How to make `Heatmaps` in `Bokeh` with a continuous color map, using Python 3?

Question

I was trying to replicate this style of HeatMap that maps continuous values to a LinearColorMapper instance: http://docs.bokeh.org/en/latest/docs/gallery/unemployment.html I wanted to make a HeatMap (w/ either charts or rect) and then add a single selection widget to select the obsv_id and then a slider widget to go through the dates.

However, I was having trouble in the beginning with the HeatMap itself with a single obsv_id/date pair. What am I doing wrong in creating this HeatMap? This would essentially be a 3x3 rectangle plot of the size variable and the loc variable.

Bonus: Can you help me/give some advice on how to wire the output of these widgets to control the plot?

I saw these posts but all of the examples use actual hex colors as a list instead of mapping using a continuous measure: python bokeh, how to make a correlation plot? http://docs.bokeh.org/en/latest/docs/gallery/categorical.html

# Init
import numpy as np
import pandas as pd
from bokeh.plotting import figure, output_notebook, output_file, reset_output, show, ColumnDataSource
from bokeh.models import LinearColorMapper
reset_output()
output_notebook()

np.random.seed(0)

# Coords
dates = ["07-3","07-11","08-6","08-28"]
#locs = ["air","water","earth"]
locs = [0,1,2]
size = [3.0, 0.2, 0.025]
observations = ["obsv_%d"%_ for _ in range(10)]


# Data
Ar_tmp = np.zeros(( len(dates)*len(locs)*len(size)*len(observations), 5 ), dtype=object)

i = 0
for date in dates:
    for loc in locs:
        for s in size:
            for obsv_id in observations:
                Ar_tmp[i,:] = np.array([obsv_id, date, loc, s, np.random.random()])
                i += 1
DF_tmp = pd.DataFrame(Ar_tmp, columns=["obsv_id", "date", "loc", "size", "value"])
DF_tmp["value"] = DF_tmp["value"].astype(float)
DF_tmp["size"] = DF_tmp["size"].astype(float)
DF_tmp["loc"] = DF_tmp["loc"].astype(float)
#     obsv_id   date    loc   size     value
# 0    obsv_0   07-3    air    3.0  0.548814
# 1    obsv_1   07-3    air    3.0  0.715189
# 2    obsv_2   07-3    air    3.0  0.602763
# 3    obsv_3   07-3    air    3.0  0.544883
# 4    obsv_4   07-3    air    3.0  0.423655

mapper = LinearColorMapper(low = DF_tmp["value"].min(), high = DF_tmp["value"].max())

# # Create Heatmap of a single observation and date pair
query_idx = set(DF_tmp.index[DF_tmp["obsv_id"] == "obsv_0"]) & set(DF_tmp.index[DF_tmp["date"] == "08-28"])

# p = HeatMap(data=DF_tmp.loc[query_idx,:], x="loc", y="size", values="value")
p = figure()
p.rect(x="loc", y="size", 
       source=ColumnDataSource(DF_tmp.loc[query_idx,:]),
       fill_color={'field': 'value', 'transform': mapper},
       line_color=None)
show(p)

My Error:

# Javascript error adding output!
# TypeError: Cannot read property 'length' of null
# See your browser Javascript console for more details.

Answer 1

You have to provide a palette to LinearColorMapper. For example:

mapper = LinearColorMapper(
    palette='Magma256',
    low=DF_tmp["value"].min(),
    high=DF_tmp["value"].max()
)

From the LinearColorMapper doc:

class LinearColorMapper(palette=None, **kwargs)

Map numbers in a range [low, high] linearly into a sequence of colors (a palette).

---

Not related to your exception, but you'll also need to pass a width and height parameters to p.rect().