[EMAIL PROTECTED] writes:
a) 2.3 doesn't have the sorted function - it uses a .sort()
function. So, I had to change line 487 from:
I think this was taken care of by Nicolas Grilly's recent patch.
b) No update() function (line 396)
for (name, value) in self.markers.items():
Out of the box matplotlib works great with Numeric and numarray data types.
However, I have my own custom class which contains data members, methods and
an array of data (underlying C array). Is there a way to expose the C array
data to the plot() routines? For example I would like to be able to
Anand Patil [EMAIL PROTECTED] writes:
- How can I make my figures and axes transparent by default?
Here's one idea:
In [1]:fig=figure(frameon=False)
In [2]:ax = fig.add_subplot(111, frameon=False)
In
On Fri, Mar 02, 2007 at 09:41:03AM -0500, Simon Wood wrote:
Out of the box matplotlib works great with Numeric and numarray data types.
However, I have my own custom class which contains data members, methods and
an array of data (underlying C array). Is there a way to expose the C array
data
On Fri, Mar 02, 2007 at 08:44:02AM -0600, Glen W. Mabey wrote:
One approach that I've used recently is to simply provide functionality
for the [] operator (done by implementing the __getslice__ member
function) that accesses the data according to standard slicing rules.
Then, you can use
Jouni K. Seppänen [EMAIL PROTECTED] writes:
Anand Patil [EMAIL PROTECTED] writes:
- When I inserted some of my old pdf plots into a latex presentation, to
my surprise their foreground color had changed from black to the color
of the text in the presentation. Is there a way to signal to
On 3/2/07, Simon Wood [EMAIL PROTECTED] wrote:
python Out of the box matplotlib works great with Numeric and
numarray data types.
However, I have my own custom class which contains data members, methods and
an array of data (underlying C array). Is there a way to expose the C array
data to
[EMAIL PROTECTED] writes:
Somebody at the usenet suggested that I play with the ticker
formatter and locator. While that helped the multi-color sample I
cited, it didn't help in my plots. The formatter only controls how
the y-axis labels are formatted, whereas AFAIK the locator only
affects
On 3/2/07, [EMAIL PROTECTED]
[EMAIL PROTECTED] wrote:
Somebody at the usenet suggested that I play with the ticker formatter and
locator. While that helped the multi-color sample I cited, it didn't help
in my plots. The formatter only controls how the y-axis labels are
formatted,
John Hunter wrote:
But numpy.asarray, which is what mpl uses to convert inputs to
arrays,
The whole idea of asarray, is that it should be able to convert properly
defined objects without even copying the data.
my own custom class which contains data members, methods and an array
of data
Thanks to the reply, John (Hunter).
That's it. The method proposed by Jouni appears to work too:
gca().yaxis.set_major_locator(LinearLocator())
but it created too many labels.
The set_ytinks call is the key. The set_ylim doesn't seem to be necessary.
Now I have to study and see how I can
On Friday 02 March 2007 14:12:24 John Hunter wrote:
I still am not able to make my mock-up custom python class work as I
would like with asarray (though it works with list). What am I
missing? The way I read it this appears to be in support of extension
code that wants to expose the array
On 3/2/07, Alan Isaac [EMAIL PROTECTED] wrote:
John asked:
What is the minimum interface for an object to be
converted to a numpy sequence via as array?
The class must inherit from object.
That will probably do it.
If all else fails, try fromiter.
I know it works with fromiter, but I
On Thu, 1 Mar 2007, Eric Firing wrote:
I agree, and this is a problem with spy also. If I remember, I will fix it.
It is only a minor annoyance, so it is low priority, though.
There is a difference in the way the axes are labeled between spy and
matshow, and I would like to change
On 3/2/07, John Hunter [EMAIL PROTECTED] wrote:
John said:
...here is the minimal interface that
appears to work
class C(object):
def __init__(self):
self._data = (1,2,3,4,5)
def __getitem__(self, i):
return self._data[i]
def __len__(self):
return
John Hunter wrote:
On 2/27/07, Christopher Barker [EMAIL PROTECTED] wrote:
There is nothing inherent in OO
design that makes it necessary to write a bunch more code.
I don't agree with this at all. Inherent in OO design is object
creation, attribute setting and method calling. pylab
Christopher Barker wrote:
[...]
It is nice to have a really simple plot command. What would it do if we
were trying to be fully OO? My key question is whether it would return
and axis, a figure or both:
Fig, ax = plot([1,2,3])
then:
ax.xlabel(whatever)
isn't bad for me.
Sometimes
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