    self.plot = None
    self.curve_item = None
    # ---

def setup_widget(self, title):
    # ---Create the plot widget:
    self.plot = BasePlot(self, options=BasePlotOptions(type="curve"))
    self.curve_item = make.curve([], [], color="b")
    self.plot.add_item(self.curve_item)
    self.plot.set_antialiasing(True)
    # ---

    button = QW.QPushButton("Test filter: {}".format(title))
    button.clicked.connect(self.process_data)
    vlayout = QW.QVBoxLayout()
    vlayout.addWidget(self.plot)
    vlayout.addWidget(button)
    self.setLayout(vlayout)

    self.update_curve()

def process_data(self):
    self.y = self.func(self.y)
    self.update_curve()

def update_curve(self):
    # ---Update curve
    self.curve_item.set_data(self.x, self.y)
    self.plot.replot()
    # ---

class WindowTest(QW.QMainWindow): def init(self): super().init() win32_fix_title_bar_background(self) self.setWindowTitle("Signal filtering 2 (plotpy)") self.setWindowIcon(get_icon("plotpy.svg"))

    hlayout = QW.QHBoxLayout()
    central_widget = QW.QWidget(self)
    central_widget.setLayout(hlayout)
    self.setCentralWidget(central_widget)
    # ---plotpy plot manager
    self.manager = PlotManager(self)
    # ---

def add_plot(self, x, y, func, title):
    widget = FilterTestWidget(self, x, y, func)
    widget.setup_widget(title)
    self.centralWidget().layout().addWidget(widget)
    # ---Register plot to manager
    self.manager.add_plot(widget.plot)
    # ---

def setup_window(self):
    # ---Add toolbar and register manager tools
    toolbar = self.addToolBar("tools")
    self.manager.add_toolbar(toolbar, id(toolbar))
    self.manager.register_all_curve_tools()
    # ---

def test_filter2(): """Testing this simple Qt/plotpy example""" x = np.linspace(-10, 10, 500) y = np.random.rand(len(x)) + 5 * np.sin(2 * x**2) / x with qt_app_context(exec_loop=True): win = WindowTest() win.add_plot(x, y, lambda x: spi.gaussian_filter1d(x, 1.0), "Gaussian") win.add_plot(x, y, sps.wiener, "Wiener") win.setup_window() win.show()

if name == "main": test_filter2()