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DAMASK_EICMD
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modified background threading because using it in postResults led to an dead lock. 

rest modifications are just style
This commit is contained in:
Martin Diehl 2016-03-04 15:22:01 +01:00
parent 48233d2767
commit 75480bc677
1 changed files with 200 additions and 214 deletions
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290
lib/damask/util.py
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@ -6,11 +6,13 @@ import numpy as np
from optparse import Option from optparse import Option
class bcolors: class bcolors:
''' """
ASCII Colors (Blender code) ASCII Colors (Blender code)
https://svn.blender.org/svnroot/bf-blender/trunk/blender/build_files/scons/tools/bcolors.py https://svn.blender.org/svnroot/bf-blender/trunk/blender/build_files/scons/tools/bcolors.py
http://stackoverflow.com/questions/287871/print-in-terminal-with-colors-using-python http://stackoverflow.com/questions/287871/print-in-terminal-with-colors-using-python
''' """
HEADER = '\033[95m' HEADER = '\033[95m'
OKBLUE = '\033[94m' OKBLUE = '\033[94m'
OKGREEN = '\033[92m' OKGREEN = '\033[92m'
@ -32,9 +34,8 @@ class bcolors:
# ----------------------------- # -----------------------------
def srepr(arg, def srepr(arg,glue = '\n'):
glue = '\n'): """joins arguments as individual lines"""
# -----------------------------
if (not hasattr(arg, "strip") and if (not hasattr(arg, "strip") and
hasattr(arg, "__getitem__") or hasattr(arg, "__getitem__") or
hasattr(arg, "__iter__")): hasattr(arg, "__iter__")):
@ -42,20 +43,19 @@ def srepr(arg,
return arg if isinstance(arg,basestring) else repr(arg) return arg if isinstance(arg,basestring) else repr(arg)
# ----------------------------- # -----------------------------
def croak(what, def croak(what, newline = True):
newline = True): """writes formated to stderr"""
# -----------------------------
sys.stderr.write(srepr(what,glue = '\n') + ('\n' if newline else '')) sys.stderr.write(srepr(what,glue = '\n') + ('\n' if newline else ''))
sys.stderr.flush() sys.stderr.flush()
# ----------------------------- # -----------------------------
def report(who,what): def report(who,what):
# ----------------------------- """reports script and file name"""
croak( (emph(who) if who else '') + (': '+what if what else '') ) croak( (emph(who) if who else '') + (': '+what if what else '') )
# ----------------------------- # -----------------------------
def emph(what): def emph(what):
# ----------------------------- """emphasizes string on screen"""
return bcolors.BOLD+srepr(what)+bcolors.ENDC return bcolors.BOLD+srepr(what)+bcolors.ENDC
# ----------------------------- # -----------------------------
@ -68,7 +68,6 @@ for f in ['cos', 'sin', 'tan']:
# ----------------------------- # -----------------------------
def gridLocation(idx,res): def gridLocation(idx,res):
# -----------------------------
return ( idx % res[0], \ return ( idx % res[0], \
( idx // res[0]) % res[1], \ ( idx // res[0]) % res[1], \
( idx // res[0] // res[1]) % res[2] ) ( idx // res[0] // res[1]) % res[2] )
@ -76,7 +75,6 @@ def gridLocation(idx,res):
# ----------------------------- # -----------------------------
def gridIndex(location,res): def gridIndex(location,res):
# -----------------------------
return ( location[0] % res[0] + \ return ( location[0] % res[0] + \
( location[1] % res[1]) * res[0] + \ ( location[1] % res[1]) * res[0] + \
( location[2] % res[2]) * res[1] * res[0] ) ( location[2] % res[2]) * res[1] * res[0] )
@ -84,9 +82,11 @@ def gridIndex(location,res):
# ----------------------------- # -----------------------------
class extendableOption(Option): class extendableOption(Option):
# ----------------------------- """
# used for definition of new option parser action 'extend', which enables to take multiple option arguments used for definition of new option parser action 'extend', which enables to take multiple option arguments
# taken from online tutorial http://docs.python.org/library/optparse.html
taken from online tutorial http://docs.python.org/library/optparse.html
"""
ACTIONS = Option.ACTIONS + ("extend",) ACTIONS = Option.ACTIONS + ("extend",)
STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",) STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
@ -102,28 +102,34 @@ class extendableOption(Option):
# ----------------------------- # -----------------------------
class backgroundMessage(threading.Thread): class backgroundMessage(threading.Thread):
# ----------------------------- """reporting with animation to indicate progress"""
choices = {'bounce': ['_','o','O','°','¯','¯','°','O','o',], choices = {'bounce': ['_','o','O','°','¯','¯','°','O','o',],
'circle': [u'\u25f4',u'\u25f5',u'\u25f6',u'\u25f7'], 'circle': [u'\u25f4',u'\u25f5',u'\u25f6',u'\u25f7'],
'hexagon': [u'\u2b22',u'\u2b23'], 'hexagon': [u'\u2b22',u'\u2b23'],
'square': [u'\u2596',u'\u2598',u'\u259d',u'\u2597'], 'square': [u'\u2596',u'\u2598',u'\u259d',u'\u2597'],
'triangle': [u'\u140a',u'\u140a',u'\u1403',u'\u1405',u'\u1405',u'\u1403'], 'triangle': [u'\u140a',u'\u140a',u'\u1403',u'\u1405',u'\u1405',u'\u1403'],
'amoeba': [u'\u2596',u'\u258f',u'\u2598',u'\u2594',u'\u259d',u'\u2595',u'\u2597',u'\u2582'], 'amoeba': [u'\u2596',u'\u258f',u'\u2598',u'\u2594',u'\u259d',u'\u2595',
'beat': [u'\u2581',u'\u2582',u'\u2583',u'\u2585',u'\u2586',u'\u2587',u'\u2587',u'\u2586',u'\u2585',u'\u2583',u'\u2582',], u'\u2597',u'\u2582'],
'prison': [u'\u168b',u'\u168c',u'\u168d',u'\u168f',u'\u168e',u'\u168d',u'\u168c',u'\u168b',], 'beat': [u'\u2581',u'\u2582',u'\u2583',u'\u2585',u'\u2586',u'\u2587',
'breath': [u'\u1690',u'\u1691',u'\u1692',u'\u1693',u'\u1694',u'\u1693',u'\u1692',u'\u1691',u'\u1690',], u'\u2587',u'\u2586',u'\u2585',u'\u2583',u'\u2582',],
'prison': [u'\u168b',u'\u168c',u'\u168d',u'\u168f',u'\u168e',u'\u168d',
u'\u168c',u'\u168b',],
'breath': [u'\u1690',u'\u1691',u'\u1692',u'\u1693',u'\u1694',u'\u1693',
u'\u1692',u'\u1691',u'\u1690',],
'pulse': [u'·',u'•',u'\u25cf',u'\u25cf',u'•',], 'pulse': [u'·',u'•',u'\u25cf',u'\u25cf',u'•',],
'ant': [u'\u2801',u'\u2802',u'\u2810',u'\u2820',u'\u2804',u'\u2840',u'\u2880',u'\u2820',u'\u2804',u'\u2802',u'\u2810',u'\u2808'], 'ant': [u'\u2801',u'\u2802',u'\u2810',u'\u2820',u'\u2804',u'\u2840',
'juggle': [u'\ua708',u'\ua709',u'\ua70a',u'\ua70b',u'\ua70c',u'\ua711',u'\ua710',u'\ua70f',u'\ua70d',], u'\u2880',u'\u2820',u'\u2804',u'\u2802',u'\u2810',u'\u2808'],
'juggle': [u'\ua708',u'\ua709',u'\ua70a',u'\ua70b',u'\ua70c',u'\ua711',
u'\ua710',u'\ua70f',u'\ua70d',],
# 'wobbler': [u'\u2581',u'\u25e3',u'\u258f',u'\u25e4',u'\u2594',u'\u25e5',u'\u2595',u'\u25e2',], # 'wobbler': [u'\u2581',u'\u25e3',u'\u258f',u'\u25e4',u'\u2594',u'\u25e5',u'\u2595',u'\u25e2',],
'grout': [u'\u2581',u'\u258f',u'\u2594',u'\u2595',], 'grout': [u'\u2581',u'\u258f',u'\u2594',u'\u2595',],
'partner': [u'\u26ac',u'\u26ad',u'\u26ae',u'\u26af',u'\u26ae',u'\u26ad',], 'partner': [u'\u26ac',u'\u26ad',u'\u26ae',u'\u26af',u'\u26ae',u'\u26ad',],
'classic': ['-', '\\', '|', '/',], 'classic': ['-', '\\', '|', '/',],
} }
def __init__(self, def __init__(self,symbol = None,wait = 0.1):
symbol = None, """sets animation symbol"""
wait = 0.1):
super(backgroundMessage, self).__init__() super(backgroundMessage, self).__init__()
self._stop = threading.Event() self._stop = threading.Event()
self.message = '' self.message = ''
@ -134,6 +140,7 @@ class backgroundMessage(threading.Thread):
self.waittime = wait self.waittime = wait
def __quit__(self): def __quit__(self):
"""cleans output"""
length = len(self.symbols[self.counter] + self.gap + self.message) length = len(self.symbols[self.counter] + self.gap + self.message)
sys.stderr.write(chr(8)*length + ' '*length + chr(8)*length) sys.stderr.write(chr(8)*length + ' '*length + chr(8)*length)
sys.stderr.write('') sys.stderr.write('')
@ -146,8 +153,7 @@ class backgroundMessage(threading.Thread):
return self._stop.is_set() return self._stop.is_set()
def run(self): def run(self):
# while not threading.enumerate()[0]._Thread__stopped: while not threading.enumerate()[0]._Thread__stopped:
while not self.stopped():
time.sleep(self.waittime) time.sleep(self.waittime)
self.update_message() self.update_message()
self.__quit__() self.__quit__()
@ -170,116 +176,19 @@ class backgroundMessage(threading.Thread):
def animation(self,which = None): def animation(self,which = None):
return ''.join(self.choices[which]) if which in self.choices else '' return ''.join(self.choices[which]) if which in self.choices else ''
'''
Non-linear least square fitting (Levenberg-Marquardt method) with
bounded parameters.
the codes of transformation between int <-> ext refers to the work of
Jonathan J. Helmus: https://github.com/jjhelmus/leastsqbound-scipy
other codes refers to the source code of minpack.py:
..\Lib\site-packages\scipy\optimize\minpack.py
'''
from numpy import (array, arcsin, asarray, cos, dot, eye, empty_like,
isscalar,finfo, take, triu, transpose, sqrt, sin)
def _check_func(checker, argname, thefunc, x0, args, numinputs,
output_shape=None):
from numpy import atleast_1d, shape, issubdtype, dtype, inexact
'''
The same as that of minpack.py,
'''
res = atleast_1d(thefunc(*((x0[:numinputs],) + args)))
if (output_shape is not None) and (shape(res) != output_shape):
if (output_shape[0] != 1):
if len(output_shape) > 1:
if output_shape[1] == 1:
return shape(res)
msg = "%s: there is a mismatch between the input and output " \
"shape of the '%s' argument" % (checker, argname)
func_name = getattr(thefunc, '__name__', None)
if func_name:
msg += " '%s'." % func_name
else:
msg += "."
raise TypeError(msg)
if issubdtype(res.dtype, inexact):
dt = res.dtype
else:
dt = dtype(float)
return shape(res), dt
def _int2extGrad(p_int, bounds):
"""
Calculate the gradients of transforming the internal (unconstrained)
to external (constained) parameter.
"""
grad = empty_like(p_int)
for i, (x, bound) in enumerate(zip(p_int, bounds)):
lower, upper = bound
if lower is None and upper is None: # No constraints
grad[i] = 1.0
elif upper is None: # only lower bound
grad[i] = x/sqrt(x*x + 1.0)
elif lower is None: # only upper bound
grad[i] = -x/sqrt(x*x + 1.0)
else: # lower and upper bounds
grad[i] = (upper - lower)*cos(x)/2.0
return grad
def _int2extFunc(bounds):
'''
transform internal parameters into external parameters.
'''
local = [_int2extLocal(b) for b in bounds]
def _transform_i2e(p_int):
p_ext = empty_like(p_int)
p_ext[:] = [i(j) for i, j in zip(local, p_int)]
return p_ext
return _transform_i2e
def _ext2intFunc(bounds):
'''
transform external parameters into internal parameters.
'''
local = [_ext2intLocal(b) for b in bounds]
def _transform_e2i(p_ext):
p_int = empty_like(p_ext)
p_int[:] = [i(j) for i, j in zip(local, p_ext)]
return p_int
return _transform_e2i
def _int2extLocal(bound):
'''
transform a single internal parameter to an external parameter.
'''
lower, upper = bound
if lower is None and upper is None: # no constraints
return lambda x: x
elif upper is None: # only lower bound
return lambda x: lower - 1.0 + sqrt(x*x + 1.0)
elif lower is None: # only upper bound
return lambda x: upper + 1.0 - sqrt(x*x + 1.0)
else:
return lambda x: lower + ((upper - lower)/2.0)*(sin(x) + 1.0)
def _ext2intLocal(bound):
'''
transform a single external parameter to an internal parameter.
'''
lower, upper = bound
if lower is None and upper is None: # no constraints
return lambda x: x
elif upper is None: # only lower bound
return lambda x: sqrt((x - lower + 1.0)**2 - 1.0)
elif lower is None: # only upper bound
return lambda x: sqrt((x - upper - 1.0)**2 - 1.0)
else:
return lambda x: arcsin((2.0*(x - lower)/(upper - lower)) - 1.0)
def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0, def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0,
col_deriv=0, ftol=1.49012e-8, xtol=1.49012e-8, col_deriv=0, ftol=1.49012e-8, xtol=1.49012e-8,
gtol=0.0, maxfev=0, epsfcn=None, factor=100, diag=None): gtol=0.0, maxfev=0, epsfcn=None, factor=100, diag=None):
from scipy.optimize import _minpack from scipy.optimize import _minpack
''' """
Non-linear least square fitting (Levenberg-Marquardt method) with
bounded parameters.
the codes of transformation between int <-> ext refers to the work of
Jonathan J. Helmus: https://github.com/jjhelmus/leastsqbound-scipy
other codes refers to the source code of minpack.py:
..\Lib\site-packages\scipy\optimize\minpack.py
An internal parameter list is used to enforce contraints on the fitting An internal parameter list is used to enforce contraints on the fitting
parameters. The transfomation is based on that of MINUIT package. parameters. The transfomation is based on that of MINUIT package.
please see: F. James and M. Winkler. MINUIT User's Guide, 2004. please see: F. James and M. Winkler. MINUIT User's Guide, 2004.
@ -293,11 +202,92 @@ def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0,
This function is based on 'leastsq' of minpack.py, the annotation of This function is based on 'leastsq' of minpack.py, the annotation of
other parameters can be found in 'leastsq'. other parameters can be found in 'leastsq'.
..\Lib\site-packages\scipy\optimize\minpack.py ..\Lib\site-packages\scipy\optimize\minpack.py
''' """
def _check_func(checker, argname, thefunc, x0, args, numinputs,
output_shape=None):
"""The same as that of minpack.py"""
res = np.atleast_1d(thefunc(*((x0[:numinputs],) + args)))
if (output_shape is not None) and (shape(res) != output_shape):
if (output_shape[0] != 1):
if len(output_shape) > 1:
if output_shape[1] == 1:
return shape(res)
msg = "%s: there is a mismatch between the input and output " \
"shape of the '%s' argument" % (checker, argname)
func_name = getattr(thefunc, '__name__', None)
if func_name:
msg += " '%s'." % func_name
else:
msg += "."
raise TypeError(msg)
if np.issubdtype(res.dtype, np.inexact):
dt = res.dtype
else:
dt = dtype(float)
return shape(res), dt
def _int2extGrad(p_int, bounds):
"""Calculate the gradients of transforming the internal (unconstrained) to external (constained) parameter."""
grad = np.empty_like(p_int)
for i, (x, bound) in enumerate(zip(p_int, bounds)):
lower, upper = bound
if lower is None and upper is None: # No constraints
grad[i] = 1.0
elif upper is None: # only lower bound
grad[i] = x/np.sqrt(x*x + 1.0)
elif lower is None: # only upper bound
grad[i] = -x/np.sqrt(x*x + 1.0)
else: # lower and upper bounds
grad[i] = (upper - lower)*np.cos(x)/2.0
return grad
def _int2extFunc(bounds):
"""transform internal parameters into external parameters."""
local = [_int2extLocal(b) for b in bounds]
def _transform_i2e(p_int):
p_ext = np.empty_like(p_int)
p_ext[:] = [i(j) for i, j in zip(local, p_int)]
return p_ext
return _transform_i2e
def _ext2intFunc(bounds):
"""transform external parameters into internal parameters."""
local = [_ext2intLocal(b) for b in bounds]
def _transform_e2i(p_ext):
p_int = np.empty_like(p_ext)
p_int[:] = [i(j) for i, j in zip(local, p_ext)]
return p_int
return _transform_e2i
def _int2extLocal(bound):
"""transform a single internal parameter to an external parameter."""
lower, upper = bound
if lower is None and upper is None: # no constraints
return lambda x: x
elif upper is None: # only lower bound
return lambda x: lower - 1.0 + np.sqrt(x*x + 1.0)
elif lower is None: # only upper bound
return lambda x: upper + 1.0 - np.sqrt(x*x + 1.0)
else:
return lambda x: lower + ((upper - lower)/2.0)*(np.sin(x) + 1.0)
def _ext2intLocal(bound):
"""transform a single external parameter to an internal parameter."""
lower, upper = bound
if lower is None and upper is None: # no constraints
return lambda x: x
elif upper is None: # only lower bound
return lambda x: np.sqrt((x - lower + 1.0)**2 - 1.0)
elif lower is None: # only upper bound
return lambda x: np.sqrt((x - upper - 1.0)**2 - 1.0)
else:
return lambda x: np.arcsin((2.0*(x - lower)/(upper - lower)) - 1.0)
i2e = _int2extFunc(bounds) i2e = _int2extFunc(bounds)
e2i = _ext2intFunc(bounds) e2i = _ext2intFunc(bounds)
x0 = asarray(x0).flatten() x0 = np.asarray(x0).flatten()
n = len(x0) n = len(x0)
if len(bounds) != n: if len(bounds) != n:
@ -312,9 +302,8 @@ def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0,
if n > m: if n > m:
raise TypeError('Improper input: N=%s must not exceed M=%s' % (n, m)) raise TypeError('Improper input: N=%s must not exceed M=%s' % (n, m))
if epsfcn is None: if epsfcn is None:
epsfcn = finfo(dtype).eps epsfcn = np.finfo(dtype).eps
# wrapped func
def funcWarp(x, *args): def funcWarp(x, *args):
return func(i2e(x), *args) return func(i2e(x), *args)
@ -333,7 +322,6 @@ def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0,
if maxfev == 0: if maxfev == 0:
maxfev = 100*(n + 1) maxfev = 100*(n + 1)
# wrapped Dfun
def DfunWarp(x, *args): def DfunWarp(x, *args):
return Dfun(i2e(x), *args) return Dfun(i2e(x), *args)
@ -369,7 +357,7 @@ def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0,
if info not in [1, 2, 3, 4] and not full_output: if info not in [1, 2, 3, 4] and not full_output:
if info in [5, 6, 7, 8]: if info in [5, 6, 7, 8]:
warnings.warn(errors[info][0], RuntimeWarning) np.warnings.warn(errors[info][0], RuntimeWarning)
else: else:
try: try:
raise errors[info][1](errors[info][0]) raise errors[info][1](errors[info][0])
@ -381,17 +369,17 @@ def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0,
if full_output: if full_output:
grad = _int2extGrad(retval[0], bounds) grad = _int2extGrad(retval[0], bounds)
retval[1]['fjac'] = (retval[1]['fjac'].T / take(grad, retval[1]['fjac'] = (retval[1]['fjac'].T / np.take(grad,
retval[1]['ipvt'] - 1)).T retval[1]['ipvt'] - 1)).T
cov_x = None cov_x = None
if info in [1, 2, 3, 4]: if info in [1, 2, 3, 4]:
from numpy.dual import inv from numpy.dual import inv
from numpy.linalg import LinAlgError from numpy.linalg import LinAlgError
perm = take(eye(n), retval[1]['ipvt'] - 1, 0) perm = np.take(np.eye(n), retval[1]['ipvt'] - 1, 0)
r = triu(transpose(retval[1]['fjac'])[:n, :]) r = np.triu(np.transpose(retval[1]['fjac'])[:n, :])
R = dot(r, perm) R = np.dot(r, perm)
try: try:
cov_x = inv(dot(transpose(R), R)) cov_x = inv(np.dot(np.transpose(R), R))
except LinAlgError as inverror: except LinAlgError as inverror:
print inverror print inverror
pass pass
@ -405,7 +393,7 @@ def _weighted_general_function(params, ydata, xdata, function, weights):
return (function(xdata, *params) - ydata)*weights return (function(xdata, *params) - ydata)*weights
def curve_fit_bound(f, xdata, ydata, p0=None, sigma=None, bounds=None, **kw): def curve_fit_bound(f, xdata, ydata, p0=None, sigma=None, bounds=None, **kw):
''' Similar as 'curve_fit' in minpack.py''' """Similar as 'curve_fit' in minpack.py"""
if p0 is None: if p0 is None:
# determine number of parameters by inspecting the function # determine number of parameters by inspecting the function
import inspect import inspect
@ -418,15 +406,15 @@ def curve_fit_bound(f, xdata, ydata, p0=None, sigma=None, bounds=None, **kw):
else: else:
p0 = [1.0] * (len(args)-1) p0 = [1.0] * (len(args)-1)
if isscalar(p0): if np.isscalar(p0):
p0 = array([p0]) p0 = np.array([p0])
args = (ydata, xdata, f) args = (ydata, xdata, f)
if sigma is None: if sigma is None:
func = _general_function func = _general_function
else: else:
func = _weighted_general_function func = _weighted_general_function
args += (1.0/asarray(sigma),) args += (1.0/np.asarray(sigma),)
return_full = kw.pop('full_output', False) return_full = kw.pop('full_output', False)
res = leastsqBound(func, p0, args=args, bounds = bounds, full_output=True, **kw) res = leastsqBound(func, p0, args=args, bounds = bounds, full_output=True, **kw)
@ -440,7 +428,7 @@ def curve_fit_bound(f, xdata, ydata, p0=None, sigma=None, bounds=None, **kw):
s_sq = (func(popt, *args)**2).sum()/(len(ydata)-len(p0)) s_sq = (func(popt, *args)**2).sum()/(len(ydata)-len(p0))
pcov = pcov * s_sq pcov = pcov * s_sq
else: else:
pcov = inf pcov = np.inf
if return_full: if return_full:
return popt, pcov, infodict, errmsg, ier return popt, pcov, infodict, errmsg, ier
@ -449,13 +437,11 @@ def curve_fit_bound(f, xdata, ydata, p0=None, sigma=None, bounds=None, **kw):
def execute(cmd,streamIn=None,wd='./'): def execute(cmd,streamIn=None,wd='./'):
''' """executes a command in given directory and returns stdout and stderr for optional stdin"""
executes a command in given directory and returns stdout and stderr for optional stdin
'''
initialPath=os.getcwd() initialPath=os.getcwd()
os.chdir(wd) os.chdir(wd)
process = subprocess.Popen(shlex.split(cmd),stdout=subprocess.PIPE,stderr = subprocess.PIPE,stdin=subprocess.PIPE) process = subprocess.Popen(shlex.split(cmd),stdout=subprocess.PIPE,stderr = subprocess.PIPE,stdin=subprocess.PIPE)
if streamIn != None: if streamIn is not None:
out,error = process.communicate(streamIn.read()) out,error = process.communicate(streamIn.read())
else: else:
out,error = process.communicate() out,error = process.communicate()