So on Linux too, there is "ABI" suffix too, for generated module...
I misunderstood. I was renaming generated module to "fib3.pyd" to be able
to do "import fib3", but now I see it's not necessary - it's importable the
same regardless the name of generated module :)
Thanks
Hi, I'm following this guide:
http://docs.scipy.org/doc/numpy-dev/f2py/getting-started.html#the-quick-and-smart-way
I'm on Windows with gfortran and VS2015. When I run:
f2py -c -m fib3 fib3.f
as output I dont get "fib3.pyd", but "fib3.cp35-win_amd64.pyd".
Does anyone know how to get
Hi,
I have data reports in text files, where first 5 lines describe the
data following, which is actually continuous time series of 2048
values wrapped in 205 rows and 10 columns, and each file has 12 such
sets.
If I crop to first dataset and leave the headers (first 5 lines),
Thanks for providing this. Reference is excellent, especially as I was
collecting Fortran and f2py resources, some month ago, and I found nothing
similar to answers you expose.
Side by side syntax is just great and intuitive
And rest is...
Thanks
On Thu, Feb 7, 2013 at 8:22 PM, Ondřej Čertík
Thanks for your reply
I suppose, variable length signals are split on equal parts and dominant
harmonic is extracted. Then scatter plot shows this pattern, which has some
low correlation, but I can't abstract what could be concluded from grid
pattern, as I lack statistical knowledge.
Maybe it's
OK, thanks guys for your suggestions, which I'll try tomorrow
I did correlation first, but no significant values
Then I did linear regression, one sample to rest and while there I spotted
this grid pattern
I was using pandas lag_plot, but it's same plot when I do MPL scatter one
sample on others
On Mon, Jul 2, 2012 at 9:26 PM, Fernando Perez wrote:
ANNOUNCING
eGenix PyRun - One file Python Runtime
Version 1.0.0
An easy-to-use single file relocatable Python run-time -
available for Windows, Mac OS X and Unix
Damn it, N is inverted and I noticed it now after posting. Sorry about
that, here is correct one:
from numpy import arange, ones
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111,
I continued in this mpl trip, with small animation sequence:
# animation
ax.view_init(90,-90)
plt.ion()
plt.draw()
plt.show()
for l in arange(25):
ax.set_xlim3d(1.5-.1*l,2.5+.1*l)
ax.set_ylim3d(1.5-.1*l,2.5+.1*l)
ax.view_init(90-3*l, -90+l)
Yeah, camera is in cliche, I know :D
Something more original can be done, perhaps some idea of transforming
grid in 2D (in Z plane) for opening sequence and then emerging latices
in some analogy with numpy arrays, finishing with complete figure, but
I guess not in matplotlib ;)
08:04, klo uo wrote:
from numpy import arange, ones
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
o = ones(4)
r = arange(4)
# planes:
for z in arange(3)+1:
ax.bar(r, o*4, zs=z, zdir='x', alpha=.05
Heh, thanks :)
It's free interpretation made from quick idea then immediately shared.
Original logo can be made exact I guess with interlaced planes and
shallower bars or similar...
On Tue, Jun 26, 2012 at 8:19 AM, Anthony Scopatz wrote:
This is awesome!
This news did not arrive at scikit-learn-gene...@lists.sourceforge.net
Is above list deprecated?
BTW thanks for supporting and working on this project ;)
On Tue, May 8, 2012 at 1:13 AM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On behalf of Andy Mueller, our release manager, I am
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