mukulikaa / numpy Goto Github PK

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The fundamental package for scientific computing with Python.

License: Other

Python 61.97% C 35.23% C++ 1.24% Fortran 0.14% Makefile 0.01% Shell 0.16% sed 0.03% Smarty 0.02% D 0.01% Dockerfile 0.03% Cython 0.85% Starlark 0.01% Meson 0.27% Forth 0.02%

numpy's Introduction

Hi there 👋

I am a Computer Engineering undergraduate from Mumbai, India.

🔭 I’m currently a Project Intern at Indian Institute of Tropical Meteorology, Pune.
🌱 I’m currently learning about applications of data science in climate science.
👯 I’m looking to collaborate on environmental and sustainablity research.
📫 How to reach me: twitter.com/mtdewgorl
😄 Pronouns: she/her
⚡ Fun fact: I love reading all kinds of fiction!

numpy's People

Contributors

numpy's Issues

ENH: This is a test feature request issue

Proposed new feature or change:

Please add this functionality because it is used here:
code example

DOC: Moving reference material from `structured array` doc in NumPy fundamentals to API reference

The Structured arrays page in NumPy fundamentals is very useful and easy to understand. Only the Recarray Helper Functions subsection seems to be reference material so I think we can move it to API reference. I am not sure exactly where we can place this material though. Maybe we can add it under numpy.rec ? Also, I have checked that it is not duplicate material and does not already exist in the reference.

cc: @melissawm @rossbar

DOC: `Writing custom array containers` in NumPy fundamentals can be categorized as a tutorial

The Writing custom array containers document seems to be a good tutorial instead of an explanation because it

has a learning objective,
gives results immediately,
begins at the beginning; there are no steps to be executed before the first one,
ends with a definite outcome; the user implements their own array container,
and is reproducible.

Also, phrases like "Notice that the return type is...", "We will do x", etc. are used.

I think we can rewrite some parts and make the doc conform to NumPy's tutorial format. Granted it does not have a storyline like the recent tutorials, we can still add it to them I guess?

Note: There is a slight error in the __init__ method of the example; it should be self.i = value instead of self._i = value. Right now if we try to reproduce the example it gives an AttributeError: 'DiagonalArray' object has no attribute 'i'. If it is a priority I will fix that before updating the rest of the doc.

Let me know your thoughts @melissawm and @rossbar!

DOC: Merging the two indexing documents

Continuing the discussion from numpy#14038:

I would remove the "Single element indexing", "Other indexing options", "Index arrays", "Indexing Multi-dimensional arrays", "Boolean or “mask” index arrays", and "Combining index arrays with slices", but make sure the content exists on the reference page.

The information you remove from the user page about mixing indexing types should be merged in under Advanced Indexing".

I agree with Matti here; most of the concepts in the basics doc are already covered in the reference one. Apart from Combining index arrays with slices, the other unique sections seem to be Assigning values to indexed arrays and Dealing with variable numbers of indices within programs. We can let them remain in the basics documentation or include them in a new how-to for all types of indexing.

I feel that having a how-to instead of an explanation for ndarray indexing would make sense because users are more likely to want to know exactly how should they use indexing for their particular use-case. But again, I am not an experienced user so there might be a need for explanations too.

If we want to keep the basics document, I would suggest renaming one of the docs. The basics doc could be renamed to Indexing basics, for example.

Let me know what you think @melissawm and @rossbar!

DOC: This is a test documentation issue

Issue with current documentation:

I think something should be replaced with something else.

Idea or request for content:

No response

This is a test install issue

Steps to reproduce:

libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007fc555e7a000)
libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007fc555b79000)
libgfortran.so.3 => /usr/lib/x86_64-linux-gnu/libgfortran.so.3 (0x00007fc55585b000)
/lib64/ld-linux-x86-64.so.2 (0x00007fc5584ed000)
libquadmath.so.0 => /usr/lib/x86_64-linux-gnu/libquadmath.so.0 (0x00007fc55561e000)
libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007fc555408000)

Error message:

Traceback (most recent call last):
  File "/home/zanella/Test_Cases/vertical_flap/structural/run.py", line 26, in <module>
    from mbc_py_interface import mbcNodal
  File "/home/zanella/softwares/mbdyn-develop/libexec/mbpy/mbc_py_interface.py", line 33, in <module>
    from numpy import *
  File "/home/zanella/softwares/Python-3.9.0/lib/python3.9/site-packages/numpy-1.20.3-py3.9-linux-x86_64.egg/numpy/__init__.py", line 145, in <module>
    from . import core
  File "/home/zanella/softwares/Python-3.9.0/lib/python3.9/site-packages/numpy-1.20.3-py3.9-linux-x86_64.egg/numpy/core/__init__.py", line 48, in <module>
    raise ImportError(msg)
ImportError: 

IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!

BUG: Build fails on `xyz` with `abc`

Describe the issue:

Build fails on xyz with abc

Reproduce the code example:

export CC=/path/to/gcc7
python setup.py build

Error message:

Defaulting to user installation because normal site-packages is not writeable
Processing /autofs/nccs-svm1_home1/[...]/numpy
  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.
   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
    Preparing wheel metadata ... done
Building wheels for collected packages: numpy
  Building wheel for numpy (PEP 517) ... error
  ERROR: Command errored out with exit status 1:
   command: /sw/summit/python/3.7/anaconda3/5.3.0/bin/python /sw/summit/python/3.7/anaconda3/5.3.0/lib/python3.7/site-packages/pip/_vendor/pep517/in_process/_in_process.py build_wheel /tmp/tmp_k8vx39q
       cwd: /tmp/pip-req-build-vyase0q6
  Complete output (860 lines):
  gcc: build/src.linux-ppc64le-3.7/numpy/core/src/umath/loops_trigonometric.dispatch.c
  gcc: build/src.linux-ppc64le-3.7/numpy/core/src/umath/loops_exponent_log.dispatch.c
  gcc: build/src.linux-ppc64le-3.7/numpy/core/src/umath/loops_arithmetic.dispatch.c
  In file included from numpy/core/src/common/simd/vsx/vsx.h:73:0,
                   from numpy/core/src/common/simd/simd.h:40,
                   from numpy/core/src/umath/loops_arithm_fp.dispatch.c.src:9:
  numpy/core/src/common/simd/vsx/operators.h: In function 'npyv_and_b64':
  numpy/core/src/common/simd/vsx/operators.h:71:1: error: invalid parameter combination for AltiVec intrinsic __builtin_vec_and
   NPYV_IMPL_VSX_BIN_B64(and)
   ^~~~~~~~~~~~~~~~~~~~~
  In file included from numpy/core/src/common/simd/vsx/vsx.h:73:0,
                   from numpy/core/src/common/simd/simd.h:40,
                   from numpy/core/src/umath/loops_arithmetic.dispatch.c.src:11:
  numpy/core/src/common/simd/vsx/operators.h: In function 'npyv_and_b64':
  numpy/core/src/common/simd/vsx/operators.h:71:1: error: invalid parameter combination for AltiVec intrinsic __builtin_vec_and
   NPYV_IMPL_VSX_BIN_B64(and)
   ^~~~~~~~~~~~~~~~~~~~~
  In file included from numpy/core/src/common/simd/vsx/vsx.h:73:0,
ppc64le-3.7/numpy/core/src/umath/loops_trigonometric.dispatch.o.d -O3 -mcpu=power8" failed with exit status 1
  ----------------------------------------
  ERROR: Failed building wheel for numpy
Failed to build numpy
ERROR: Could not build wheels for numpy which use PEP 517 and cannot be installed directly

NumPy/Python version information:

NumPy: 1.22.0.dev0+944.gc6ac4dab5
Python: 3.9.5

mukulikaa / numpy Goto Github PK

numpy's Introduction

Hi there 👋

I am a Computer Engineering undergraduate from Mumbai, India.

numpy's People

Contributors

numpy's Issues

Proposed new feature or change:

Issue with current documentation:

Idea or request for content:

Steps to reproduce:

Error message:

Describe the issue:

Reproduce the code example:

Error message:

NumPy/Python version information:

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