Revision: 6194
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6194&view=rev
Author: jdh2358
Date: 2008-10-15 02:33:38 +0000 (Wed, 15 Oct 2008)
Log Message:
-----------
using exiting examples rather than new pyplot ones for screenshots
Modified Paths:
--------------
trunk/matplotlib/doc/users/intro.rst
trunk/matplotlib/doc/users/screenshots.rst
Removed Paths:
-------------
trunk/matplotlib/doc/pyplots/screenshots_barchart_demo.py
trunk/matplotlib/doc/pyplots/screenshots_date_demo.py
trunk/matplotlib/doc/pyplots/screenshots_ellipse_demo.py
trunk/matplotlib/doc/pyplots/screenshots_fill_demo.py
trunk/matplotlib/doc/pyplots/screenshots_histogram_demo.py
trunk/matplotlib/doc/pyplots/screenshots_path_patch_demo.py
trunk/matplotlib/doc/pyplots/screenshots_pie_demo.py
trunk/matplotlib/doc/pyplots/screenshots_scatter_demo.py
trunk/matplotlib/doc/pyplots/screenshots_simple_plots.py
trunk/matplotlib/doc/pyplots/screenshots_slider_demo.py
trunk/matplotlib/doc/pyplots/screenshots_subplot_demo.py
trunk/matplotlib/doc/pyplots/screenshots_table_demo.py
Deleted: trunk/matplotlib/doc/pyplots/screenshots_barchart_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_barchart_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_barchart_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,24 +0,0 @@
-# a bar plot with errorbars
-# a bar plot with errorbars
-from pylab import *
-
-N = 5
-menMeans = (20, 35, 30, 35, 27)
-menStd = ( 2, 3, 4, 1, 2)
-
-ind = arange(N) # the x locations for the groups
-width = 0.35 # the width of the bars
-p1 = bar(ind, menMeans, width, color='r', yerr=menStd)
-
-womenMeans = (25, 32, 34, 20, 25)
-womenStd = ( 3, 5, 2, 3, 3)
-p2 = bar(ind+width, womenMeans, width, color='y', yerr=womenStd)
-
-ylabel('Scores')
-title('Scores by group and gender')
-xticks(ind+width, ('G1', 'G2', 'G3', 'G4', 'G5') )
-xlim(-width,len(ind))
-yticks(arange(0,41,10))
-
-legend( (p1[0], p2[0]), ('Men', 'Women'), shadow=True)
-show()
Deleted: trunk/matplotlib/doc/pyplots/screenshots_date_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_date_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_date_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,42 +0,0 @@
-#!/usr/bin/env python
-"""
-Show how to make date plots in matplotlib using date tick locators and
-formatters. See major_minor_demo1.py for more information on
-controlling major and minor ticks
-
-All matplotlib date plotting is done by converting date instances into
-days since the 0001-01-01 UTC. The conversion, tick locating and
-formatting is done behind the scenes so this is most transparent to
-you. The dates module provides several converter functions date2num
-and num2date
-
-"""
-
-import datetime
-import matplotlib.pyplot as plt
-import matplotlib.dates as mdates
-import matplotlib.mlab as mlab
-
-years = mdates.YearLocator() # every year
-months = mdates.MonthLocator() # every month
-yearsFmt = mdates.DateFormatter('%Y')
-
-intc = mlab.csv2rec('mpl_examples/data/intc.csv')
-
-fig = plt.figure()
-ax = fig.add_subplot(111)
-ax.plot(intc.date, intc.adj_close)
-
-# format the ticks
-ax.xaxis.set_major_locator(years)
-ax.xaxis.set_major_formatter(yearsFmt)
-ax.xaxis.set_minor_locator(months)
-ax.autoscale_view()
-
-# format the coords message box
-def price(x): return '$%1.2f'%x
-ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
-ax.format_ydata = price
-
-ax.grid(True)
-plt.show()
Deleted: trunk/matplotlib/doc/pyplots/screenshots_ellipse_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_ellipse_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_ellipse_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,149 +0,0 @@
-
-# This example can be boiled down to a more simplistic example
-# to show the problem, but bu including the upper and lower
-# bound ellipses, it demonstrates how significant this error
-# is to our plots.
-
-import math
-from pylab import *
-from matplotlib.patches import Ellipse, Arc
-
-# given a point x, y
-x = 2692.440
-y = 6720.850
-
-# get is the radius of a circle through this point
-r = math.sqrt( x*x+y*y )
-
-# show some comparative circles
-delta = 6
-
-
-##################################################
-def custom_ellipse( ax, x, y, major, minor, theta, numpoints = 750, **kwargs ):
- xs = []
- ys = []
- incr = 2.0*math.pi / numpoints
- incrTheta = 0.0
- while incrTheta <= (2.0*math.pi):
- a = major * math.cos( incrTheta )
- b = minor * math.sin( incrTheta )
- l = math.sqrt( ( a**2 ) + ( b**2 ) )
- phi = math.atan2( b, a )
- incrTheta += incr
-
- xs.append( x + ( l * math.cos( theta + phi ) ) )
- ys.append( y + ( l * math.sin( theta + phi ) ) )
- # end while
-
- incrTheta = 2.0*math.pi
- a = major * math.cos( incrTheta )
- b = minor * math.sin( incrTheta )
- l = sqrt( ( a**2 ) + ( b**2 ) )
- phi = math.atan2( b, a )
- xs.append( x + ( l * math.cos( theta + phi ) ) )
- ys.append( y + ( l * math.sin( theta + phi ) ) )
-
- ellipseLine = ax.plot( xs, ys, **kwargs )
-
-
-
-
-##################################################
-# make the axes
-ax1 = subplot( 311, aspect='equal' )
-ax1.set_aspect( 'equal', 'datalim' )
-
-# make the lower-bound ellipse
-diam = (r - delta) * 2.0
-lower_ellipse = Ellipse( (0.0, 0.0), diam, diam, 0.0, fill=False,
edgecolor="darkgreen" )
-ax1.add_patch( lower_ellipse )
-
-# make the target ellipse
-diam = r * 2.0
-target_ellipse = Ellipse( (0.0, 0.0), diam, diam, 0.0, fill=False,
edgecolor="darkred" )
-ax1.add_patch( target_ellipse )
-
-# make the upper-bound ellipse
-diam = (r + delta) * 2.0
-upper_ellipse = Ellipse( (0.0, 0.0), diam, diam, 0.0, fill=False,
edgecolor="darkblue" )
-ax1.add_patch( upper_ellipse )
-
-# make the target
-diam = delta * 2.0
-target = Ellipse( (x, y), diam, diam, 0.0, fill=False, edgecolor="#DD1208" )
-ax1.add_patch( target )
-
-# give it a big marker
-ax1.plot( [x], [y], marker='x', linestyle='None', mfc='red', mec='red',
markersize=10 )
-
-##################################################
-# make the axes
-ax = subplot( 312, aspect='equal' , sharex=ax1, sharey=ax1)
-ax.set_aspect( 'equal', 'datalim' )
-
-# make the lower-bound arc
-diam = (r - delta) * 2.0
-lower_arc = Arc( (0.0, 0.0), diam, diam, 0.0, fill=False,
edgecolor="darkgreen" )
-ax.add_patch( lower_arc )
-
-# make the target arc
-diam = r * 2.0
-target_arc = Arc( (0.0, 0.0), diam, diam, 0.0, fill=False, edgecolor="darkred"
)
-ax.add_patch( target_arc )
-
-# make the upper-bound arc
-diam = (r + delta) * 2.0
-upper_arc = Arc( (0.0, 0.0), diam, diam, 0.0, fill=False, edgecolor="darkblue"
)
-ax.add_patch( upper_arc )
-
-# make the target
-diam = delta * 2.0
-target = Arc( (x, y), diam, diam, 0.0, fill=False, edgecolor="#DD1208" )
-ax.add_patch( target )
-
-# give it a big marker
-ax.plot( [x], [y], marker='x', linestyle='None', mfc='red', mec='red',
markersize=10 )
-
-
-
-
-
-##################################################
-# now lets do the same thing again using a custom ellipse function
-
-
-
-# make the axes
-ax = subplot( 313, aspect='equal', sharex=ax1, sharey=ax1 )
-ax.set_aspect( 'equal', 'datalim' )
-
-# make the lower-bound ellipse
-custom_ellipse( ax, 0.0, 0.0, r-delta, r-delta, 0.0, color="darkgreen" )
-
-# make the target ellipse
-custom_ellipse( ax, 0.0, 0.0, r, r, 0.0, color="darkred" )
-
-# make the upper-bound ellipse
-custom_ellipse( ax, 0.0, 0.0, r+delta, r+delta, 0.0, color="darkblue" )
-
-# make the target
-custom_ellipse( ax, x, y, delta, delta, 0.0, color="#BB1208" )
-
-# give it a big marker
-ax.plot( [x], [y], marker='x', linestyle='None', mfc='red', mec='red',
markersize=10 )
-
-
-# give it a big marker
-ax.plot( [x], [y], marker='x', linestyle='None', mfc='red', mec='red',
markersize=10 )
-
-##################################################
-# lets zoom in to see the area of interest
-
-ax1.set_xlim(2650, 2735)
-ax1.set_ylim(6705, 6735)
-
-savefig("ellipse")
-show()
-
-
Deleted: trunk/matplotlib/doc/pyplots/screenshots_fill_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_fill_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_fill_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,7 +0,0 @@
-from pylab import *
-t = arange(0.0, 1.01, 0.01)
-s = sin(2*2*pi*t)
-
-fill(t, s*exp(-5*t), 'r')
-grid(True)
-show()
Deleted: trunk/matplotlib/doc/pyplots/screenshots_histogram_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_histogram_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_histogram_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,20 +0,0 @@
-from matplotlib import rcParams
-from pylab import *
-
-
-mu, sigma = 100, 15
-x = mu + sigma*randn(10000)
-
-# the histogram of the data
-n, bins, patches = hist(x, 100, normed=1)
-
-# add a 'best fit' line
-y = normpdf( bins, mu, sigma)
-l = plot(bins, y, 'r--', linewidth=2)
-xlim(40, 160)
-
-xlabel('Smarts')
-ylabel('P')
-title(r'$\rm{IQ:}\/ \mu=100,\/ \sigma=15$')
-
-show()
Deleted: trunk/matplotlib/doc/pyplots/screenshots_path_patch_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_path_patch_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_path_patch_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,36 +0,0 @@
-import numpy as np
-import matplotlib.path as mpath
-import matplotlib.patches as mpatches
-import matplotlib.pyplot as plt
-
-Path = mpath.Path
-
-fig = plt.figure()
-ax = fig.add_subplot(111)
-
-pathdata = [
- (Path.MOVETO, (1.58, -2.57)),
- (Path.CURVE4, (0.35, -1.1)),
- (Path.CURVE4, (-1.75, 2.0)),
- (Path.CURVE4, (0.375, 2.0)),
- (Path.LINETO, (0.85, 1.15)),
- (Path.CURVE4, (2.2, 3.2)),
- (Path.CURVE4, (3, 0.05)),
- (Path.CURVE4, (2.0, -0.5)),
- (Path.CLOSEPOLY, (1.58, -2.57)),
- ]
-
-codes, verts = zip(*pathdata)
-path = mpath.Path(verts, codes)
-patch = mpatches.PathPatch(path, facecolor='red', edgecolor='yellow',
alpha=0.5)
-ax.add_patch(patch)
-
-x, y = zip(*path.vertices)
-line, = ax.plot(x, y, 'go-')
-ax.grid()
-ax.set_xlim(-3,4)
-ax.set_ylim(-3,4)
-ax.set_title('spline paths')
-plt.show()
-
-
Deleted: trunk/matplotlib/doc/pyplots/screenshots_pie_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_pie_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_pie_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,26 +0,0 @@
-"""
-Make a pie chart - see
-http://matplotlib.sf.net/matplotlib.pylab.html#-pie for the docstring.
-
-This example shows a basic pie chart with labels optional features,
-like autolabeling the percentage, offsetting a slice with "explode"
-and adding a shadow.
-
-Requires matplotlib0-0.70 or later
-
-"""
-from pylab import *
-
-# make a square figure and axes
-figure(1, figsize=(6,6))
-ax = axes([0.1, 0.1, 0.8, 0.8])
-
-labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
-fracs = [15,30,45, 10]
-
-explode=(0, 0.05, 0, 0)
-pie(fracs, explode=explode, labels=labels, autopct='%1.1f%%', shadow=True)
-title('Raining Hogs and Dogs', bbox={'facecolor':'0.8', 'pad':5})
-
-show()
-
Deleted: trunk/matplotlib/doc/pyplots/screenshots_scatter_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_scatter_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_scatter_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,28 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-import matplotlib.mlab as mlab
-
-intc = mlab.csv2rec('mpl_examples/data/intc.csv')
-
-delta1 = np.diff(intc.adj_close)/intc.adj_close[:-1]
-
-# size in points ^2
-volume = (15*intc.volume[:-2]/intc.volume[0])**2
-close = 0.003*intc.close[:-2]/0.003*intc.open[:-2]
-
-fig = plt.figure()
-ax = fig.add_subplot(111)
-ax.scatter(delta1[:-1], delta1[1:], c=close, s=volume, alpha=0.75)
-
-#ticks = arange(-0.06, 0.061, 0.02)
-#xticks(ticks)
-#yticks(ticks)
-
-ax.set_xlabel(r'$\Delta_i$', fontsize=20)
-ax.set_ylabel(r'$\Delta_{i+1}$', fontsize=20)
-ax.set_title('Volume and percent change')
-ax.grid(True)
-
-plt.show()
-
-
Deleted: trunk/matplotlib/doc/pyplots/screenshots_simple_plots.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_simple_plots.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_simple_plots.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,11 +0,0 @@
-from pylab import *
-
-t = arange(0.0, 2.0, 0.01)
-s = sin(2*pi*t)
-plot(t, s, linewidth=1.0)
-
-xlabel('time (s)')
-ylabel('voltage (mV)')
-title('About as simple as it gets, folks')
-grid(True)
-show()
Deleted: trunk/matplotlib/doc/pyplots/screenshots_slider_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_slider_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_slider_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,43 +0,0 @@
-from pylab import *
-from matplotlib.widgets import Slider, Button, RadioButtons
-
-ax = subplot(111)
-subplots_adjust(left=0.25, bottom=0.25)
-t = arange(0.0, 1.0, 0.001)
-a0 = 5
-f0 = 3
-s = a0*sin(2*pi*f0*t)
-l, = plot(t,s, lw=2, color='red')
-axis([0, 1, -10, 10])
-
-axcolor = 'lightgoldenrodyellow'
-axfreq = axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
-axamp = axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)
-
-sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0)
-samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)
-
-def update(val):
- amp = samp.val
- freq = sfreq.val
- l.set_ydata(amp*sin(2*pi*freq*t))
- draw()
-sfreq.on_changed(update)
-samp.on_changed(update)
-
-resetax = axes([0.8, 0.025, 0.1, 0.04])
-button = Button(resetax, 'Reset', color=axcolor, hovercolor=0.975)
-def reset(event):
- sfreq.reset()
- samp.reset()
-button.on_clicked(reset)
-
-rax = axes([0.025, 0.5, 0.15, 0.15], axisbg=axcolor)
-radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
-def colorfunc(label):
- l.set_color(label)
- draw()
-radio.on_clicked(colorfunc)
-
-show()
-
Deleted: trunk/matplotlib/doc/pyplots/screenshots_subplot_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_subplot_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_subplot_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,25 +0,0 @@
-#!/usr/bin/env python
-from pylab import *
-
-def f(t):
- s1 = cos(2*pi*t)
- e1 = exp(-t)
- return multiply(s1,e1)
-
-t1 = arange(0.0, 5.0, 0.1)
-t2 = arange(0.0, 5.0, 0.02)
-t3 = arange(0.0, 2.0, 0.01)
-
-subplot(211)
-plot(t1, f(t1), 'bo', t2, f(t2), 'k--', markerfacecolor='green')
-grid(True)
-title('A tale of 2 subplots')
-ylabel('Damped oscillation')
-
-subplot(212)
-plot(t3, cos(2*pi*t3), 'r.')
-grid(True)
-xlabel('time (s)')
-ylabel('Undamped')
-show()
-
Deleted: trunk/matplotlib/doc/pyplots/screenshots_table_demo.py
===================================================================
--- trunk/matplotlib/doc/pyplots/screenshots_table_demo.py 2008-10-15
02:14:48 UTC (rev 6193)
+++ trunk/matplotlib/doc/pyplots/screenshots_table_demo.py 2008-10-15
02:33:38 UTC (rev 6194)
@@ -1,94 +0,0 @@
-#!/usr/bin/env python
-import matplotlib
-
-from pylab import *
-from matplotlib.colors import colorConverter
-
-
-#Some simple functions to generate colours.
-def pastel(colour, weight=2.4):
- """ Convert colour into a nice pastel shade"""
- rgb = asarray(colorConverter.to_rgb(colour))
- # scale colour
- maxc = max(rgb)
- if maxc < 1.0 and maxc > 0:
- # scale colour
- scale = 1.0 / maxc
- rgb = rgb * scale
- # now decrease saturation
- total = sum(rgb)
- slack = 0
- for x in rgb:
- slack += 1.0 - x
-
- # want to increase weight from total to weight
- # pick x s.t. slack * x == weight - total
- # x = (weight - total) / slack
- x = (weight - total) / slack
-
- rgb = [c + (x * (1.0-c)) for c in rgb]
-
- return rgb
-
-def get_colours(n):
- """ Return n pastel colours. """
- base = asarray([[1,0,0], [0,1,0], [0,0,1]])
-
- if n <= 3:
- return base[0:n]
-
- # how many new colours to we need to insert between
- # red and green and between green and blue?
- needed = (((n - 3) + 1) / 2, (n - 3) / 2)
-
- colours = []
- for start in (0, 1):
- for x in linspace(0, 1, needed[start]+2):
- colours.append((base[start] * (1.0 - x)) +
- (base[start+1] * x))
-
- return [pastel(c) for c in colours[0:n]]
-
-
-
-axes([0.2, 0.2, 0.7, 0.6]) # leave room below the axes for the table
-
-data = [[ 66386, 174296, 75131, 577908, 32015],
- [ 58230, 381139, 78045, 99308, 160454],
- [ 89135, 80552, 152558, 497981, 603535],
- [ 78415, 81858, 150656, 193263, 69638],
- [ 139361, 331509, 343164, 781380, 52269]]
-
-colLabels = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
-rowLabels = ['%d year' % x for x in (100, 50, 20, 10, 5)]
-
-# Get some pastel shades for the colours
-colours = get_colours(len(colLabels))
-colours.reverse()
-rows = len(data)
-
-ind = arange(len(colLabels)) + 0.3 # the x locations for the groups
-cellText = []
-width = 0.4 # the width of the bars
-yoff = array([0.0] * len(colLabels)) # the bottom values for stacked bar chart
-for row in xrange(rows):
- bar(ind, data[row], width, bottom=yoff, color=colours[row])
- yoff = yoff + data[row]
- cellText.append(['%1.1f' % (x/1000.0) for x in yoff])
-
-# Add a table at the bottom of the axes
-colours.reverse()
-cellText.reverse()
-the_table = table(cellText=cellText,
- rowLabels=rowLabels, rowColours=colours,
- colLabels=colLabels,
- loc='bottom')
-ylabel("Loss $1000's")
-vals = arange(0, 2500, 500)
-yticks(vals*1000, ['%d' % val for val in vals])
-xticks([])
-title('Loss by Disaster')
-#savefig('table_demo_small', dpi=75)
-#savefig('table_demo_large', dpi=300)
-
-show()
Modified: trunk/matplotlib/doc/users/intro.rst
===================================================================
--- trunk/matplotlib/doc/users/intro.rst 2008-10-15 02:14:48 UTC (rev
6193)
+++ trunk/matplotlib/doc/users/intro.rst 2008-10-15 02:33:38 UTC (rev
6194)
@@ -2,11 +2,11 @@
============
matplotlib is a library for making 2D plots of arrays in `Python
-<http://www.python.org>`_. Although it has its origins in emulating
-the `MATLAB™ <http://www.mathworks.com>`_ graphics commands, it does
-not require MATLAB, and can be used in a Pythonic, object oriented
+<http://www.python.org>`. Although it has its origins in emulating
+the `MATLAB™ <http://www.mathworks.com>` graphics commands, it is
+independent of MATLAB, and can be used in a Pythonic, object oriented
way. Although matplotlib is written primarily in pure Python, it
-makes heavy use of `NumPy <http://www.numpy.org>`_ and other extension
+makes heavy use of `NumPy <http://www.numpy.org>` and other extension
code to provide good performance even for large arrays.
matplotlib is designed with the philosophy that you should be able to
@@ -25,7 +25,8 @@
programming language, and decided to start over in Python. Python
more than makes up for all of MATLAB's deficiencies as a programming
language, but I was having difficulty finding a 2D plotting package
-(for 3D `VTK <http://www.vtk.org/>`_) more than exceeds all of my needs).
+(for 3D `VTK <http://www.vtk.org/>` more than exceeds all of my
+needs).
When I went searching for a Python plotting package, I had several
requirements:
@@ -57,26 +58,28 @@
The matplotlib code is conceptually divided into three parts: the
*pylab interface* is the set of functions provided by
:mod:`matplotlib.pylab` which allow the user to create plots with code
-quite similar to MATLAB figure generating code. The *matplotlib
-frontend* or *matplotlib API* is the set of classes that do the heavy
-lifting, creating and managing figures, text, lines, plots and so on.
-This is an abstract interface that knows nothing about output. The
-*backends* are device dependent drawing devices, aka renderers, that
-transform the frontend representation to hardcopy or a display device.
-Example backends: PS creates `PostScript®
-<http://http://www.adobe.com/products/postscript/>`_ hardcopy, SVG
-creates `Scalable Vector Graphics <http://www.w3.org/Graphics/SVG/>`_
+quite similar to MATLAB figure generating code
+(:ref:`pyplot-tutorial`). The *matplotlib frontend* or *matplotlib
+API* is the set of classes that do the heavy lifting, creating and
+managing figures, text, lines, plots and so on
+(:ref:`artist-tutorial`). This is an abstract interface that knows
+nothing about output. The *backends* are device dependent drawing
+devices, aka renderers, that transform the frontend representation to
+hardcopy or a display device (:ref:`what-is-a-backend`). Example
+backends: PS creates `PostScript®
+<http://http://www.adobe.com/products/postscript/>` hardcopy, SVG
+creates `Scalable Vector Graphics <http://www.w3.org/Graphics/SVG/>`
hardcopy, Agg creates PNG output using the high quality `Anti-Grain
-Geometry <http://www.antigrain.com>`_ library that ships with
-matplotlib, GTK embeds matplotlib in a `Gtk+ <http://www.gtk.org/>`_
+Geometry <http://www.antigrain.com>` library that ships with
+matplotlib, GTK embeds matplotlib in a `Gtk+ <http://www.gtk.org/>`
application, GTKAgg uses the Anti-Grain renderer to create a figure
and embed it a Gtk+ application, and so on for `PDF
-<http://www.adobe.com/products/acrobat/adobepdf.html>`_, `WxWidgets
-<http://www.wxpython.org/>`_, `Tkinter
-<http://docs.python.org/lib/module-Tkinter.html>`_ etc.
+<http://www.adobe.com/products/acrobat/adobepdf.html>`, `WxWidgets
+<http://www.wxpython.org/>`, `Tkinter
+<http://docs.python.org/lib/module-Tkinter.html>` etc.
matplotlib is used by many people in many different contexts. Some
-people want to automatically generate PostScript® files to send
+people want to automatically generate PostScript files to send
to a printer or publishers. Others deploy matplotlib on a web
application server to generate PNG output for inclusion in
dynamically-generated web pages. Some use matplotlib interactively
Modified: trunk/matplotlib/doc/users/screenshots.rst
===================================================================
--- trunk/matplotlib/doc/users/screenshots.rst 2008-10-15 02:14:48 UTC (rev
6193)
+++ trunk/matplotlib/doc/users/screenshots.rst 2008-10-15 02:33:38 UTC (rev
6194)
@@ -1,16 +1,13 @@
Here you will find a host of example figures with the code that
generated them
-.. _screenshots_simple_plot:
-
Simple Plot
===========
The most basic :func:`~matplotlib.pyplot.plot`, with text labels
-.. plot:: screenshots_simple_plots.py
+.. plot:: ../mpl_examples/pylab_examples/simple_plot.py
-
.. _screenshots_subplot_demo:
Subplot demo
@@ -19,9 +16,8 @@
Multiple regular axes (numrows by numcolumns) are created with the
:func:`~matplotlib.pyplot.subplot` command.
-.. plot:: screenshots_subplot_demo.py
+.. plot:: ../mpl_examples/pylab_examples/subplot_demo.py
-
.. _screenshots_histogram_demo:
Histograms
@@ -30,8 +26,9 @@
The :func:`~matplotlib.pyplot.hist` command automatically generates
histograms and will return the bin counts or probabilities
-.. plot:: screenshots_histogram_demo.py
+.. plot:: ../mpl_examples/pylab_examples/histogram_demo.py
+
.. _screenshots_path_demo:
Path demo
@@ -40,9 +37,8 @@
You can add aribitrary paths in matplotlib as of release 0.98. See
the :mod:`matplotlib.path`.
-.. plot:: screenshots_path_patch_demo.py
+.. plot:: ../mpl_examples/api/path_patch_demo.py
-
.. _screenshots_ellipse_demo:
Ellipses
@@ -57,9 +53,8 @@
provides a scale free, accurate graph of the arc regardless of zoom
level
-.. plot:: screenshots_ellipse_demo.py
+.. plot:: ../mpl_examples/pylab_examples/ellipse_demo.py
-
.. _screenshots_barchart_demo:
Bar charts
@@ -68,11 +63,11 @@
The :func:`~matplotlib.pyplot.bar`
command takes error bars as an optional argument. You can also use up
and down bars, stacked bars, candlestic' bars, etc, ... See
-`bar_stacked.py <examples/pylab_examples/bar_stacked.py>`_ for another
example.
+`bar_stacked.py <examples/pylab_examples/bar_stacked.py>`_ for another example.
You can make horizontal bar charts with the
:func:`~matplotlib.pyplot.barh` command.
-.. plot:: screenshots_barchart_demo.py
+.. plot:: ../mpl_examples/pylab_examples/barchart_demo.py
.. _screenshots_pie_demo:
@@ -87,7 +82,7 @@
Take a close look at the attached code that produced this figure; nine
lines of code.
-.. plot:: screenshots_pie_demo.py
+.. plot:: ../mpl_examples/pylab_examples/pie_demo.py
.. _screenshots_table_demo:
@@ -97,7 +92,7 @@
The :func:`~matplotlib.pyplot.table` command will place a text table
on the axes
-.. plot:: screenshots_table_demo.py
+.. plot:: ../mpl_examples/pylab_examples/table_demo.py
.. _screenshots_scatter_demo:
@@ -112,7 +107,7 @@
alpha attribute is used to make semitransparent circle markers with
the Agg backend (see :ref:`what-is-a-backend`)
-.. plot:: screenshots_scatter_demo.py
+.. plot:: ../mpl_examples/pylab_examples/scatter_demo2.py
.. _screenshots_slider_demo:
@@ -123,9 +118,9 @@
Matplotlib has basic GUI widgets that are independent of the graphical
user interface you are using, allowing you to write cross GUI figures
and widgets. See matplotlib.widgets and the widget `examples
-<examples/widgets>`_
+<examples/widgets>`
-.. plot:: screenshots_slider_demo.py
+[.. plot:: ../mpl_examples/widgets/slider_demo.py
.. _screenshots_fill_demo:
@@ -137,7 +132,7 @@
plot filled polygons. Thanks to Andrew Straw for providing this
function
-.. plot:: screenshots_fill_demo.py
+.. plot:: ../mpl_examples/pylab_examples/fill_demo.py
.. _screenshots_date_demo:
@@ -147,9 +142,9 @@
You can plot date data with major and minor ticks and custom tick
formatters for both the major and minor ticks; see matplotlib.ticker
-and matplotlib.dates for details and usage.
+and matplotlib.dates for details and usage.
-.. plot:: screenshots_date_demo.py
+.. plot:: ../mpl_examples/api/date_demo.py
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