nschloe/awesome-scientific-computing 520
:sunglasses: Curated list of awesome software for numerical analysis and scientific computing
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nschloe/colorio 118
Tools for color models
nschloe/dmsh 118
Simple mesh generator inspired by distmesh.
Accurate sums and dot products for Python.
Cleans up your LaTeX files.
Visualization for SciPy sparse matrices.
Clean matplotlib line plots
Collected experimental color data.
Color maps for complex-valued functions
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PR opened nschloe/meshio
I've added a new test with a valid Nastran grid in long format that currently fails. The issue is that chunks2[1:3]] in the code below will only be length 1 since the second line in the test grid card is not long enough (not more than 16 characters long). This leads leads to ValueError: not enough values to unpack (expected 2, got 1).
chunks2 = _chunk_line(next_line)
next_line = f.readline()
points.append(
[
_nastran_string_to_float(i + j)
for i, j in [chunks[5:7], chunks[7:9], chunks2[1:3]]
]
)
The solution I've added here is to simply use 72 for the line length instead of len(line), which will result in the fixed format line "chunks" always having 9 fields. It fills the empty ones with empty strings, ''.
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startednschloe/optimesh
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PR opened nschloe/tikzplotlib
I've starting debugging #453 and found the place where the bug happens, but I don't know how to fix it.
https://github.com/nschloe/tikzplotlib/blob/dc919b3c538544ecf4b3d86deaf2cb9b80f0af80/tikzplotlib/_util.py#L9
def get_legend_text(obj):
"""Check if line is in legend."""
leg = obj.axes.get_legend()
if leg is None:
return None
# leg.legendHandles = [<matplotlib.collections.LineCollection object at 0x7fc13a90d278>, <matplotlib.collections.LineCollection object at 0x7fc13a90d780>]
keys = [h.get_label() for h in leg.legendHandles if h is not None] # = ['_nolegend_', '_nolegend_']
values = [t.get_text() for t in leg.texts] # = ['y1', 'y2']
# obj = <matplotlib.lines.Line2D object at 0x7fc13c957dd8>
label = obj.get_label() # = '_nolegend_'
d = dict(zip(keys, values)) # = {'_nolegend_': 'y2'}
if label in d:
return d[label] # Both return the same label
return None
Could you give guidance hints on how to proceed? I think I need to either get from the Line2D object to the LineCollection or vice versa to check if the Line2D is included in the one of the LineCollections.
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fork mb/tikzplotlib
Convert matplotlib figures to TikZ/PGFplots for smooth integration into LaTeX.
https://pypi.org/project/tikzplotlib
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pull request commentnschloe/awesome-scientific-computing
Thanks for the feedback!
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pull request commentnschloe/awesome-scientific-computing
I just checked out Kratos. What's awesome:
* It's open source. * It's on GitHub. * It's got a Python interface.What's not awesome:
Installation:
* No native packages (Debian, Red Hat,...)
We are working in the pypy packages...
* 1.73 GiB git check out (???)
Many developments, we need to perform some clean up.
* Had to abort compilation after 10+ mins at only 17% progress.
Yes, but many large projects take long to compile.
Use:
* There's a Python interface, but it mostly looks like C++ code, e.g., ```python gid_output.ExecuteInitializeSolutionStep() ## The actual solution goes here if gid_output.IsOutputStep(): # Call ExecuteBeforeOutputStep on any auxiliar processes you have here gid_output.PrintOutput() # Call AfterBeforeOutputStep on any auxiliar processes you have here gid_output.ExecuteFinalizeSolutionStep() gid_output.ExcecuteFinalize() ``` (From [here](https://github.com/KratosMultiphysics/Kratos/wiki/Python-Script-Tutorial:-Writing-Output-File)).
That's because we focus to make one consistent interface between C++ and python, like Qt does (being less pythonic)
More:
* 100+ contributors, but <600 gh stars?
Mostly researchers, not very well known yet
* bundling of third-party libraries (admittedly other packages do that, too, but it's not awesome)
Do you prefer something like PETSc, where third party are automatically downloaded?
I'm inclined not to merge it.
Completely fair, I just want it to add my two cents.
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startednschloe/meshplex
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PR opened nschloe/awesome-scientific-computing
Basically that
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fork loumalouomega/awesome-scientific-computing
:sunglasses: Curated list of awesome software for numerical analysis and scientific computing
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startednschloe/awesome-scientific-computing
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