Introduction

pip3 install chartkra

chartkra facilitates the chart displaying on PyQt widgets by the use of matplotlib. It can easily to display the following figures:

1. plots
2. bars
3. pies
4. heatmaps

Usage

It's very easy to getting started with chartkra. What you need to do is to instantiate a chartkra object, and pass its get_widget function to PyQt Widget's addWidget function:

# initialize
chart = chartkra()
self.gridLayout.addWidget(chart.get_widget())
# draw charts
# ...

It's the same way to showing a heatmap, just need to instantiate a HeatMap object instead.

# initialize
heatmap = HeatMap()
self.gridLayout.addWidget(heatmap.get_widget())
# draw heatmap
# ...

Drawing Figures

Drawing Plots

Use function draw_plot to draw. Pass what you're going to show on x axis to listx, and what you're going to show on y axis to listy.

chart.draw_plot(listx=['12/01', '12/02', '12/03'], listy=[1, 2, 3])

Drawing Bars

Use function draw_bar to draw. Pass what you're going to show on x axis to listx, and what you're going to show on y axis to listy.

chart.draw_bar(listx=['zone1', 'zone2', 'zone3'], listy=[1, 2, 3])

Drawing Pies

Use function draw_pie to draw. The sizes and the labels reference the partition in the pie figure respectively.

chart.draw_pie(sizes=[1, 2, 3], labels=['zone1', 'zone2', 'zone3'])

Drawing Heatmaps

Example: Pedestrian Trajectory Heatmap

codes:

heatmap.set_zone(pic='office_inte.jpg', width=8.2, height=10.836, points=points)
heatmap.set_display(accuracy=25, style=plt.cm.jet, rotation=0, title='Pedestrian Trajectory Heatmap')
heatmap.set_colorbar(position='right', width='5%', padding=0.1)
heatmap.show()

When creating a heatmap, it is needed to declare the function set_zone and its arguments:

• pic: the path of picture which you want to show in heatmap.
• width: width of the picture(zone).
• height: height of the picture(zone).
• points: the points scattered in the zone, the units of each point need to be the same as the width and the height of picture(zone).

By setting up argument title and title_padding in function set_display, you can customized the title of figure and the padding between title and figure.

Accuracy

It is customized by argument accuracy in function set_display

Styles

It is customized by argument style in function set_display. The accepted styles can be found on https://matplotlib.org/examples/color/colormaps_reference.html

Orientations

It is customized by argument rotation in function set_display. The accepted values includes 0, 90, 180 and 270.

Colorbars

It is customized by assign arguments in function set_colorbar

• position: accepted values includes top, right, left, bottom.
• width: the width of the colorbar.
• padding: distance between colorbar and figure.

Others

• The showing of colorbars is not requires. The colorbars will not be showed by default if you don't declare function set_colorbar.
• By using function disable_heatmap_layer, the figure will only display picture.
• By using function disable_img_layer, the figure will only display heatmap layer.

Save Figure to File

In general situations, using function show would be enough for showing a figure. If you want to save the figure to file as well, just declare function show_and_save_fig instead and assign arguments filename and display resolution like:

heatmap.show_and_save_fig(filename='sample.png', dpi=150)