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https://github.com/matplotlib/trendvis
https://github.com/matplotlib/trendvis
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/matplotlib/trendvis
- Owner: matplotlib
- License: other
- Created: 2015-03-11T05:03:16.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2022-11-07T23:18:32.000Z (about 2 years ago)
- Last Synced: 2024-04-14T01:46:26.868Z (8 months ago)
- Language: Python
- Size: 394 KB
- Stars: 114
- Watchers: 34
- Forks: 15
- Open Issues: 2
-
Metadata Files:
- Readme: README.rst
- License: LICENSE.txt
Awesome Lists containing this project
- my-awesome-starred - trendvis - (Python)
README
========
TrendVis
========
TrendVis is a plotting package that uses
`matplotlib `_ to create information-dense,
sparkline-like, quantitative visualizations of multiple disparate data sets in
a common plot area against a common variable. This plot type is particularly
well-suited for time-series data. The results speak for themselves:
.. image:: https://raw.githubusercontent.com/mscross/scipy_proceedings/trendvis/papers/mellissa_cross_t/barredplot.png
:target: https://raw.githubusercontent.com/mscross/scipy_proceedings/trendvis/papers/mellissa_cross_t/barredplot.png
:alt: TrendVis example
For further reading on TrendVis, see the `SciPy 2015 Proceedings `_.
============
Installation
============
TrendVis is pure Python, natively supports Python 2 and 3, and depends only on
`matplotlib `_ version 1.2 or greater.
Setup and installation is simple::
pip install -U trendvis
or, if you would like to develop the package, fork and clone the repo then run::
python setup.py develop
at package root.
==============
Quick Examples
==============
Below are several examples showing various features in TrendVis and a typical
workflow. Version >= 0.2.1 is required.
Single column ``XGrid``
-----------------------
.. code-block:: python
import numpy as np
import matplotlib.pyplot as plt
import trendvis
# Pseudorandom data and plot attributes
random_generator = np.random.RandomState(seed=123)
yvals = random_generator.rand(10)
# Plot attributes
nums = 10
lw = 1.5
# convenience function trendvis.gridwrapper() is available
# to initialize XGrid and do most of the formatting shown here
ex0 = trendvis.XGrid([1,2,1], figsize=(5,5))
# Convenience function for plotting line data
# Automatically colors y axis spines to
# match line colors (auto_spinecolor=True)
trendvis.plot_data(ex0,
[[(np.linspace(0, 9.5, num=nums), yvals, 'blue')],
[(np.linspace(1, 9, num=nums), yvals*5, 'red')],
[(np.linspace(0.5, 10, num=nums), yvals*10, 'green')]],
lw=lw, markeredgecolor='none', marker='s')
# Get rid of extra spines
ex0.cleanup_grid()
ex0.set_spinewidth(lw)
ex0.set_all_ticknums([(2, 1)], [(0.2, 0.1), (1, 0.5), (2, 1)])
ex0.set_ticks(major_dim=(7, 3), minor_dim=(4, 2))
ex0.set_ylabels(['stack axis 0', 'stack axis 1', 'stack axis 2'])
# In XGrid.fig.axes, axes live in a 1 level list
# In XGrid.axes, axes live in a nested list of [row][column]
ex0.axes[2][0].set_xlabel('Main Axis', fontsize=14)
# Compact the plot
ex0.fig.subplots_adjust(hspace=-0.3)
.. image:: https://cloud.githubusercontent.com/assets/2184487/8859118/f4706b72-3140-11e5-9351-5182977a991c.png
:target: https://cloud.githubusercontent.com/assets/2184487/8859118/f4706b72-3140-11e5-9351-5182977a991c.png
:alt: Single column XGrid
Two-row ``YGrid`` with frame
----------------------------
.. code-block:: python
import numpy as np
import matplotlib.pyplot as plt
import trendvis
# Pseudorandom data
random_generator = np.random.RandomState(seed=1234)
xvals = random_generator.rand(20)
# Plot attributes
numpts = 20
lw = 1.5
# Initialize a YGrid
ex1 = trendvis.YGrid([1, 2, 1], yratios=[1, 2], figsize=(5,5))
# Convenience function
trendvis.plot_data(ex1,
[[(xvals, np.linspace(2, 18.5, num=numpts), 'blue')],
[(xvals*5, np.linspace(1, 17, num=numpts), 'red')],
[(xvals*10, np.linspace(0.5, 20, num=numpts), 'green')]],
lw=lw, auto_spinecolor=True, markeredgecolor='none', marker='s')
# Remove extra spines, color stack (y) ticks
ex1.cleanup_grid()
ex1.set_spinewidth(lw)
# Tick, tick label formatting
ex1.set_all_ticknums([(0.2, 0.1), (1, 0.5), (2, 1)], [(2, 1), (2, 1)])
ex1.set_ticks(major_dim=(7, 3), minor_dim=(4, 2))
ex1.set_ylim([(0, 15, 20), (1, 0, 11)])
# Axes labels
ex1.set_xlabels(['stack axis 0', 'stack axis 1', 'stack axis 2'])
ex1.axes[0][0].set_ylabel('Main Axis 0', fontsize=14)
ex1.axes[2][1].set_ylabel('Main Axis 1', fontsize=14,
rotation=270, labelpad=14)
# Draw boxes around each row
ex1.draw_frame()
# Broken axis cutout marks also available, try this instead of the frame:
# ex0.draw_cutout(di=0.05)
# Compact the plot
ex1.fig.subplots_adjust(wspace=-0.3)
.. image:: https://cloud.githubusercontent.com/assets/2184487/8859244/b07c0f9c-3141-11e5-8c1c-7d20f77ce7ee.png
:target: https://cloud.githubusercontent.com/assets/2184487/8859244/b07c0f9c-3141-11e5-8c1c-7d20f77ce7ee.png
:alt: Two-column YGrid
Three-column ``XGrid`` with advanced features
---------------------------------------------
.. code-block:: python
import numpy as np
import matplotlib.pyplot as plt
import trendvis
# Make some pseudorandom data
random_generator = np.random.RandomState(seed=123)
yvals = random_generator.rand(40)
yvals1 = np.copy(yvals)
yvals1[20:] = np.array([0.2, 0.3, 0.2, 0.5, 0.34, 0.24,
0.15, 0.23, 0.26, 0.21] * 2)
numpts = 40
lw = 1.5
x0 = np.linspace(2, 49.5, num=numpts)
x1 = np.linspace(1, 49, num=numpts)
x11 = np.linspace(1.5, 47.5, num=numpts)
twin0 = np.linspace(2, 50, num=numpts)
twin1 = np.linspace(0.5, 48, num=numpts)
# Initialize XGrid and twin axes
ex2 = trendvis.XGrid([3, 4], xratios=[1, 3, 2], figsize=(5, 5),
startside='right')
ex2.make_twins([0, 1])
# Convenience function
trendvis.plot_data(ex2,
[[(x0, yvals, 'blue')],
[(x1, yvals1*5, 'red'), (x11, yvals1*5.2, 'orchid')],
[],
[(twin1, yvals*2, '0.5')]],
lw=lw, marker=None)
# Adjust twinned y-axis positions for readability
ex2.move_spines(twin_shift=0.6)
# For any other kind of plot (fill_between, scatter, errorbar, etc),
# get axis and plot directly
# Note: ex2.axes[2][2] == ex2.get_axis(0, xpos=2, is_twin=True)
for ax in ex2.axes[2]:
ax.fill_between(twin0, yvals+0.075, yvals-0.1,
edgecolor='none', color='darkorange')
# Handle axis ticks
ex2.cleanup_grid()
ex2.set_spinewidth(lw)
ex2.autocolor_spines()
ex2.set_all_ticknums([(2, 1), (2, 1), (2, 1)],
[(0.2, 0.1), (1, 0.5), (1, 0.25), (0.5, 0.25)])
ex2.set_ticks(major_dim=(6, 1.5), minor_dim=(3, 1))
ex2.set_ylabels(['row 0', 'row 1', 'twin row 0', 'twin row 1'])
# Rotate x-axis tick labels
for ax in ex2.fig.axes:
plt.setp(ax.xaxis.get_majorticklabels(), rotation=45)
# Draw a vertical bar behind the data - horizontal bars available too
ex2.draw_bar(ex2.axes[1][2], ex2.axes[0][2], (45, 47), color='lightblue')
# Ok to set axis limits after drawing on figure using TrendVis methods,
# TrendVis will reset the bar to the right place!
ex2.set_xlim([(0, 0, 3), (1, 13, 24), (2, 43, 50)])
ex2.set_ylim([(2, 0, 2)])
# matplotlib annotations supported
ex2.get_axis(0).text(0, 0.75, 'Text')
# Cutouts instead of frames
ex2.draw_cutout(lw=lw)
# Set the suptitle and compact the plot
ex2.fig.suptitle('Title', fontsize=16, y=1.05);
ex2.fig.subplots_adjust(hspace=-0.1)
.. image:: https://cloud.githubusercontent.com/assets/2184487/8860699/097e51fa-314b-11e5-93e5-eb158aa5b801.png
:target: https://cloud.githubusercontent.com/assets/2184487/8860699/097e51fa-314b-11e5-93e5-eb158aa5b801.png
:alt: Three-column XGrid with advanced features
===========================
Examples in Published Works
===========================
*Great Basin hydrology, paleoclimate, and connections with the North Atlantic: A speleothem stable isotope and trace element record from Lehman Caves, NV* by Mellissa Cross, David McGee, Wallace S. Broecker, Jay Quade, Jeremy D. Shakun, Hai Cheng, Yanbin Lu, and R. Lawrence Edwards. doi:`10.1016/j.quascirev.2015.06.016 `_
Figures 2, 3, 4, 5, and panels 1 and 2 in figure 6 made with TrendVis.
Additional references to works containing TrendVis figures are welcome!