Annotated Heatmap Using Python View Node

[HeatherPikairos]

Hello Forum!

As I mentioned in a previous topic, I’m learning how to make plots/charts with Matplotlib in Python, so I’m sharing what I have created in case the workflows are useful to other KNIMErs

This time I’m sharing an Annotated Heatmap generated using the -Python View- node and a series of selection widgets to select colours and labels.

You can find my workflow on the hub:

20230426 Pikairos Annotated Heatmap using Python View for KNIME 4.7 –...

I hope this is useful
Thanks
Heather

[HeatherPikairos]

Sharing the Python code for improved searching on Google etc.

import knime.scripting.io as knio
from io import BytesIO
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import pandas

#vertical axis
vertical = knio.flow_variables['vertical_axis']

#horizontal axis
horizontal = knio.flow_variables['horizontal_axis']

#color map to use
c = knio.flow_variables['colour_scheme']

#input data
data = knio.input_tables[0].to_pandas()
matrix = data.select_dtypes(include='number').to_numpy()

# print(matrix)

#plot creation
fig, ax = plt.subplots()

#image size
im = ax.imshow(matrix,cmap=c,vmin=-1,vmax=1)

# We want to show all ticks...
ax.set_xticks(np.arange(len(data[horizontal])))
ax.set_yticks(np.arange(len(data[vertical])))

# ... and label them with the respective list entries
ax.set_xticklabels(data[horizontal],size=knio.flow_variables['label_size'])
ax.set_yticklabels(data[vertical],size=knio.flow_variables['label_size'])

# Rotate the tick labels and set their alignment.
plt.setp(ax.get_xticklabels(), rotation=45, ha="right",
         rotation_mode="anchor")

# Loop over data dimensions and create text annotations.
for i in range(np.size(matrix[1,:])):
    for j in range(np.size(matrix[:,1])):
        text = ax.text(j, i, matrix[i, j],
                       ha="center", va="center", color=knio.flow_variables['font_colour_indentifier'], size=knio.flow_variables['font_size'],rotation=knio.flow_variables['label_angle_int'])

#plot title set
ax.set_title(knio.flow_variables['title_input'])

#resizing
fig.tight_layout()
#plt.show()

# Create buffer to write into
buffer = BytesIO()
# Create plot and write it into the buffer
plt.savefig(buffer, format='svg')
# The output is the content of the buffer
output_image = buffer.getvalue()

# Assign the figure to the output_view variable
knio.output_view = knio.view(fig)  # alternative: knio.view_matplotlib()

[aworker]

Hi @HeatherPikairos

Thank you for sharing this workflow with the KNIME community !

It works like a charm !

Best
Ael