File | Date | Author | Commit |
---|---|---|---|
colorview2d | 2016-09-26 | Alois Dirnaichner | [9786d0] + Rewrite the README file. |
test | 2016-09-26 | Alois Dirnaichner | [bc843f] + Cleaned the project dir further. |
LICENCE.txt | 2015-02-11 | Alois Dirnaichner | [3181b7] Added licence file. |
MANIFEST.in | 2015-02-03 | Alois Dirnaichner | [75c070] Fixed the line in the MANIFEST.in file that led... |
README.md | 2016-09-26 | Alois Dirnaichner | [9786d0] + Rewrite the README file. |
REQUIREMENTS.txt | 2015-06-24 | Alois Dirnaichner | [7f61ed] Added correct requirements from the pip freeze.... |
VERSION.txt | 2015-06-16 | Alois Dirnaichner | [742b62] Update to the Readme |
setup.py | 2016-09-26 | Alois Dirnaichner | [88a1b5] Cleaned mod files. |
Use colorview2d to visualize and analize 2d data with (linear) axes.
Features:
~~~~~~~~~
Installation
~~~~~~~~~~~~
You can use the python package index via pip
sudo pip2.7 install --upgrade colorview2d
or easy_install
sudo easy_install --upgrade colorview2d
Note that numpy can not be installed via the
python package index. Please install these packages via the package
manager that is shipped with your linux distribution.
Usage
~~~~~
I stronlgy recommend to use ipython interactive shell for this tutorial.
We initialize some random data with x and y ranges:
data = np.random.random((100, 100))
xrange = (0., np.random.random())
yrange = (0., np.random.random())
Obtain a colorview2d.CvFig object:
cvfig = colorview2d.CvFig(data, (yrange, xrange))
Note that the order of the ranges (y range first) is not a typo.
It is reminiscent of the rows-first order of the 2d array.
What is the data about? We add some labels:
cvfig.config['Xlabel'] = 'foo (f)'
cvfig.config['Ylabel'] = 'bar (b)'
cvfig.config['Zlabel'] = 'nicyness (n)'
Let us have a look.
cvfig.show_plt_fig()
We do not like the font and the ticks labels are too small
cvfig.config.update({'Font': 'Ubuntu', 'Fontsize': 16})
Also, the colormap, being default matplotlib's jet, is not greyscale-compatible, so we change to
'Blues' (have a look at the matplotlib documentation to get a list of colormaps).
cvfig.config['Colormap'] = 'Blues'
Its time to plot a pdf and save the config
cvfig.plot_pdf('Nice_unmodified.pdf')
cvfig.save_config('Nice_unmodified.cv2d')
We realize that there is some (unphysical :) noise in the data. Nicyness does not fluctuate
so much along foo or bar and our cheap nice-intstrument produced some additional fluctuations.
cvfig.add_mod('Smooth', (1, 1))
also we are interested more in the change of our nice landscape and not in its absolute
values so we derive along the bar axis
cvfig.add_mod('Derive')
Have a look at the mods/ folder for other mods and documentation on the arguments.
It is also straightforward to create your own mod there. Just have a look at the other mods
in the folder.
To re-use this data later (without having to invoke colorview2d again), we can store
the data to a gnuplot-style plain text file.
cvfig.fileloader.save_gpfile('Nice_smooth_and_derived.dat')
This tutorial only covers a part of the features.
More documentation on colorview2d will be added soon.
26.9.2015, Alois Dirnaichner