Interactive Portrait Plot

This notebook shows usage examples of interactive Portrait Diagram. Detailed API description can be found here.

Import functions

[1]:

from bokeh.plotting import output_file, save, output_notebook

[2]:

from ESMBenchmarkViz import portrait_plot

[3]:

# Enable Bokeh output in the notebook
output_notebook()

Loading BokehJS ...

[4]:

import numpy as np

# Test dummy array -- fill random numbers for each array
data1 = np.random.randn(8, 7)
data2 = np.random.randn(8, 7)
data3 = np.random.randn(8, 7)
data4 = np.random.randn(8, 7)

"""
# Test dummy array -- fill same numbers for each array to make sure they are at the right position
data1 = np.full((8, 7), -2)
data2 = np.full((8, 7), -1)
data3 = np.full((8, 7), 1)
data4 = np.full((8, 7), 2)
"""

[4]:

'\n# Test dummy array -- fill same numbers for each array to make sure they are at the right position\ndata1 = np.full((8, 7), -2)\ndata2 = np.full((8, 7), -1)\ndata3 = np.full((8, 7), 1)\ndata4 = np.full((8, 7), 2)\n'

[5]:

data_all = [data1, data2, data3, data4]

xaxis_labels = ['A1', 'A2', 'A3', 'A4', 'A5', 'A6', 'A7']
yaxis_labels = ['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8']

xaxis_labels = ['Metric '+x for x in xaxis_labels]
yaxis_labels = ['Model '+y for y in yaxis_labels]

Basic usage examples

Following examples show portriat plots with different number of splits in each box.

[6]:

p = portrait_plot(
    data1,
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    width=600,
)

[7]:

p = portrait_plot(
    [data1, data2],
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    width=600,
)

[8]:

p = portrait_plot(
    [data1, data2, data3],
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    width=600,
)

[9]:

p = portrait_plot(
    data_all,  # or [data1, data2, data3, data4] (top, right, bottom, left: clockwise from top)
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    legend_labels=['Data1', 'Data2', 'Data3', 'Data4'],
    cmap_bounds=[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5],
    width=600,
)

[10]:

p = portrait_plot(
    [data1, data2, data3, data4, data1],
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    legend_labels=['Data1', 'Data2', 'Data3', 'Data4', 'Data1-2'],
    cmap_bounds=[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5],
    width=600,
)

[11]:

p = portrait_plot(
    [data1, data2, data3, data4, data1, data2],
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    legend_labels=['Data1', 'Data2', 'Data3', 'Data4', 'Data1-2', 'Data2-2'],
    cmap_bounds=[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5],
    width=600,
)

[12]:

p = portrait_plot(
    [data1, data2, data3, data4, data1, data2, data3],
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    legend_labels=['Data1', 'Data2', 'Data3', 'Data4', 'Data1-2', 'Data2-2', 'Data3-2'],
    cmap_bounds=[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5],
    width=600,
)

[13]:

p = portrait_plot(
    [data1, data2, data3, data4, data1, data2, data3, data4],
    xaxis_labels=xaxis_labels,
    yaxis_labels=yaxis_labels,
    legend_labels=['Data1', 'Data2', 'Data3', 'Data4', 'Data1-2', 'Data2-2', 'Data3-2', 'Data4-2'],
    cmap_bounds=[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5],
    width=600,
)

Save the plot

[14]:

# set output to static HTML file
output_file(filename="interactive_portrait_plot.html", title="Interactive Portrait Plot")

# save the results to a file
save(p)

# Result: [`interactive_portrait_plot.html`](interactive_scatter_plot.html)

[14]:

'/Users/lee1043/Documents/Research/git/ESMBenchmarkViz/docs/examples/interactive_portrait_plot.html'