Module API

mpl_qt_viz

A Python package providing enhanced data visualization and ROI selection built on top of Matplotlib and PyQt5.

Subpackages

roiSelection	Useful classes for interacting with Matplotlib plots.
visualizers	Qt Widgets for interactive data visualization.

Examples

Examples

PlotNd visualization of a 3D array

from mpl_qt_viz.visualizers import PlotNd
import numpy as np
from PyQt5.QtWidgets import QApplication
import sys

# Generate a 3-dimensional dimension array with numpy.meshgrid.
# The Plot Nd Widget supports higher dimensionality as well.
x = np.linspace(0, 1, num=75)
y = np.linspace(0, 1, num=100)
z = np.linspace(0, 3, num=40)
X, Y, Z = np.meshgrid(x, y, z)
# Create a 3-dimensional example data array.
arr = np.sin(2 * np.pi * 1 * Z) + .5 * X + np.cos(2 * np.pi * 4 * Y)

#Run an application with the PlotNd widget
app = QApplication(sys.argv)
p = PlotNd(data=arr,
           names=('Dim1', 'D2', 'D3'),  # Manually sets how each dimension is labeled.
           indices=[y, x, z])  # Specifies the data range for each dimension.
p.setColorMap('plasma')
sys.exit(app.exec_())

DockablePlotWindow providing organization for related plots

import numpy as np
import random
from PyQt5.QtWidgets import QApplication
from mpl_qt_viz.visualizers import DockablePlotWindow
import sys

# Plot names that will be randomly selected from in this example
names = ['plot', 'data', 'other']
# Valid plot location specifiers that will be randomly selected from in this example
areas = ['left', 'right', 'bottom', 'top']


def makePlot(ax):
    """Generate a random line plot on ax."""
    x = np.linspace(0, 10)
    # y = np.random.random(x.size)
    freq1 = .5 + np.random.rand()
    freq2 = .5 + np.random.rand()
    ax.plot(x, np.sin(freq1 * x))
    ax.plot(x, np.cos(freq2 * x), ls='--')


def makeImage(ax):
    """Generate a random image plot on ax."""
    freq = 1 + 10 * np.random.rand()
    X, Y = np.meshgrid(np.linspace(-1, 1), np.linspace(-1, 1))
    R = X**2 + Y**2
    arr = np.sin(freq * R)
    ax.imshow(arr, cmap='jet')

plotTypes = [('plot', makePlot), ('image', makeImage)]


app = QApplication([])  # Make an application for the widgets to run in.

w = DockablePlotWindow("My Dockable Plot Window")
for i in range(10):
    name, func = random.choice(plotTypes)
    # Use the widget's `subplots` method to generate matplotlib plots docked in the widget.
    fig, ax = w.subplots(name, dockArea=random.choice(areas))
    func(ax)

w2 = DockablePlotWindow(title="My 2nd Plot Window")
for i in range(10):
    x = np.linspace(0, 1)
    y = np.random.random(x.size)
    fig, ax = w2.subplots(random.choice(names), dockArea=random.choice(areas))
    ax.plot(x, y)

sys.exit(app.exec())  # Run the application until all windows are closed

MultiPlot containing various images and line plots

import sys
import matplotlib.pyplot as plt
from PyQt5.QtWidgets import QApplication
import numpy as np
from mpl_qt_viz.visualizers import MultiPlot

app = QApplication(sys.argv)

# Generate a list of lists of artists and create a new MultiPlot with them.
ims = [[plt.imshow(np.random.random((512, 512))), plt.text(100, 100, str(i))] for i in range(3)]
mp = MultiPlot(ims, "Images")

#Adjust the figure and axes
plt.gcf().subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0)
mp.ax.get_xaxis().set_visible(False)
mp.ax.get_yaxis().set_visible(False)
mp.show()  # Show the widget

#Create a second MultiPlot with line plots
fig, ax = plt.subplots()
lines = [ax.plot(np.random.random((50,))) for i in range(3)]
mp2 = MultiPlot(lines, 'Lines')
mp2.show()

sys.exit(app.exec())

todo

Add example of ROI drawing tools.

Using the PlotNd widget to visualize hyperspectral imagery of a cancer cell PlotNd widget to visualize hyperspectral imagery of a cancer cell.

Using the DockablePlotsWindow to help organize a large number of plots.

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