-
Notifications
You must be signed in to change notification settings - Fork 5
/
setup.py
191 lines (162 loc) · 10.2 KB
/
setup.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
#!/usr/bin/env python
##############################################################################
#
# Copyright (C) 2011-2018 Dr Adam S. Candy and others.
#
# Shingle: An approach and software library for the generation of
# boundary representation from arbitrary geophysical fields
# and initialisation for anisotropic, unstructured meshing.
#
# Web: http://www.shingleproject.org
#
# Contact: Dr Adam S. Candy, [email protected]
#
# This file is part of the Shingle project.
#
# Please see the AUTHORS file in the main source directory for a full list
# of contributors.
#
# Shingle is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Shingle is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with Shingle. If not, see <http://www.gnu.org/licenses/>.
#
##############################################################################
from setuptools import setup, Extension
#from distutils.core import setup, Extension
import os, sys
from shingle.Version import version
description = """
Shingle
=======
[](http://travis-ci.org/shingleproject/Shingle)
[](https://www.python.org/downloads/)
[](https://pypi.python.org/pypi/shingle/)
[](https://doi.org/10.5281/zenodo.496172)
Generalised self-consistent and automated domain discretisation for multi-scale geophysical models.
Shingle is a generalised and accessible framework for model-independent and self-consistent geophysical domain discretisation, which accurately conform to fractal-like bounds and at varyingly resolved spatial scales. The full heterogeneous set of constraints are necessarily completely described by an extensible, hierarchical formal grammar with an intuitive natural language basis for geophysical domain features to achieve robust reproduction and consistent model intercomparisons.
LibShingle: Computational research software library providing a high-level abstraction to spatial discretisation, or mesh generation, for domains containing complex, fractal-like boundaries that characterise those in numerical simulations of geophysical dynamics. This is accompanied by a compact, shareable and necessarily complete description of the domain discretisation.
Geophysical model domains typically contain irregular, complex fractal-like boundaries and physical processes that act over a wide range of scales. Constructing geographically constrained boundary-conforming spatial discretisations of these domains with flexible use of anisotropic, fully unstructured meshes is a challenge. The problem contains a wide range of scales and a relatively large, heterogeneous constraint parameter space. Approaches are commonly ad hoc, model or application specific and insufficiently described. Development of new spatial domains is frequently time-consuming, hard to repeat, error prone and difficult to ensure consistent due to the significant human input required. As a consequence, it is difficult to reproduce simulations, ensure a provenance in model data handling and initialisation, and a challenge to conduct model intercomparisons rigorously. Moreover, for flexible unstructured meshes, there is additionally a greater potential for inconsistencies in model initialisation and forcing parameters. This library introduces a consistent approach to unstructured mesh generation for geophysical models, that is automated, quick-to-draft and repeat, and provides a rigorous and robust approach that is consistent to the source data throughout. The approach is enabling further new research in complex multi-scale domains, difficult or not possible to achieve with existing methods.
Outline web page: [http://shingleproject.org](http://shingleproject.org "Shingle")
Further details are provided in the library source and [Shingle project manual](https://github.com/shingleproject/Shingle/blob/master/doc/ShingleManual.pdf?raw=true "Shingle manual").
For further information and updates, please contact the lead author Dr Adam S. Candy at [email protected] and see related research pages at [http://candylab.org](http://candylab.org "http://candylab.org").
Example geophysical domains
---------------------------
A selection of geophysical domains where Shingle has been applied to describe and generate geophysical domain spatial discretisation.
Objectives
----------
1. Introduce a consistent approach to the generation of boundary representation to arbitrary geoid bounds.
2. A user-friendly, accessible and extensible framework for model-independent geophysical domain mesh generation.
3. An intuitive, hierarchical formal grammar to fully describe and share the full heterogeneous set of constraints for the spatial discretisation of geophysical model domains.
4. Natural language basis for describing geophysical domain features.
5. Self-consistent, scalable, automated and efficient mesh prototyping.
6. Platform for iterative development that is repeatable, reproducible with a provenance history of generation.
7. Enabling rigorous unstructured mesh generation in general, for a wide range of geophysical applications, in a process that is automated, quick-to-draft and repeat, rigorous and robust, and consistent to the source data throughout.
Verification test engine
------------------------
Includes a selection of examples, from a relatively straight-forward high-level GUI-driven interaction accessible to modellers new to mesh generation, to complex low-level development communicating with the LibShingle library. Python interaction is used within the source, in generating documentation and in example Jupyter notebooks.
A verification test engine is continuously run in response to source code changes, some of which is tested under [http://travis-ci.org/shingleproject/Shingle](Travis "Travis").
An earlier version of the library Shingle 1.0 is available at: [https://github.com/shingleproject/Shingle1.0](https://github.com/shingleproject/Shingle1.0 "Shingle1.0"), with details on the [Shingle1.0 webpage](http://shingleproject.org/index_shingle1.0.html "Shingle1.0 webpage").
"""
# Best to use GCC. Symbols are misnamed using clang.
os.environ["CC"] = "gcc"
os.environ["CXX"] = "g++"
libspud = Extension('libspud',
sources = [
'spud/python/libspud.c',
'spud/src/spud.cpp',
'spud/src/spud_interfaces.cpp',
'spud/src/tinystr.cpp',
'spud/src/tinyxml.cpp',
'spud/src/tinyxmlerror.cpp',
'spud/src/tinyxmlparser.cpp'
],
library_dirs=[os.path.abspath("spud")],
include_dirs=[os.path.abspath("spud/include")],
extra_link_args=['-lstdc++']
#extra_link_args=['-flat_namespace', '-lstdc++']
)
setup(name='shingle',
version=version,
description='Generation of boundary representation and mesh spatial discretisations from arbitrary geophysical fields.',
author = 'Adam S. Candy',
author_email='[email protected]',
license = "LGPLv3",
url = 'http://shingleproject.org',
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 4 - Beta',
# Indicate who your project is intended for
'Intended Audience :: Science/Research',
"Intended Audience :: Developers",
'Operating System :: OS Independent',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Topic :: Scientific/Engineering :: Physics',
'Topic :: Scientific/Engineering :: Mathematics',
'Topic :: Scientific/Engineering :: Atmospheric Science',
'Topic :: Scientific/Engineering :: GIS',
"Topic :: Software Development :: Libraries",
# Pick your license as you wish (should match "license" above)
"License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)",
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 2.7',
'Programming Language :: C'
],
keywords = 'geophysics, meshing, boundary representation, unstructured meshes, mulit-scale modelling, mesh generation, oceanography',
library_dirs=[os.path.abspath("spud")],
include_dirs=[os.path.abspath("spud/include")],
packages = ['shingle'],
#scripts=['src/shingle'],
entry_points = {
'console_scripts': ['shingle=shingle.CommandLine:main'],
},
options = {
'build_scripts': {
'executable': '/usr/bin/env python',
},
},
data_files = [('', [
'schema/shingle_options.rng',
'README.md',
'AUTHORS',
'COPYING',
'LICENSE',
])],
package_data={
'shingle':[
'schema/shingle_options.rng',
'README.md',
'AUTHORS',
'COPYING',
'LICENSE',
],
},
# install_requires = [
# 'libspud',
# 'numpy',
# 'ScientificPython',
# 'matplotlib',
# 'shapely',
# 'GDAL',
# 'Pillow',
# ],
ext_modules = [libspud],
include_package_data = True,
long_description_content_type = 'text/markdown',
long_description = description,
)