10000 pep 8, some doc update and new site.template.cfg. · PythonOptimizers/HSL.py@2a8e666 · GitHub
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syarrasyarra
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pep 8, some doc update and new site.template.cfg.
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‎config/setup.cpy

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@@ -8,12 +8,10 @@ import pysparse
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from distutils.core import setup
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from setuptools import find_packages
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from distutils.extension import Extension
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from Cython.Distutils import build_ext
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from numpy.distutils.misc_util import Configuration
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from numpy.distutils.system_info import get_info
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from numpy.distutils.core import setup
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from Cython.Build import cythonize
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import numpy as np
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‎config/setup.py

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@@ -8,12 +8,10 @@
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from distutils.core import setup
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from setuptools import find_packages
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from distutils.extension import Extension
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from Cython.Distutils import build_ext
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from numpy.distutils.misc_util import Configuration
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from numpy.distutils.system_info import get_info
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from numpy.distutils.core import setup
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from Cython.Build import cythonize
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import numpy as np
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‎doc/source/scaling.rst

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@@ -26,7 +26,7 @@ Example
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Output
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.. code-block:: bash
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.. code-block:: none
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orignal values:
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i j val

‎hsl/solvers/pyma27.py

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@@ -8,6 +8,7 @@
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from sils import Sils
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from hsl.solvers import _pyma27
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class PyMa27Solver(Sils):
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def __init__(self, A, **kwargs):
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# Statistics on A
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self.rwords = 0 # Number of real words used during factorization
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self.iwords = 0 # " int
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self.ncomp = 0 # " data compresses performed in analysis
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self.ncomp = 0 # " data compresses performed in analysis
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self.nrcomp = 0 # " real
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self.nicomp = 0 # " int
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self.n2x2pivots = 0 # " 2x2 pivots used
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self.neig = 0 # " negative eigenvalues detected
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self.neig = 0 # " negative eigenvalues detected
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# Factors
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self.L = spmatrix.ll_mat(self.n, self.n, 0)

‎hsl/solvers/sils.py

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@@ -6,15 +6,21 @@
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import numpy
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class Sils:
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"""
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Abstract class for the factorization and solution of symmetric indefinite
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systems of linear equations. The methods of this class must be overridden.
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"""
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def __init__(self, A, **kwargs):
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if not A.issym:
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raise ValueError, 'Input matrix must be symmetric'
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try:
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symmetric = A.issym
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except:
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symmetric = A.is_symmetric
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if not symmetric:
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raise ValueError('Input matrix must be symmetric')
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self.n = A.shape[0]
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self.sqd = 'sqd' in kwargs and kwargs['sqd']
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@@ -25,19 +31,13 @@ def __init__(self, A, **kwargs):
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self.context = None
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def solve(self, b, get_resid=True):
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"""
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Must be subclassed.
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"""
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"""Must be subclassed."""
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raise NotImplementedError
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def refine(self, b, nitref=3):
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"""
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Must be subclassed.
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"""
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"""Must be subclassed."""
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raise NotImplementedError
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def fetch_perm(self):
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"""
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Must be subclassed.
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"""
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"""Must be subclassed."""
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raise NotImplementedError

‎hsl/solvers/src/_cyma27_base.cpx

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@@ -20,16 +20,16 @@ cdef extern from "ma27.h":
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int nsteps
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int iflag # Pivot selection
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double ops # Operation count
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char rankdef # Indicate whether matrix is rank-deficient
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int rank; # Matrix rank
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int la
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@type|generic_to_c_type@ *factors # Matrix factors
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int maxfrt
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@type|generic_to_c_type@ *w # Real workspace
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@type|generic_to_c_type@ *residual # = b - Ax
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@type|generic_to_c_type@ *residual # = b - Ax
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char fetched # Factors have been fetched
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# Used for de-allocation
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@@ -173,11 +173,12 @@ cdef class BaseMA27Solver_@index@_@type@:
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def refine(self, np.ndarray[@type|generic_to_c_type@, ndim=1] x, np.ndarray[@type|generic_to_c_type@, ndim=1] rhs,
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np.ndarray[@type|generic_to_c_type@, ndim=1] residual, double tol=1e-8, int nitref=3, *args):
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"""
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refine performs iterative refinement if necessary
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until the scaled residual norm ||b-Ax||/(1+||b||) falls below a threshold 'tol'
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or until nitref steps are taken.
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"""Perform iterative refinement.
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If necessary, it performs iterative refinement until the scaled
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residual norm ||b-Ax||/(1+||b||) falls below a threshold 'tol' or until
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nitref steps are taken.
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warning: Make sure you have called solve() with the same right-hand
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side b before calling refine().
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return (new_x, new_res)
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def stats(self):
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"""
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Return statistics on the solve
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"""
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"""Return statistics on the solve."""
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return (self.data.info[8], # storage for real data of factors
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self.data.info[9], # storage for int data of factors
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self.data.info[10], # nb of data compresses performed in analysis

‎site.template.cfg

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@@ -97,12 +97,44 @@
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# named ma57d and one named mc29d. These should not be altered. The file
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# hsl_zd11d.f90 should be placed in hsl_dir.
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#
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# 4. You will also need the METIS library and header files. The source tree may
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# be downloaded from http://glaros.dtc.umn.edu/gkhome/metis/metis/download
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[CODE_GENERATION]
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# log file name **without** extension (by default, we use '.log')
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log_name = generator
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# DEBUG/INFO/WARNING/ERROR/CRITICAL
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log_level = DEBUG
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console_log_level = DEBUG
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file_log_level = DEBUG
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# 32bits/64bits
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# if left blank, we use INT64_t on 64 bits platforms and INT32_t on 32 bits platforms
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DEFAULT_INDEX_TYPE =
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# Do you want to generate the .c files from Cython?
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use_cython = true
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# Use debug symbols?
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use_debug_symbols = false
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# Defaults
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# ========
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# The settings given here will apply to all other sections if not overridden.
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# This is a good place to add general library and include directories like
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# /usr/local/{lib,include}
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#
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[DEFAULT]
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library_dirs = /usr/local/lib
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include_dirs = /usr/local/include
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[HSL]
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hsl_dir = /Users/syarra/work/programs/hsl
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hsl_rootdir = /Users/syarra/work/programs/hsl
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# METIS
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# -----
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# You will need the METIS library and header files.
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# The source tree may be downloaded from
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# http://glaros.dtc.umn.edu/gkhome/metis/metis/download
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[METIS]
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metis_dir = /usr/local/opt/metis4/lib
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metis_lib = metis
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# Optional
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[CYSPARSE]
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cysparse_rootdir = /Users/syarra/work/VirtualEnvs/nlpy_new/programs/cysparse/

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