Hello all and sorry for my bad english,
i am a beginner with python and i try to save a lot of data in several folders
in a 4D matrix
and then to plot two columns of this 4D matrix.
Bellow, i have the code to fill my 4D matrix, it works very well :
[CODE]matrix4D=[]
for i in Numbers:
You problem isn't with colon indexing, but with the interpretation of the
arguments to plot. multiple calls to plot with scalar arguments do not have
the same result as a single call with array arguments. For this to work as
intended, you would need plt.hold(True), for starters, and maybe there
By default, the hold is already True. In fact, that might explain some of
the differences in what you are seeing. There are more points in the second
image than in the first one, so I wonder if you are seeing some leftovers
of previous plot commands?
One issue I do see is that the slicing is
On Do, 2014-05-01 at 09:45 -0400, Benjamin Root wrote:
By default, the hold is already True. In fact, that might explain some
of the differences in what you are seeing. There are more points in
the second image than in the first one, so I wonder if you are seeing
some leftovers of previous
Thanks all for your help!
i will try
bye ;-)
- Original Message -
From: Sebastian Berg
Sent: 05/01/14 03:54 PM
To: numpy-discussion@scipy.org
Subject: Re: [Numpy-discussion] arrays and : behaviour
On Do, 2014-05-01 at 09:45 -0400, Benjamin Root wrote: By default, the hold
is already
thanks, it works well
see you and thanks again
- Original Message -
From: Sebastian Berg
Sent: 05/01/14 03:54 PM
To: numpy-discussion@scipy.org
Subject: Re: [Numpy-discussion] arrays and : behaviour
On Do, 2014-05-01 at 09:45 -0400, Benjamin Root wrote: By default, the hold
is
Hi all,
I am trying to calculate the 2nd-order gradient numerically of an
array in numpy.
import numpy as np
a = np.sin(np.arange(0, 10, .01))
da = np.gradient(a)
dda = np.gradient(da)
This is what I come up. Is the the way it should be done?
I am asking this, because in numpy
Am 01.05.14 18:45, schrieb Yuxiang Wang:
Hi all,
I am trying to calculate the 2nd-order gradient numerically of an
array in numpy.
import numpy as np
a = np.sin(np.arange(0, 10, .01))
da = np.gradient(a)
dda = np.gradient(da)
It looks like you are looking for the
On Thu, May 1, 2014 at 3:42 PM, Christian K. ckk...@hoc.net wrote:
It looks like you are looking for the derivative rather than the
gradient. Have a look at:
np.diff(a, n=1, axis=-1)
n is the order if the derivative.
depending on your use case, you may want to use a polynomial fit for a
