And nothing is printed, so no empty strings. Then I tried
scipy.recfromcsv, and it worked perfectly! OpenOffice also has no
problem with it.
Therefore, it seems that the file is ok, but the csv2rec version from
matplotlib find some inconsistency. Any help? Could it be a bug? (as
the scipy versi
Hi All,
I have a pcolor plot with 101 rows, and I was using this:
...
ODEPTH = np.linspace(0, 10, 101)
...
odepthl = [str(x) for x in ODEPTH]
ax.yaxis.set_ticks(np.arange(ODEPTH.size)+0.5)
ax.yaxis.set_ticklabels(odepthl)
...
To set the ticks centered on each row. Now I'm interested on having
th
I'm plotting several images at once, sharing axes, because I use it
for exploratory purposes. Each image is the same satellite image at
different dates. I'm experimenting a slow response from matplotlib
when zooming and panning, and I would like to ask for any tips that
could speed up the process.
On Wed, May 23, 2012 at 11:00 AM, Guillaume Gay
wrote:
> Hello
>
>
> What is the size of a single image file? If they are very big, it is
> better to do everything from processing to ploting at once for each file.
As stated below, each image is single-channel, of 4600x3840 pixels. As
you can see
On Wed, May 23, 2012 at 6:27 PM, Tony Yu wrote:
>
> I'm not sure what you mean by "normalize the values to an appropriate number
> of bits", but I don't think setting `vmin` or `vmax` will change the data
> type of the image. So if you have 64-bit floating point images (100+ Mb per
> image), then
> It seems that setting `interpolation='none'` is significantly slower than
> setting it to 'nearest' (or even 'bilinear'). On supported backends (e.g.
> any Agg backend) the code paths for 'none' and 'nearest' are different:
> 'nearest' gets passed to Agg's interpolation routine, whereas 'none' do
Dear all,
I have a CSV file with the first column with timestamps:
0:00:00 01/01/2007, 0.000, 10, 0.000, 10,
0.000, 10:
00:00:00 02/01/2007, 0.000, 10, 0.000, 10,
0.000, 10
00:00:00 03/01/2007, 0.000, 10, 0.000, 10,
0.000, 10
On Fri, Jun 29, 2012 at 12:02 PM, Andreas Hilboll wrote:
>
> You could use numpy.genfromtxt together with its `converters` parameter:
>
> converters : variable, optional
> The set of functions that convert the data of a column to a value.
> The converters can also be used to pr
