A Simple Tool for Ploting the Heatmap Overlay Image

Jupyter Notebook Demo

HeatMap Class: 3 inputs:

1. image: image path (string) or image value (numpy array)
2. heatmap: 2-D numpy value (no shape restriction)
3. (optional) gaussian filter: mosaic smoothing (gaussian_std, default is 10. when set to 0, means no filter apply)

from HeatMap import HeatMap
# input a image path and a numpy array heatmap
hm = HeatMap('demo_image.jpg',heat_map)
# or input a numpy array image and heatmap
hm = HeatMap(image,heat_map,gaussian_std=0)

Method 1 plot: 6 parameters (all optional)

1. transparency: define the transparency of heamap overlay (lower -> more transparent, default is 0.7)
2. color_map: color map style (default is bwr)
3. show_axis: show axis or not (boolean True/False, default is False)
4. show_original: show original image (boolean True/False, default is False)
5. show_colorbar: show color bar (boolean True/False, default is False)
6. width_pad: the width padding (default is 0, set to negative value for reducing the space between figures)

#simple default plot
hm.plot()

#customised plot
hm.plot(transparency=0.6,
        color_map='seismic',
        show_axis=True,
        show_original=True,
        show_colorbar=True,
        width_pad=-10)

Method 2 save: 1 required, 8+ optional*

required

1. filename: filename for saved figure (string)

optinal:

1. save_path: figure saving directory (default is the current working directory)
2. formate: figure saving fomate (jpg, jpeg, png, pdf, ps, eps and svg), default is 'png'
3. transparency: define the transparency of heamap overlay (lower -> more transparent, default is 0.7)
4. color_map: color map style (default is bwr)
5. show_axis: show axis or not (boolean True/False, default is False)
6. show_original: show original image (boolean True/False, default is False)
7. show_colorbar: show color bar (boolean True/False, default is False)
8. width_pad: the width padding (default is 0, set to negative value for reducing the space between figures)
9. other parameters from pyplot.savefig can be used here

# simple save
hm.save('heatmap_result_1')

# customised save
hm.save('heatmap_result_2','png',
        transparency=0.6,
        color_map='seismic',
        show_axis=True,
        show_original=True,
        show_colorbar=True,
        width_pad=-10)