On Wed, Oct 28, 2009 at 7:20 PM, Phillip M. Feldman
<pfeld...@verizon.net> wrote:
> If I get one y-axis with the 'host', and each invocation of twinx adds
> another y-axis, then it seems that I must invoke twinx three times to get
> four y-axes. Does twinx add more than one y-axis per invocation? (The
> documentation that I've been able to find is ambiguous about this).
twinx add a single axes.
In your original code, you were calling twinx 4-times.
See if the attached code works.
While I acknowledge that using spines with multiple y-axis is a bit
tricky, I don't think the situation will change anytime soon.
Regards,
-JJ
# multiple_yaxes_with_spines.py
# This is a template Python program for creating plots (line graphs) with 2, 3,
# or 4 y-axes. (A template program is one that you can readily modify to meet
# your needs). Almost all user-modifiable code is in Section 2. For most
# purposes, it should not be necessary to modify anything else.
# Dr. Phillip M. Feldman, 27 Oct, 2009
# Acknowledgment: This program is based on code written by Jae-Joon Lee,
# URL= http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/
# examples/pylab_examples/multiple_yaxis_with_spines.py?revision=7908&view=markup
# Section 1: Import modules, define functions, and allocate storage.
import matplotlib.pyplot as plt
from numpy import *
def make_patch_spines_invisible(ax):
ax.set_frame_on(True)
ax.patch.set_visible(False)
for sp in ax.spines.itervalues():
sp.set_visible(False)
def set_spine_direction(ax, direction):
if direction in ["right", "left"]:
ax.yaxis.set_ticks_position(direction)
ax.yaxis.set_label_position(direction)
elif direction in ["top", "bottom"]:
ax.xaxis.set_ticks_position(direction)
ax.xaxis.set_label_position(direction)
else:
raise ValueError("Unknown Direction: %s" % (direction,))
ax.spines[direction].set_visible(True)
# Create list to store dependent variable data:
y= [0, 0, 0, 0]
# Section 2: Define names of variables and the data to be plotted.
# `labels` stores the names of the independent and dependent variables). The
# first (zeroth) item in the list is the x-axis label; remaining labels are the
# first y-axis label, second y-axis label, and so on. There must be at least
# two dependent variables and not more than four.
labels= ['Indep. Variable', 'Dep. Variable #1', 'Dep. Variable #2',
'Dep. Variable #3', 'Dep. Variable #4']
# Plug in your data here, or code equations to generate the data if you wish to
# plot mathematical functions. x stores values of the independent variable;
# y[0], y[1], ... store values of the dependent variables. Each of these should
# be a NumPy array.
# If you are plotting mathematical functions, you will probably want an array of
# uniformly spaced values of x; such an array can be created using the
# `linspace` function. For example, to define x as an array of 51 values
# uniformly spaced between 0 and 2, use the following command:
# x= linspace(0., 2., 51)
# Here is an example of 6 experimentally measured values for the first dependent
# variable:
# y[0]= array( [3, 2.5, 7.3e4, 4, 8, 3] )
# Note that the above statement requires both parentheses and square brackets.
# With a bit of work, one could make this program read the data from a text file
# or Excel worksheet.
# Independent variable:
x= linspace(0., 2., 51)
# First dependent variable:
y[0]= sqrt(x)
# Second dependent variable:
y[1]= 0.2 + x**0.3 - 0.1*x**2
y[2]= 30.*sin(1.5*x)
y[3]= 30.*abs(cos(1.5*x))
# Set line colors here; each color can be specified using a single-letter color
# identifier ('b'= blue, 'r'= red, 'g'= green, 'k'= black, 'y'= yellow,
# 'm'= magenta, 'y'= yellow), an RGB tuple, or almost any standard English color
# name written without spaces, e.g., 'darkred'.
colors= ['b', 'darkred', 'g', 'magenta']
spine_directions = ["left", "right", "right", "left"]
# Set the line width here. linewidth=2 is recommended.
linewidth= 2
# Set the axis label size in points here. 16 is recommended.
axis_label_size= 16
# Section 3: Generate the plot.
N_dependents= len(labels) - 1
if N_dependents > 4: raise Exception, \
'This code currently handles a maximum of four independent variables.'
# Open a new figure window, setting the size to 10-by-7 inches and the facecolor
# to white:
fig= plt.figure(figsize=(10,7), dpi=120, facecolor=[1,1,1])
host= fig.add_subplot(111)
# Use twinx() to create extra axes for all dependent variables except the first
# (we get the first as part of the host axes).
y_axis= N_dependents * [0]
y_axis[0]= host
for i in range(1,N_dependents): y_axis[i]= host.twinx()
host.spines["right"].set_visible(False)
make_patch_spines_invisible(y_axis[1])
set_spine_direction(y_axis[1], "right")
if N_dependents >= 3:
# The following statement positions the third y-axis to the right of the
# frame, with the space between the frame and the axis controlled by the
# numerical argument to set_position; this value should be between 1.10 and
# 1.2.
y_axis[2].spines["right"].set_position(("axes", 1.15))
make_patch_spines_invisible(y_axis[2])
set_spine_direction(y_axis[2], "right")
plt.subplots_adjust(left=0.0, right=0.8)
if N_dependents >= 4:
# The following statement positions the fourth y-axis to the left of the
# frame, with the space between the frame and the axis controlled by the
# numerical argument to set_position; this value should be between 1.10 and
# 1.2.
y_axis[3].spines["left"].set_position(("axes", -0.15))
make_patch_spines_invisible(y_axis[3])
set_spine_direction(y_axis[3], "left")
plt.subplots_adjust(left=0.2, right=0.8)
p= N_dependents * [0]
# Plot the curves:
for i in range(N_dependents):
p[i], = y_axis[i].plot(x, y[i], colors[i],
linewidth=linewidth, label=labels[i])
# Set axis limits. Use ceil() to force upper y-axis limits to be round numbers.
host.set_xlim(x.min(), x.max())
# Label the x-axis:
host.set_xlabel(labels[0], size=axis_label_size)
for i in range(N_dependents):
# Label the y-axis and set text color:
y_axis[i].set_ylabel(labels[i+1], size=axis_label_size)
y_axis[i].yaxis.label.set_color(colors[i])
# If you want to override the default axis limits, uncomment the following
# line of code and adjust arguments appropriately:
# y_axis[i].set_ylim(0.0, ceil(y[i].max()))
if i== 1: y_axis[i].set_ylim(0.0, 1.5)
y_axis[i].spines[spine_directions[i]].set_color(colors[i])
for obj in y_axis[i].yaxis.get_ticklines():
# `obj` is a matplotlib.lines.Line2D instance
obj.set_color(colors[i])
obj.set_markeredgewidth(3)
for obj in y_axis[i].yaxis.get_ticklabels():
obj.set_color(colors[i])
obj.set_size(12)
obj.set_weight(600)
# To enable the legend, uncomment the following two lines:
# lines= p[1:]
# host.legend(lines, [l.get_label() for l in lines])
plt.draw(); plt.show()
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