Merge pull request #57 from kthyng/master

cpt-city update and some docs

Author: kthyng

README.rst

@@ -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

docs/source/index.rst

@@ -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
 ^^^^^
@@ -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
 
@@ -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
 ^^^^^
@@ -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.
 
@@ -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:
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^