matplotlib-users Mailing List for matplotlib

Even better:

f, axarr = plt.subplots(allplots, 1, figsize = fig_size)

Its always difficult to predict which **kwargs could/would be valid...

On 25/06/12 18:30, Benjamin Root wrote:
>
>
>
> Your call to "plt.subplots" is creating a new figure object, which
> never gets the figsize parameter (only the old figure object has that
> set).
>
> Cheers!
> Ben Root
>

Hi,
indeed you are right. I added "f.set_size_inches(fig_size)" and it works
Also I had a wrong conversion of inch to cm (2.58 before).

Thank you for your help,
Mogliii



The final code:
#################

import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import numpy as np

x = np.arange(10)
y = np.arange(10)

fig_width_cm = 21                         # A4 page
fig_height_cm = 29.7
inches_per_cm = 1 / 2.54              # Convert cm to inches
fig_width = fig_width_cm * inches_per_cm # width in inches
fig_height = fig_height_cm * inches_per_cm       # height in inches
fig_size = [fig_width, fig_height]


pdf = PdfPages('outfile.pdf')
allplots = 3  # This is the variable number of subplots
f, axarr = plt.subplots(allplots, 1)
f.set_size_inches(fig_size)


for plot in range(allplots):
    axarr[plot].plot(x + plot, y)

pdf.savefig()
pdf.close()

On Mon, Jun 25, 2012 at 1:12 PM, mogliii <mo...@gm...> wrote:

> Hi,
>
> In my script a variable number of graphs is generated. I want to place
> them in one column with arbitrary number of rows onto an A4 canvas (for
> pdf export).
>
> Unfortunately the figsize directive seems to have no effect. The figure
> is always 8x6 inch.
>
> Which code do I have to use in this case?
>
>
> My minimal code:
> #######################################
>
> import matplotlib.pyplot as plt
> from matplotlib.backends.backend_pdf import PdfPages
> import numpy as np
>
> x = np.arange(10)
> y = np.arange(10)
>
> fig_width_cm = 21                         # A4 page
> fig_height_cm = 29.7
> inches_per_cm = 1 / 2.58               # Convert cm to inches
> fig_width = fig_width_cm * inches_per_cm # width in inches
> fig_height = fig_height_cm * inches_per_cm       # height in inches
> fig_size = [fig_width, fig_height]
>
>
> pdf = PdfPages('outfile.pdf')
> fig = plt.figure(figsize = fig_size)
> allplots = 3  # This is the variable number of subplots
> f, axarr = plt.subplots(allplots, 1)
>
>
> for plot in range(allplots):
>    axarr[plot].plot(x+plot, y)
>
> pdf.savefig()
> pdf.close()
>
>
Your call to "plt.subplots" is creating a new figure object, which never
gets the figsize parameter (only the old figure object has that set).

Cheers!
Ben Root

Hi,

In my script a variable number of graphs is generated. I want to place
them in one column with arbitrary number of rows onto an A4 canvas (for
pdf export).

Unfortunately the figsize directive seems to have no effect. The figure
is always 8x6 inch.

Which code do I have to use in this case?


My minimal code:
#######################################

import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import numpy as np

x = np.arange(10)
y = np.arange(10)

fig_width_cm = 21                         # A4 page
fig_height_cm = 29.7
inches_per_cm = 1 / 2.58               # Convert cm to inches
fig_width = fig_width_cm * inches_per_cm # width in inches
fig_height = fig_height_cm * inches_per_cm       # height in inches
fig_size = [fig_width, fig_height]


pdf = PdfPages('outfile.pdf')
fig = plt.figure(figsize = fig_size)
allplots = 3  # This is the variable number of subplots
f, axarr = plt.subplots(allplots, 1)


for plot in range(allplots):
    axarr[plot].plot(x+plot, y)

pdf.savefig()
pdf.close()

Hello,

I made a crude sonogram https://gist.github.com/2983547 with the note
names instead of the frequency. But, It really angers me not to be
able to have a log scale for the frequency.

Does any well known workaround exists?
Is there an easy way to grosso modo do :
x = time, y = frequency, z=amplitude of spectre with something like a
specter of one croche at time = t according to the bpm and make an y
scale logarithmic, then project the amplitude (z) with a colormap on
x,y plane according to the amplitude, and and have 3D representation?

Basically, I guess it boils down to know if combining those 2 is
possible : http://matplotlib.sourceforge.net/examples/mplot3d/contourf3d_demo2.html
+ log scale for y. I guess I could improve the result by using
logscale on Z and colormap
(http://stackoverflow.com/questions/5748076/python-matplotlib-contour-plot-logarithmic-color-scale)


Since it is only for fun, and I don't want to invest myself too much
my question is really did I missed something while googling for an
easy solution and if so, what are the good keywords?

Cheers
-- 
Julien

Christoph Groth writes:

> show_figures([Figure().add_subplot(1,1,1).plot(range(10)),
>               Figure().add_subplot(1,1,1).plot([x*x for x in range(10)])])

This wouldn't work of course, it should be rather

f1 = Figure()
f1.add_subplot(1, 1, 1).plot(range(10))
f2 = Figure()
f2.add_subplot(1, 1, 1).plot([x*x for x in range(10)])
show_figures([f1, f2])

Dear matplotlib developers,

I prefer to use matplotlib in my scripts without its state-machine
wrapper and it works mostly nicely.  One thing which is missing
currently is a standard way to display a bunch of figures using the
default backend.  What I have to do now is:

from matplotlib.pyplot import figure, show
f = figure()
ax = f.add_subplot(1, 1, 1)
ax.plot(range(10))
f = figure()
ax = f.add_subplot(1, 1, 1)
ax.plot([x*x for x in range(10)])
show()

What I don't like about this approach is that figure() not only creates
a figure instance, but also a hidden reference to it somewhere in the
state machine and show uses these hidden references.  I find this
inelegant.

What about adding a function "show_figures" to matplotlib (not to
matplotlib.pyplot but somewhere else) which would show all the figures
in a sequence using the default backend?  Then the following would be
possible:

f1 = Figure()
ax = f1.add_subplot(1, 1, 1)
ax.plot(range(10))
f2 = Figure()
ax = f2.add_subplot(1, 1, 1)
ax.plot([x*x for x in range(10)])
show_figures([f1, f2])

or even:

show_figures([Figure().add_subplot(1,1,1).plot(range(10)),
              Figure().add_subplot(1,1,1).plot([x*x for x in range(10)])])