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Jul 19, 2016
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cpt-city update and some docs #57

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bfcc638
updated docs with new deep example and some typos
kthyng Jul 17, 2016
5864f60
added link to cpt-city with gmt
kthyng Jul 19, 2016
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2 changes: 1 addition & 1 deletion README.rst
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Expand Up @@ -8,7 +8,7 @@ Besides Python, the cmocean colormaps are also available for:
* For `MATLAB <http://www.mathworks.com/matlabcentral/fileexchange/57773-cmocean-perceptually-uniform-colormaps>`_ by `Chad Greene <http://www.chadagreene.com/>`_
* For R: `Oce <http://dankelley.github.io/oce/>`_ oceanographic analysis package by `Dan Kelley <http://www.dal.ca/faculty/science/oceanography/people/faculty/daniel-e-kelley.html>`_ and `Clark Richards <http://clarkrichards.org/>`_
* For `Ocean Data Viewer <https://github.com/kthyng/cmocean-odv>`_
* For `Generic Mapping Tools (GMT) <https://github.com/kthyng/cmocean-gmt>`_
* For Generic Mapping Tools (GMT) at `cpt-city <http://soliton.vm.bytemark.co.uk/pub/cpt-city/cmocean/index.html>`_ and on `github <https://github.com/kthyng/cmocean-gmt>`_
* For `Paraview <https://github.com/kthyng/cmocean-paraview>`_, inspired by `Phillip Wolfram <https://github.com/pwolfram>`_.
* In `Plotly <https://plot.ly/python/cmocean-colorscales/>`_
* Chad Greene's `Antartic Mapping Tools <http://www.mathworks.com/matlabcentral/fileexchange/47638-antarctic-mapping-tools>`_ in Matlab uses cmocean
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34 changes: 9 additions & 25 deletions docs/source/index.rst
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Expand Up @@ -145,17 +145,10 @@ deep

The *deep* colormap is sequential from light yellow to potentially represent shallower water through pale green to increasingly dark blue and purple to represent increasing depth.

.. plot::
:include-source:

import cmocean
import matplotlib.pyplot as plt
.. figure:: https://cloud.githubusercontent.com/assets/3487237/16900541/4af66c4c-4bf5-11e6-92a9-82eaa39cb18b.png
:target: http://iuryt.github.io/tutorial/Como_fazer_um_mapa02.html

fig = plt.figure(figsize=(8, 3))
ax = fig.add_subplot(1, 2, 1)
cmocean.plots.test(cmocean.cm.deep, ax=ax)
ax = fig.add_subplot(1, 2, 2)
cmocean.plots.quick_plot(cmocean.cm.deep, ax=ax)
Bathymetry plot, by `Iury Sousa <http://iuryt.github.io/>`_

dense
^^^^^
Expand All @@ -172,8 +165,6 @@ algae

The *algae* colormap is sequential with whitish-green for low values and increasing in green with increasing value, which could be used to represent an increase in chlorophyll in the water. Two examples of this colormap are shown below, from Texas A&M University gliders. This colormap is based on matplotlib's Greens, but was recreated from scratch using the viscm tool.

.. image:: http://gcoos2.tamu.edu/gandalf_data/deployments/tamu/unit_540/plots/sci_flbbcd_chlor_units.png
:target: http://gcoos2.tamu.edu/gandalf_data/deployments/tamu/unit_540/plots/sci_flbbcd_chlor_units.png
.. image:: http://gcoos2.tamu.edu/gandalf_data/deployments/tamu/unit_541/plots/sci_flbbcd_chlor_units.png
:target: http://gcoos2.tamu.edu/gandalf_data/deployments/tamu/unit_541/plots/sci_flbbcd_chlor_units.png

Expand Down Expand Up @@ -217,17 +208,10 @@ amp

The *amp* colormap is sequential from whitish to dark red and could be used to represent an increase in wave height values. This colormap is the positive half of the *balance* colormap.

.. plot::
:include-source:

import cmocean
import matplotlib.pyplot as plt
.. figure:: https://cloud.githubusercontent.com/assets/3487237/16920916/840d91d4-4cdd-11e6-8db5-f93cd61b78c2.png
:target: http://soliton.vm.bytemark.co.uk/pub/cpt-city/

fig = plt.figure(figsize=(8, 3))
ax = fig.add_subplot(1, 2, 1)
cmocean.plots.test(cmocean.cm.amp, ax=ax)
ax = fig.add_subplot(1, 2, 2)
cmocean.plots.quick_plot(cmocean.cm.amp, ax=ax)
Earthquake magnitude, by `Natalie Accardo <http://www.natalieaccardo.com/>`_ using GMT.

tempo
^^^^^
Expand Down Expand Up @@ -344,7 +328,7 @@ Output a dictionary to define a colormap with:
import cmocean

cmdict = cmocean.tools.get_dict(cmocean.cm.matter, N=9)
print cmdict
print(cmdict)

Make a colormap instance with ``cmap = cmocean.tools.cmap(rgbin, N=10)`` given the rgb input array.

Expand Down Expand Up @@ -375,11 +359,11 @@ cmocean available elsewhere!
* For `MATLAB <http://www.mathworks.com/matlabcentral/fileexchange/57773-cmocean-perceptually-uniform-colormaps>`_ by `Chad Greene <http://www.chadagreene.com/>`_
* For R: `Oce <http://dankelley.github.io/oce/>`_ oceanographic analysis package by `Dan Kelley <http://www.dal.ca/faculty/science/oceanography/people/faculty/daniel-e-kelley.html>`_ and `Clark Richards <http://clarkrichards.org/>`_
* For `Ocean Data Viewer <https://github.com/kthyng/cmocean-odv>`_
* For `Generic Mapping Tools (GMT) <https://github.com/kthyng/cmocean-gmt>`_
* For Generic Mapping Tools (GMT) at `cpt-city <http://soliton.vm.bytemark.co.uk/pub/cpt-city/cmocean/index.html>`_ and on `github <https://github.com/kthyng/cmocean-gmt>`_
* For `Paraview <https://github.com/kthyng/cmocean-paraview>`_, inspired by `Phillip Wolfram <https://github.com/pwolfram>`_.
* In `Plotly <https://plot.ly/python/cmocean-colorscales/>`_
* Chad Greene's `Antartic Mapping Tools <http://www.mathworks.com/matlabcentral/fileexchange/47638-antarctic-mapping-tools>`_ in Matlab uses cmocean
* In PyNcView: coming soon!
.. * In PyNcView: coming soon!

Examples of beautiful visualizations:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Expand Down