Color maps of UV-CDAT

Import modules

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[1]:

import vcs, EzTemplate
import MV2
import numpy as np

Prepare a dummy array

(top) - We need a 2-D dummy array that will contain monotonically increasing numbers each of two rows, to be used for the visualization

[2]:

a=[]
num_levels = 224

for i in range(0,num_levels):
  a.append(i/float(num_levels))

for i in range(0,num_levels):
  a.append(i/float(num_levels))

a = MV2.array(a)
a = MV2.reshape(a, (-1,num_levels))

Colormap visualizing function

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  • Below function will visualize given colormaps to provide a selection guidance.

[3]:

def visualize(cmlst, v, loadcmap):

    T = vcs.createtemplate()
    T.blank(['title','mean','min','max','dataname','crdate','crtime',
         'units','zvalue','tvalue','xunits','yunits','xname','yname', 'legend'])

    cmlst_num = len(cmlst)
    nrows = int(round(cmlst_num/2.))

    M = EzTemplate.Multi(template=T, rows=nrows, columns=2)
    M.margins.top = 0.05
    M.margins.bottom = 0.05
    M.margins.left = 0.2
    M.margins.right = 0.2
    M.spacing.vertical= 0.005

    for i in range(0, cmlst_num):
        box = v.createboxfill()
        box.color_1 = 16
        box.color_2 = 240
        box.xticlabels('','') # Hide x-axis tick labels
        box.yticlabels('','') # Hide y-axis tick labels
        box.colormap = loadcmap(cmlst[i])

        if i >= nrows: #right column
            jj=1
            ii=i-nrows
            x = 0.81 # text starting x position
        else: # left column
            jj=0
            ii=i
            x = 0.01 # text starting x position

        t = M.get(row=ii, column=jj, legend='none')
        t.blank(['legend'])

        v.plot(a, t, box, bg=1)

        subplot_title = vcs.createtext()
        subplot_title.string = box.colormap
        subplot_title.x = x
        subplot_title.y = (t.box1.y1 + t.box1.y2) / 2.
        subplot_title.height = 8
        subplot_title.halign = 'left'
        subplot_title.valign = 'half'
        subplot_title.color = 'black'
        v.plot(subplot_title, t)
        v.removeobject(box)
        v.removeobject(subplot_title)

        #print box.colormap  ## List available color maps
    return(v)

Open a VCS canvas

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  • Let’s open a VCS canvas to play with!

[4]:

v = vcs.init(geometry={"width":600,"height":1200}, bg=1)
vcs.utils.defaultColorsRange = range(16,240)

VCS colormaps

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  • VCS is default module that is being used for the UV-CDAT. You can use VCS color maps which is loaded at the beginning.

[5]:

cmlst = v.listelements('colormap')
loadcmap = str
v = visualize(cmlst, v, loadcmap)

plot_title = v.createtext()
plot_title.string = 'VCS Colormaps'
plot_title.height = 15
plot_title.halign = 'center'
plot_title.valign = 'bottom'
plot_title.x = 0.5
plot_title.y = 0.96
v.plot(plot_title)

[5]:
../_images/Jupyter_Colormap_Tutorial_11_0.png

Matplotlib colormaps in VCS

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  • You can load and visualize Matplotlib colormaps in the VCS canvas.

  • Use vcs.colors.matplotlib2vcs to convert

  • For now if same name is already being used in VCS, new name with tail _000 is assigned, as showing below as “warning messages”.

  • You can also use vcs.utils.loadmatplotlibcolormaps() to bring all Matplotlib colormaps to VCS

[6]:

v.clear()

import matplotlib.pyplot as plt

# Get list of all available colormaps from matplotlib (except '_r' which is reversed one)
cmlst = [x for x in plt.colormaps() if not '_r' in x]
cmlst = sorted(cmlst, key=lambda s: s.lower()) # Sort as case-insensitive alphabet order

loadcmap = vcs.colors.matplotlib2vcs
v = visualize(cmlst, v, loadcmap)

plot_title.string = 'Matplotlib Colormaps for VCS'
v.plot(plot_title)

/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/vcs/colors.py:43: UserWarning: inferno colormap name was already existing, your colormap name will be: inferno_mpl_000
  (vcs_name, vcs_name_final))
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/vcs/colors.py:43: UserWarning: magma colormap name was already existing, your colormap name will be: magma_mpl_000
  (vcs_name, vcs_name_final))
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/vcs/colors.py:43: UserWarning: plasma colormap name was already existing, your colormap name will be: plasma_mpl_000
  (vcs_name, vcs_name_final))
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/vcs/colors.py:43: UserWarning: rainbow colormap name was already existing, your colormap name will be: rainbow_mpl_000
  (vcs_name, vcs_name_final))
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The spectral and spectral_r colormap was deprecated in version 2.0. Use nipy_spectral and nipy_spectral_r instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The Vega10 colormap was deprecated in version 2.0. Use tab10 instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The Vega20 colormap was deprecated in version 2.0. Use tab20 instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The Vega20b colormap was deprecated in version 2.0. Use tab20b instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The Vega20c colormap was deprecated in version 2.0. Use tab20c instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)
/Users/doutriaux1/anaconda2/envs/nightly2/lib/python2.7/site-packages/vcs/colors.py:43: UserWarning: viridis colormap name was already existing, your colormap name will be: viridis_mpl_000
  (vcs_name, vcs_name_final))

[6]:
../_images/Jupyter_Colormap_Tutorial_13_1.png