whilst trying to write an array to disk I am coming across the following.
What am I doing wrong? Surely f is a file handle?
(python 3.4.3, numpy 1.9.2)
import numpy as np
a = np.arange(10.)
with open('test.dat', 'w') as f:
TypeError Traceback (most recent call
last)<ipython-input-57-cf77f423517e> in <module>() 2 a =
np.arange(10.) 3 with open('test.dat', 'w') as f:----> 4
in savetxt(fname, X, fmt, delimiter, newline, header, footer,
comments) 1085 else: 1086 for row in X:-> 1087
fh.write(asbytes(format % tuple(row) + newline))
1088 if len(footer) > 0: 1089 footer =
footer.replace('\n', '\n' + comments)
TypeError: must be str, not bytes
Dr. Andrew Nelson
We have released a small experimental package called numtraits that
builds on top of the traitlets package and provides a NumericalTrait
class that can be used to validate properties such as:
* number of dimension (for arrays)
* shape (for arrays)
* domain (e.g. positive, negative, range of values)
* units (with support for astropy.units, pint, and quantities)
The idea is to be able to write a class like:
radius = NumericalTrait(domain='strictly-positive', ndim=0)
position = NumericalTrait(shape=(3,))
and all the validation will then be done automatically when the user
sets 'radius' or 'position'.
In addition, tuples and lists can get automatically converted to
arrays, and default values can be specified. You can read more about
the package and see examples of it in use here:
and it can be easily installed with
pip install numtraits
The package supports both Python 3.3+ and Legacy Python (2.7) :)
At this point, we would be very interested in feedback - the package
is still very young and we can still change the API if needed. Please
open issues with suggestions!
Tom and Francesco
After long conversations at BIDS this weekend and after reading the entire
governance document, I realized that the steering council is very large
and I don't agree with the mechanism by which it is chosen.
A one year time frame is pretty short on the context of a two decades old
project and I believe the current council has too few people who have been
around the community long enough to help unstuck difficult situations if
that were necessary.
I would recommend three possible adjustments to the steering council
1 - define a BDFL for the council. I would nominate chuck Harris
2 - limit the council to 3 people. I would nominate chuck, nathaniel, and
3 - add me as a permanent member of the steering council.
Writing NumPy was a significant amount of work. I have been working
indirectly or directly in support of NumPy continously since I wrote it.
While I don't actively participate all the time, I still have a lot of
knowledge, context, and experience in how NumPy is used, why it is the way
it is, and how things could be better. I also work with people directly
who have and will contribute regularly.
I am formally requesting that the steering council concept be adjusted in
one of these three ways.
---------- Forwarded message ----------
From: Thomas Caswell <tcaswell(a)gmail.com>
Date: Wed, Sep 23, 2015 at 8:51 PM
Subject: [Matplotlib-devel] Fwd: [NumFOCUS Projects] grant opportunity
To: matplotlib development list <matplotlib-devel(a)python.org>
If anyone has some downtime and would like to be paid to hack on open source.
Submissions are due Sept 30
---------- Forwarded message ---------
From: Gina Helfrich <gina(a)numfocus.org>
Date: Fri, Sep 18, 2015 at 12:10 PM
Subject: [NumFOCUS Projects] grant opportunity
Wanted to bring this opportunity to your attention:
Stripe is looking to host three to four developers at their San
Francisco office for three months to work full-time on an open-source
project. The grant is no-strings-attached: $7,500 per month in
addition to desk space at our office and meals during the week. "We
want to provide everything needed to focus and have a substantial
impact on an open-source project."
More info: https://stripe.com/blog/open-source-retreat-2016
The program will run from January 15th until April 15th, 2016 at
Stripe HQ in the Mission District of San Francisco.
Gina Helfrich, Ph.D.
NumFOCUS | Open Code, Better Science
gina(a)numfocus.org | 512-222-5449
You received this message because you are subscribed to the Google
Groups "Fiscally Sponsored Project Representatives" group.
To unsubscribe from this group and stop receiving emails from it, send
an email to projects+unsubscribe(a)numfocus.org.
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Visit this group at http://groups.google.com/a/numfocus.org/group/projects/.
To view this discussion on the web visit
Matplotlib-devel mailing list
Nathaniel J. Smith -- http://vorpus.org
The Tentative NumPy Tutorial is no longer accessible by the URL
http://wiki.scipy.org/Tentative_NumPy_Tutorial, it returns a 403. The
link to this page is still on NumPy homepage though. Has the page been
moved somewhere else?
Apologies for the cross-posting.
The Data Science Student Society of the University of California San Diego,
or DS3 @ UCSD as they like to call themselves, will be holding biweekly
Python themed workshops starting this fall. On the week of October 19th,
they will be having yours truly doing a "Become an Open Source Contributor"
piece. It will be a shortish event, 60-90 minutes, so my idea was to cover
1. (15 min) An introduction to the Python data science landscape.
2. (30 min) An overview of the GitHub workflow that most (all?) of the
3. (30-45 min) A hands on session, where we would make sure everyone
gets set up in GitHub, and forks and clones their favorite project. Time
and participant willingness permitting, I would like to take advantage of
my commit bits, and have some of the participants submit a simple PR, e.g.
fixing a documentation typo, to NumPy or SciPy, and hit the green button
right there, so that they get to leave as knighted FOSS contributors.
And this is what I am hoping to get from you, the community:
1. If anyone in the area would like to get involved, please contact me.
I have recruited a couple of volunteers from PySanDiego, but could use more
2. I'm also hoping to get some help, especially with the introductory
part. Given that the crowd will mostly be university students and some
faculty, it would be great if someone who actually knew what they were
talking about could deliver a short, 10 minute talk, on Python, data
science, and academia. I'm sure we could arrange it to have someone join
by video conference.
3. If you have organized anything similar in the past, and have material
that I could use to, ahem, draw inspiration from, or recommendations to
make, or whatever, I'd love to hear from you.
Thanks for reading!
( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes
de dominación mundial.
Trying to figure out at least a bit from the discussions. While I am happy with the draft, I wonder if someone has some insights about some questions:
1. How large crowds have examples of working well with apache style voting?
2. How large do we expect numpy steering council to be (I have always thought about 10).
3. More on opinions, how large does the community feel is too large (so that we should maybe elect people).
And to maybe more a discussion point, does the community feel that those who would be/are affectivly now in the Steering Council do not sufficiently represent old time contributers who were not active in the past year(s).
I cannot form/change my opinion based on the previous discussion, because I would like to get an idea of how everyone feels about these points first. Then we can fight about details :)
(sending from phone, so sorry about eventual weird typos)
I am pleased to announce release 2015.3 of SfePy.
SfePy (simple finite elements in Python) is a software for solving systems of
coupled partial differential equations by the finite element method or by the
isogeometric analysis (preliminary support). It is distributed under the new
Home page: http://sfepy.org
Mailing list: http://groups.google.com/group/sfepy-devel
Git (source) repository, issue tracker, wiki: http://github.com/sfepy
Highlights of this release
- preliminary support for parallel computing
- unified evaluation of basis functions (= isogeometric analysis fields can be
evaluated in arbitrary points)
- (mostly) fixed finding of reference element coordinates of physical points
- several new or improved examples
For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1
(rather long and technical).
Robert Cimrman on behalf of the SfePy development team
Contributors to this release in alphabetical order: