Cmocean Colorscales in Python/v3

How to make Cmocean Colorscales in Python with Plotly.

Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.

New to Plotly?¶

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We also have a quick-reference cheatsheet (new!) to help you get started!

cmocean¶

cmocean is a package containing colormaps for commonly-used oceanographic variables. Below we provide a function to convert a cmocean colormap to a Plotly colorscale. Check out all of the cmocean colormaps below!

Imports¶

In [2]:

import plotly.plotly as py
import plotly.graph_objs as go
from plotly import tools

import cmocean

import numpy as np
import os

Defining Colormaps¶

In [3]:

import cmocean

def cmocean_to_plotly(cmap, pl_entries):
    h = 1.0/(pl_entries-1)
    pl_colorscale = []

    for k in range(pl_entries):
        C = map(np.uint8, np.array(cmap(k*h)[:3])*255)
        pl_colorscale.append([k*h, 'rgb'+str((C[0], C[1], C[2]))])

    return pl_colorscale

The examples data can be downloaded from here.

In [4]:

# Plotting the colorscale.

example_dir = os.path.join(os.path.dirname('__file__'), "examples")
hist2d = np.loadtxt(os.path.join(example_dir, "hist2d.txt"))
st_helens = np.loadtxt(os.path.join(example_dir,
                                        "st-helens_before-modified.txt.gz")).T
dx = dy = 0.05
y, x = np.mgrid[-5 : 5 + dy : dy, -5 : 10 + dx : dx]
z = np.sin(x)**10 + np.cos(10 + y*x) + np.cos(x) + 0.2*y + 0.1*x

elem_len = [len(hist2d), len(st_helens), len(z)]
max_len = max(elem_len)

def colorscale_plot(colorscale, title):
    trace1 = go.Heatmap(z=hist2d, colorscale=colorscale, showscale=False)
    trace2 = go.Heatmap(z=st_helens, colorscale=colorscale, y0=-5, x0=-5)
    trace3 = go.Heatmap(z=z,colorscale=colorscale, showscale=False)

    fig = tools.make_subplots(rows=1, cols=3, print_grid=False)
    fig.append_trace(trace1, 1, 1)
    fig.append_trace(trace2, 1, 2)
    fig.append_trace(trace3, 1, 3)

    fig['layout'].update(title=title)
    fig['layout']['xaxis2'].update(range=[0, 450])
    fig['layout']['yaxis2'].update(range=[0, 270])

    return fig

Thermal¶

In [5]:

thermal = cmocean_to_plotly(cmocean.cm.thermal, max_len)
py.iplot(colorscale_plot(colorscale=thermal, title='Thermal'))

Out[5]:

Haline¶

In [8]:

haline = cmocean_to_plotly(cmocean.cm.haline, max_len)
py.iplot(colorscale_plot(colorscale=haline, title='Haline'))

Out[8]:

Solar¶

In [9]:

solar = cmocean_to_plotly(cmocean.cm.solar, max_len)
py.iplot(colorscale_plot(colorscale=solar, title='Solar'))

Out[9]:

Ice¶

In [10]:

ice = cmocean_to_plotly(cmocean.cm.ice, max_len)
py.iplot(colorscale_plot(colorscale=ice, title='Ice'))

Out[10]:

Gray¶

In [11]:

gray = cmocean_to_plotly(cmocean.cm.gray, max_len)
py.iplot(colorscale_plot(colorscale=gray, title='Gray'))

Out[11]:

Oxy¶

In [12]:

oxy = cmocean_to_plotly(cmocean.cm.oxy, max_len)
py.iplot(colorscale_plot(colorscale=oxy, title='Oxy'))

Out[12]:

Deep¶

In [13]:

deep = cmocean_to_plotly(cmocean.cm.deep, max_len)
py.iplot(colorscale_plot(colorscale=deep, title='Deep'))

Out[13]:

Dense¶

In [15]:

dense = cmocean_to_plotly(cmocean.cm.dense, max_len)
py.iplot(colorscale_plot(colorscale=dense, title='Dense'))

Out[15]:

Algae¶

In [16]:

algae = cmocean_to_plotly(cmocean.cm.algae, max_len)
py.iplot(colorscale_plot(colorscale=algae, title='Algae'))

Out[16]:

Matter¶

In [17]:

matter = cmocean_to_plotly(cmocean.cm.matter, max_len)
py.iplot(colorscale_plot(colorscale=matter, title='Matter'))

Out[17]:

Turbid¶

In [18]:

turbid = cmocean_to_plotly(cmocean.cm.turbid, max_len)
py.iplot(colorscale_plot(colorscale=turbid, title='Turbid'))

Out[18]:

Speed¶

In [20]:

speed = cmocean_to_plotly(cmocean.cm.speed, max_len)
py.iplot(colorscale_plot(colorscale=speed, title='Speed'))

Out[20]:

Amp¶

In [21]:

amp = cmocean_to_plotly(cmocean.cm.amp, max_len)
py.iplot(colorscale_plot(colorscale=amp, title='Amp'))

Out[21]:

Tempo¶

In [22]:

tempo = cmocean_to_plotly(cmocean.cm.tempo, max_len)
py.iplot(colorscale_plot(colorscale=tempo, title='Tempo'))

Out[22]:

Phase¶

In [23]:

phase = cmocean_to_plotly(cmocean.cm.phase, max_len)
py.iplot(colorscale_plot(colorscale=phase, title='Phase'))

Out[23]:

Balance¶

In [24]:

balance = cmocean_to_plotly(cmocean.cm.balance, max_len)
py.iplot(colorscale_plot(colorscale=balance, title='Balance'))

Out[24]:

Delta¶

In [25]:

delta = cmocean_to_plotly(cmocean.cm.delta, max_len)
py.iplot(colorscale_plot(colorscale=delta, title='Delta'))

Out[25]:

Curl¶

In [26]:

curl = cmocean_to_plotly(cmocean.cm.curl, max_len)
py.iplot(colorscale_plot(colorscale=curl, title='Curl'))

Out[26]:

Reference¶

Learn more about Plotly colorscales here: https://plotly.com/python/colorscales/

Acknowledgment¶

Special thanks to Kristen Thyng for the statistics of colormaps.