def ART2(X, a=10, b=10, c=0.3, d=0.75, theta=0.1, rho=0.997, output=None, e=1E-8):
if a <= 0:
print('a should > 0, but a is ', str(a))
raise
if b <= 0:
print('b should > 0, but is ', str(b))
raise
if d < 0 or d > 1:
print('0 <= d <= 1, but d is ', str(d))
raise
if c * d / (1 - d) > 1:
print('c*d/(1-d) <= 1, but c*d/(1-d) is ', str(c * d / (1 - d)))
if rho <= 0 or rho > 1:
print('0 < rho <= 1, but rho is ', str(rho))
raise
if e > 1E-1:
warnings('e << 1, but e is ', str(e))
X = np.array(X)
m, n = X.shape
if output is None:
output = m
WF1_F2 = np.dot(np.ones((output,n)),0.5/((1-d)*math.sqrt(n)))
WF2_F1 = np.zeros((n, output))
w = np.zeros(m)
for j in range(m):
Input = X[j,:]
u,J = ART_Process(Input, output,a,b,c,d,WF1_F2,WF2_F1, rho,theta,e)
WF2_F1[:,J] = np.transpose((u/(1-d))[0])
WF1_F2[J,:] = (u/(1-d))[0]
w[j] = J
return w
def window_args(self, val):
# If future value is not available, force to set the labels at the
# right end of the window to avoid data leakage.
if not self.future_value_available and "center" in val and val[
"center"] is True:
val["center"] = False
warnings("window_args['center'] is set to False, because "
"future_value_available is False")
self._window_args = val
def get_min_cost(features, label):
Xs = np.array(features)
ys = np.array(label)
Xs_multiply = np.dot(Xs.T, Xs)
try:
inverse = np.linalg.inv(Xs_multiply)
except np.linalg.LinAlgError:
warnings("looks like matrix is non-inverable")
min_cost = np.dot(inverse, np.dot(Xs.T, ys))
return min_cost
def __call__(self, inputs):
axes = self.get_axes()
for axe in axes:
try:
f = axe.get_figure()
f.clf()
except:
import warnings
warnings('a figure could not be selected or deleted.')
axe.get_figure().canvas.draw()
return self.get_input('axes')
def __call__(self, inputs):
axes = self.get_axes()
for axe in axes:
try:
f = axe.get_figure()
f.clf()
except:
import warnings
warnings('a figure could not be selected or deleted.')
axe.get_figure().canvas.draw()
return self.get_input('axes')
def getFile(filename, commentPrefix='#', lowercase=False, unique=False):
retVal = list() if not unique else OrderedDict()
if filename:
filename = filename.strip('"\'')
checkFile(filename)
try:
with open(filename, 'r') as f:
for l in f:
if commentPrefix:
if l.find(commentPrefix) != -1:
l = l[:l.find(commentPrefix)]
line = line.strip()
if line:
if lowercase:
line = line.lower()
if unique and line in retVal:
continue
if unique:
retVal[line] = True
else:
retVal.append(line)
except (IOError, OSError, MemoryError) as ex:
errMsg = "something went wrong while trying "
errMsg += "to read the content of file '%s' ('%s')" % (filename, (ex))
raise warnings(errMsg)
return retVal if not unique else list(retVal.keys())
def culledLegForwardTransform(orders, locations, functionVals, threshold=None):
# inspired by : A Simple Regularization of the Polynomial Interpolation For the Runge Phenomemenon
if len(locations.shape)==1:
vandermonde=leg.legvander(locations, orders[0])
elif locations.shape[1]==2:
vandermonde=leg.legvander2d(locations[:,0], locations[:,1], orders)
elif locations.shape[1]==3:
vandermonde=leg.legvander3d(locations[:,0],locations[:,1],locations[:,2], orders)
elif locations.shape[1]==4:
vandermonde=legvander4d(locations,orders)
elif locations.shape[1]==5:
vandermonde=legvander5d(locations,orders)
else:
raise NotImplementedError # there's a bad startup joke about this being good enough for the paper.
# preconditioner = np.diag((0.94) ** (2* (np.arange(vandermonde.shape[0]))))
# vandermonde=np.dot(preconditioner, vandermonde)
U,S,Vh=np.linalg.svd(vandermonde)
numTake=0
filtS=S
if threshold is None:
Eps= np.finfo(functionVals.dtype).eps
Neps = np.prod(cmn.numpyze(orders)) * Eps * S[0] #truncation due to ill-conditioning
Nt = max(np.argmax(Vh, axis=0)) #"Automatic" determination of threshold due to Runge's phenomenon
threshold=min(Neps, Nt)
while numTake<=0:
filter=S>threshold
numTake=filter.sum()
if numTake>0:
filtU=U[:,:numTake]; filtS=S[:numTake]; filtVh=Vh[:numTake, :]
else:
if threshold>1e-13:
threshold=threshold/2
warnings.warn('cutting threshold for eigenvalues to '+str(threshold))
else:
warnings('seems all eigenvalues are zero (<1e-13), setting to zero and breaking')
filtS=np.zeros_like(S)
truncVander=np.dot(filtU,np.dot(np.diag(filtS),filtVh))
ret, _, _, _=npl.lstsq(truncVander, functionVals, rcond=None)
return np.reshape(ret, np.array(orders).flatten()+1)
def k_nearest_neighbors(data, predict, k=3):
if len(data) > k:
warnings(
"The dataset is larger than the K parameter. Increase the size of K"
)
distance = []
for group in data:
for feature in data[group]:
euclidean_distance = np.linalg.norm(
np.array(feature) - np.array(predict))
distance.append([euclidean_distance, group])
for i in sorted(distance)[:k]:
votes = i[1]
vote_result = Counter(votes).most_common(1)[0][0]
return vote_result
def __init__(self, jobdir=None, jobid=None, ram_dir=None):
"""Declare a Ramses instance for a given job. The job can be
specified by one of the following options:
1. r = Ramses(`job_dir`), where `job_dir` is the path to the job directory.
2. r = Ramses(jobid = `_id`, ram_dir = `ram_dir`), where `ram_dir` is the directory where all the RAMSES jobs are stored, and `_id` is the string after "Job". This is equivalent to Ramses(`ram_dir/Job_id`)
3. ramtools.set_RAM_DIR(`ram_dir`); r = Ramses(jobid = `_id`).
Args:
jobdir : str
relative/absolute path to the job directory
jobid : str
jobid, postfix to 'Job' to get the job directory name (in `ram_dir`)
ram_dir : str
the base directory for the RAMSES jobs
"""
if jobdir is not None:
self.jobPath = jobdir
self.jobid = os.path.basename(jobdir)[3:]
elif jobid is None:
warnings("Need to specify either jobdir or jobid")
return
else:
if ram_dir is None:
if RAM_DIR is None:
warnings("Need to define ram_dir. Either specify"
"ram_dir as a parameter, or define a global RAM_DIR"
"by calling ramtools.set_RAM_DIR(`ram_dir`)")
return
else:
ram_dir = RAM_DIR
self.jobPath = f"{ram_dir}/Job{jobid}"
self.jobid = jobid
self.ds1 = None
if self.get_units() == 0:
self.tRelax = self.get_trelax()
self.ramses_dir = os.path.dirname(self.jobPath if self.jobPath[-1] !=
'/' else self.jobPath[:-1])
self.data_dir = os.path.join(self.ramses_dir, "h5_data")
def truncatedVandermondeForwardTransform(freqs, locations, functionVals, threshold=None):
freqProd=freqTuples(freqs)
if len(locations.shape)==1:
pointLoc=locations[:,np.newaxis]
else:
pointLoc=locations
# TODO: noncomplex evaluation of vandermonde
exponentTerm=2*np.pi*1j*np.dot(pointLoc,freqProd) # no transpose?
pseudoVander=np.exp(exponentTerm)
U,S,Vh=np.linalg.svd(pseudoVander)
numTake=0
filtS=S
if threshold is None:
Eps= np.finfo(functionVals.dtype).eps
Neps = np.prod(cmn.numpyze(freqs.shape)) * Eps * S[0] #truncation due to ill-conditioning
# Nt = max(np.argmax(Vh, axis=0)) #"Automatic" determination of threshold due to Runge's phenomenon
# threshold=min(Neps, Nt)
threshold=Neps
while numTake<=0:
filter=S>threshold
numTake=filter.sum()
if numTake>0:
filtU=U[:,:numTake]; filtS=S[:numTake]; filtVh=Vh[:numTake, :]
else:
if threshold>1e-13:
threshold=threshold/2
warnings.warn('cutting threshold for eigenvalues to '+str(threshold))
else:
warnings('seems all eigenvalues are zero (<1e-13), setting to zero and breaking')
filtS=np.zeros_like(S)
truncVander=np.dot(filtU,np.dot(np.diag(filtS),filtVh))
ret, _, _, _=npl.lstsq(truncVander, functionVals, rcond=None)
if len(freqs.shape)>1:
numFreqs=list(map(len, freqs))
else:
numFreqs=len(freqs)
return np.reshape(ret, numFreqs)
def setRandomAgent():
userAgents = open('data/txt/random_agents.txt', 'r')
if not userAgents:
debugMsg = info + "loading random HTTP User-Agent header(s) from "
debugMsg += "file 'data/txt/random_agents.txt'"
logging.debug(debugMsg)
try:
userAgents = getFile('data/txt/random_agents.txt')
except IOError:
errMsg = "unable to read HTTP User-Agent file "
errMsg += "file 'data/txt/random_agents.txt'"
raise warnings(errMsg)
return random.sample(userAgents, 1)[0]
def checkFile(filename, raiseOnError=True):
valid = True
if filename:
filename = filename.strip('"\'')
else:
try:
if filename is None or not os.path.isfile(filename):
valid = False
except:
valid = False
if valid:
try:
with open(filename, "rb"):
pass
except:
valid = False
if not valid and raiseOnError:
raise warnings("unable to read file '%s'" % filename)
return valid
try:
from setuptools import setup
except ImportError:
from distutils import setup
import warnings
warnings('Please install setuptools or distribute!')
# Workaround for http://bugs.python.org/issue15881#msg170215
try:
import multiprocessing # noqa
except ImportError:
pass
long_description = open('README.rst').read()
setup(
name='requirements-parser',
version='0.1.0',
description='Parses Pip requirement files',
long_description=long_description,
author='David Fischer',
author_email='*****@*****.**',
url='https://github.com/davidfischer/requirements-parser',
license='BSD',
platforms=['OS Independent'],
packages=['requirements'],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'License :: OSI Approved :: BSD License',
'Operating System :: OS Independent',
# GromacsWrapper
# Copyright (c) 2009-2010 Oliver Beckstein <*****@*****.**>
# Released under the GNU Public License 3 (or higher, your choice)
# See the file COPYING for details.
"""
:mod:`gromacs` -- GromacsWrapper Package Overview
=================================================
**GromacsWrapper** (package :mod:`gromacs`) is a thin shell around the `Gromacs`_
tools for light-weight integration into python scripts or interactive use in
`ipython`_.
.. _`Gromacs`: http://www.gromacs.org
.. _`ipython`: http://ipython.scipy.org
Modules
-------
:mod:`gromacs`
The top level module contains all gromacs tools; each tool can be
run directly or queried for its documentation. It also defines
the root logger class (name *gromacs* by default).
:mod:`gromacs.config`
Configuration options. Not really used much at the moment.
:mod:`gromacs.cbook`
The Gromacs cook book contains typical applications of the tools. In many
cases this not more than just an often-used combination of parameters for
def assert_equal_objects(obj1, obj2, attributes_dict=None, logger=None):
def print_not_equal_message(attr, logger):
# logger.error("\n\nValueError: Original and read object field "+ attr + " not equal!")
# raise ValueError("\n\nOriginal and read object field " + attr + " not equal!")
warning("Original and read object field " + attr + " not equal!",
logger)
if isinstance(obj1, dict):
get_field1 = lambda obj, key: obj[key]
if not (isinstance(attributes_dict, dict)):
attributes_dict = dict()
for key in obj1.keys():
attributes_dict.update({key: key})
else:
get_field1 = lambda obj, attribute: getattr(obj, attribute)
if not (isinstance(attributes_dict, dict)):
attributes_dict = dict()
for key in obj1.__dict__.keys():
attributes_dict.update({key: key})
if isinstance(obj2, dict):
get_field2 = lambda obj, key: obj.get(key, None)
else:
get_field2 = lambda obj, attribute: getattr(obj, attribute, None)
equal = True
for attribute in attributes_dict:
#print attributes_dict[attribute]
field1 = get_field1(obj1, attributes_dict[attribute])
field2 = get_field2(obj2, attributes_dict[attribute])
try:
#TODO: a better hack for the stupid case of an ndarray of a string, such as model.zmode or pmode
# For non numeric types
if isinstance(field1, basestring) or isinstance(field1, list) or isinstance(field1, dict) \
or (isinstance(field1, np.ndarray) and field1.dtype.kind in 'OSU'):
if np.any(field1 != field2):
print_not_equal_message(attributes_dict[attribute], logger)
equal = False
# For numeric types
elif isinstance(field1, (int, float, long, complex, np.number, np.ndarray)) \
and not (isinstance(field1, np.ndarray) and field1.dtype.kind in 'OSU'):
# TODO: handle better accuracy differences and complex numbers...
if np.any(np.float32(field1) - np.float32(field2) > 0):
print_not_equal_message(attributes_dict[attribute], logger)
equal = False
else:
warning(
"Comparing str(objects) for field " +
attributes_dict[attribute] +
" because it is of unknown type!", logger)
if np.any(str(field1) != str(field2)):
print_not_equal_message(attributes_dict[attribute], logger)
equal = False
except:
try:
warnings(
"Comparing str(objects) for field " +
attributes_dict[attribute] +
" because there was an error!", logger)
if np.any(str(field1) != str(field2)):
print_not_equal_message(attributes_dict[attribute], logger)
equal = False
except:
raise_value_error(
"ValueError: Something went wrong when trying to compare "
+ attributes_dict[attribute] + " !", logger)
if equal:
return True
else:
return False
def index_doc(self, doc):
_id = doc[0]
d = doc[1]
status = self.es.index(index='nssd', doc_type='doc', body=d, id=_id)
if not status['created']:
warnings('Document {} not created'.format(status['_id']))
from enchant.errors import *
from enchant.utils import EnchantStr, get_default_language, UTF16EnchantStr
from enchant.pypwl import PyPWL
# Due to the unfortunate name collision between the enchant "tokenize" module
# and the stdlib "tokenize" module, certain values of sys.path can cause
# the former to override the latter and break the "warnings" module.
# This hacks around it by making a dummy "warnings" module.
try:
import warnings
except ImportError:
class warnings(object):
def warn(self,*args,**kwds):
pass
warnings = warnings()
class ProviderDesc(object):
"""Simple class describing an Enchant provider.
Each provider has the following information associated with it:
* name: Internal provider name (e.g. "aspell")
* desc: Human-readable description (e.g. "Aspell Provider")
* file: Location of the library containing the provider
"""
_DOC_ERRORS = ["desc"]
def __init__(self,name,desc,file):
try:
from setuptools import setup
except ImportError:
from distutils import setup
import warnings
warnings('Please install setuptools or distribute!')
# Workaround for http://bugs.python.org/issue15881#msg170215
try:
import multiprocessing # noqa
except ImportError:
pass
long_description = open('README.rst').read()
setup(
name='requirements-parser',
version='0.2.0',
description='Parses Pip requirement files',
long_description=long_description,
author='David Fischer',
author_email='*****@*****.**',
url='https://github.com/davidfischer/requirements-parser',
license='BSD',
platforms=['OS Independent'],
packages=['requirements'],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'License :: OSI Approved :: BSD License',
try:
from setuptools import setup
except ImportError:
from distutils import setup
import warnings
warnings("Please install setuptools or distribute!")
# Workaround for http://bugs.python.org/issue15881#msg170215
try:
import multiprocessing # noqa
except ImportError:
pass
long_description = open("README.rst").read()
setup(
name="requirements-parser",
version="0.0.6",
description="Parses Pip requirement files",
long_description=long_description,
author="David Fischer",
author_email="*****@*****.**",
url="https://github.com/davidfischer/requirements-parser",
license="BSD",
platforms=["OS Independent"],
packages=["requirements"],
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
# GromacsWrapper
# Copyright (c) 2009-2010 Oliver Beckstein <*****@*****.**>
# Released under the GNU Public License 3 (or higher, your choice)
# See the file COPYING for details.
""":mod:`gromacs` -- GromacsWrapper Package Overview
=================================================
**GromacsWrapper** (package :mod:`gromacs`) is a thin shell around the `Gromacs`_
tools for light-weight integration into python scripts or interactive use in
`ipython`_.
.. _`Gromacs`: http://www.gromacs.org
.. _`ipython`: http://ipython.scipy.org
Modules
-------
:mod:`gromacs`
The top level module contains all gromacs tools; each tool can be
run directly or queried for its documentation. It also defines
the root logger class (name *gromacs* by default).
:mod:`gromacs.config`
Configuration options. Not really used much at the moment.
:mod:`gromacs.cbook`
The Gromacs cook book contains typical applications of the tools. In many
cases this not more than just an often-used combination of parameters for
a tool.
# GromacsWrapper
# Copyright (c) 2009-2010 Oliver Beckstein <*****@*****.**>
# Released under the GNU Public License 3 (or higher, your choice)
# See the file COPYING for details.
""":mod:`gromacs` -- GromacsWrapper Package Overview
=================================================
**GromacsWrapper** (package :mod:`gromacs`) is a thin shell around the `Gromacs`_
tools for light-weight integration into python scripts or interactive use in
`ipython`_.
.. _`Gromacs`: http://www.gromacs.org
.. _`ipython`: http://ipython.scipy.org
Modules
-------
:mod:`gromacs`
The top level module contains all gromacs tools; each tool can be
run directly or queried for its documentation. It also defines
the root logger class (name *gromacs* by default).
:mod:`gromacs.config`
Configuration options. Not really used much at the moment.
:mod:`gromacs.cbook`
The Gromacs cook book contains typical applications of the tools. In many
cases this not more than just an often-used combination of parameters for
a tool.
# -*- coding: utf-8 -*-
import os, sys
import configparser
import warnings
#
# Look for a global .ini in the current directory. If none is
# there, raise an exception and exit. Look for a local .ini
# in the same directory. If that isn't present, issue a warning
# but carry on and use the global values
#
global_filepath = os.path.abspath("piwars.ini")
if not os.path.isfile(global_filepath):
warnings("No global ini found at %s" % global_filepath)
local_filepath = os.path.join(os.path.dirname(global_filepath), "piwars.local.ini")
if not os.path.isfile(local_filepath):
warnings.warn("No local ini found at %s" % local_filepath)
ini = configparser.ConfigParser()
ini.read([global_filepath, local_filepath])
#
# Since we already have code which expects to find a set of simple
# module constants, keep that approach alive. This does however preclude
# the easy possibility of a reload-while-running
#
LISTEN_ON_IP = ini["network"]["listen_on_ip"]
LISTEN_ON_PORT = ini["network"]["listen_on_port"]
PUBSUB_LISTEN_ON_IP = ini["pubsub"]["listen_on_ip"]
PUBSUB_LISTEN_ON_PORT = ini["pubsub"]["listen_on_port"]
CODEC = ini["i18n"]["codec"]
def which_file(cls, filename=None, deep=True):
"""
Which file is class method . List of files are the typical files able
to read by pyCSAMT softwares.
Sensitive class method.
Parameters
----------
**filename** :str
corresponding file to read , pathLike
**deep** : bool ,
control reading : False for just control the extension file ,
not opening file . True control in deeper file and
find which file were inputted.
Returns
---------
str
FileType could be [`avg` | `j` | `edi` | `resp` | `mesh` | `occamdat` |
`stn` | `model` | `iter` | `logfile` | `startup`]
List of files read by pyCSAMT :
============== =======================================================
CodeFile Description
============== =======================================================
*avg* Zonge Engineering file Plainty file of ASTATIC file.
*j* A.G .Jonhson J=Format file.
*edi* SEG (Society of Exploration Geophysics) Electrical
Data Interchange file (SEG-EDI)
*stn* Zonge Engineering station file
*occamdat* deGroot-Hedlin, C., and S. Constable, Occam file.
*mesh* Constable, S. C., R. L. Parker, and C. G. Constable
mesh file
*model* Occam Model file
*startup* Occam startup file
*iter* Occam iteration file get after Inversion
*resp* Occam response file , Get after inversion
*logfile* Occam Logfile, Get after inverson (Inversion file )
============== =======================================================
:Example:
>>> files = ['K1_exp.bln','LCS01.avg' ,'LCS01_2_to_1.avg', 'K1.stn',
... 'csi000.dat','csa250.edi','LogFile.logfile',
... 'Occam2DMesh','Occam2DModel', 'OccamDataFile.dat',
... 'S00_ss.edi', 'Startup','RESP13.resp',
... 'ITER02.iter']
>>> for ii in files :
>>> path = os.path.join(os.environ["pyCSAMT"],
... 'csamtpy','data', ii)
... try :
... print(_sensitive.which_file(path,deep=True))
... except :pass
"""
_code = {
'edi': cls._edi,
'j': cls._j,
'startup': cls._occam_startup,
'occamdat': cls._occam_datafile,
'model': cls._occam_modelfile,
'mesh': cls._occam_meshfile,
'iter': cls._occam_startup,
'avg': cls._avg,
'stn': cls._stn,
'logfile': cls._occam_logfile,
'resp': ['none', 'none'],
}
_filename = filename
if _filename is None:
pyCSAMTError_file_handling(
'Error file: NoneType can not be computed. Check your right path.'
)
if _filename is not None:
if os.path.basename(_filename).split('.')[-1].lower() in list(
_code.keys()): #code file recognized
_flag = os.path.basename(_filename).split('.')[-1].lower()
if deep == False: return _flag
else: _flag = 0 #file not recognized
# Open the file now
with open(_filename, 'r', encoding='utf8') as _f:
_data_lines = _f.readlines()
if _flag != 0:
# file extension has been recognized on dict code keys.
cls._logger.info('Reading %s file' % os.path.basename(_filename))
_value_code = _code[_flag]
if _flag == 'edi': #avoid expensive function then controle 2thing before continue
if _value_code[0] not in _data_lines[0]:
warnings.warn('File probably is incorrect. Please consult EDI_Main file components : {0}'.\
format(''.join(cls._edi)))
raise pyCSAMTError_file_handling(
"Wrong SEG-EDI file. It'seems -File provided doesnt include '>HEAD. Please provide the right EDI-FORMAT"
)
elif _value_code[-1] not in _data_lines[-1]:
warnings.warn('File probably incorrect. Please consult EDI_Main file composents : {0}'.\
format(''.join(cls._edi)))
raise pyCSAMTError_file_handling(
"Wrong SEG-EDI file. It'seems -File provided doesnt include '>END. Please provide the right EDI-FORMAT"
)
elif _flag == 'resp': # control quick response file
#check if the len of resp= 7
if len(_data_lines[0].strip().split()) != 7:
raise pyCSAMTError_file_handling(
"Wrong OCCAM-RESPONSE file. Please provide the right response file."
)
else:
return _flag
elif _flag == 'avg':
_reason = cls.validate_avg(avg_data_lines=_data_lines)[0]
if _reason not in ['yesAST', 'yes']:
warnings(
'File <{0}> does not match Zonge AVGfile. Get info to {1}'
.format(os.path.basename(_filename), notion.AVG))
raise pyCSAMTError_file_handling(
"Wrong <{0}>Zonge AVG-file. Please provide the right file."
.format(os.path.basename(_filename)))
return _flag
elif _flag == 'mesh':
try:
[float(ss) for ss in _data_lines[1].strip().split()
] #check the first occam layer
except:
warnings.warn(
'Wrong OCCAM-MESH file.Get more info on that site :https://marineemlab.ucsd.edu/Projects/Occam/index.html'
)
raise pyCSAMTError_file_handling("Wrong OCCAM-MESH <%s>file .We don't find the characteristic of thefirst layer."\
"Please provide the right OCCAM meshfile." % os.path.basename(_filename))
for _meshcodec in _value_code:
if _meshcodec in _data_lines[-1]: return _flag
else:
warnings.warn(
'Trouble occurs while reading the "OCCAM-params specs.More details in :{0}.\n {1}'
.format(notion.occam_mesh_parameter_specs_info,
notion.occam_mesh_parameter_specs_meaning))
raise pyCSAMTError_file_handling(
'We do not find a "Parameter specs" in your <{0}>'.
format(os.path.basename(_filename)))
#once both thing has already been controled . then continue . avoid avg because already has deep controlled
# with special static method then pass
_ccounter = 0 # threshold control is match to 7 except stn.
for _codec in _value_code: # loop the dict value of code #loop now all the
if _flag not in ['avg', 'resp', 'mesh']:
for num, _data_item in enumerate(_data_lines):
if _codec in _data_item:
_ccounter += 1
if _flag == 'stn':
if _ccounter >= 3: return _flag
elif _flag == 'j':
if _ccounter >= 5: return _flag
if _ccounter >= 7: return _flag
if _ccounter < 7: raise pyCSAMTError_file_handling('ERROR occurs while reading file !<{0}>. '\
'File doesnt not match the typical <{1}> Format.'.format(os.path.basename(_filename), _flag))
elif _flag == 0: #file not recognized in _codekeys ,
#then try to read and to find which file mastch the best.
_ccounter = 0
for _keycode, _value_code in _code.items():
for num, valueitem in enumerate(_data_lines):
for codec in _value_code: #read value in code
if codec.lower() in valueitem.lower():
_ccounter += 1
if _keycode == 'j':
if _ccounter >= 4: return _keycode
if _ccounter >= 7:
if _keycode == 'startup':
if all([
float(val)
for val in _data_lines[len(_value_code) +
1].strip().split()
]) == False:
return 'iter'
else:
return _keycode
return _keycode
#Now we assune that the file must be the response file then read according response control
try:
resp0 = [float(ss) for ss in _data_lines[0]]
resp_end = [float(ss) for ss in _data_lines[-1]]
resp_mid = [
float(ss) for ss in _data_lines[int(len(_data_lines) / 2)]
] # get the middele of file and try float converter
assert (len(resp0) == len(resp_end)) and (len(resp_end)==len(resp_mid)),\
pyCSAMTError_file_handling('We presume that RESP <{0}> file doesnt not match a OCCAM-RESPONSE file.'.format(os.path.basename(_filename)))
except:
message = ''.join(
'Error reading File. pyCSAMT can read only <{0}> Format file.',
'Format file. Program can not find the type of that file : <{1}>.',
'You may use script <rewriteXXX> of pyCSAMT to try to rewrite file',
'either to SEG-EDI |j|STN|AVG| or OCCAM{DAT, RESP,MODEL,ITER} files.'
)
cls._logger.error(
message.format('|'.join(list(_code.keys())),
os.path.basename(_filename)))
warnings.warn(
message.format('|'.join(list(_code.keys())),
os.path.basename(_filename)))
return
return 'resp'
def execute_method(methodName,
inGraph,
graphName,
distances=True,
distFunction="default",
methodParams="default"):
print "Executing " + methodName
method = method_dispatcher(methodName)
if methodName.startswith("panos_sim"):
if methodParams == "default" or methodParams == None:
signatures = method(inGraph, graphName)
else:
eigs, strategy, compressed, sigma = methodParams
signatures = method(inGraph, graphName, eigs, strategy, compressed,
sigma)
elif is_spectral(methodName):
if methodParams == "default" or methodParams == None:
signatures = method(inGraph, graphName)
else:
eigs, energies, strategy = methodParams
print "Using " + str(
eigs
) + " eigenvalues for a %d-dimensional embedding via the eigenvalue strategy \'%s\'" % (
energies, strategy)
signatures = method(inGraph, graphName, eigs, energies, strategy)
elif methodName == "refex_sim":
signatures = method(graphName)
elif methodName == "cycle_sim":
cycleLength, matrixType, keepEven, clearConverged = methodParams
if clearConverged and distances:
assert (distFunction == calc_emd)
signatures = method(inGraph, cycleLength, matrixType, keepEven,
clearConverged)
elif methodName in [
"sim_rank", "role_sim", "vertex_sim", "commute_time_dist"
]:
if distances == False: # These methods only return a distance per pair of nodes.
warnings('%s only provides a distance matrix.' % (methodName, ))
if methodName == "vertex_sim":
distanceMatrix = method(inGraph, dist=True)
elif methodName == "commute_time_dist":
distanceMatrix = method(inGraph)
else:
distanceMatrix = method(graphName)
distanceMatrix[abs(distanceMatrix) < 1e-9] = 0.0
# Safeguarding against floating point numerical errors.
return distanceMatrix
else:
assert (False)
if distances:
distanceMatrix = pairwise_distances_(signatures,
methodName,
distFunction=distFunction)
return distanceMatrix
else:
return signatures
def CommitNewContainer(self, containerName, commitmessage, authtoken,
BASE):
self.containerName = containerName
self.containerId = containerName
# self.tempFrame.description = self.descriptionText.toPlainText()
self.workingFrame.commitMessage = commitmessage
commitContainer = self.dictify()
commitFrame = self.workingFrame.dictify()
url = BASE + 'CONTAINERS/newContainer'
payload = {
'containerdictjson': json.dumps(commitContainer),
'framedictjson': json.dumps(commitFrame)
}
filesToUpload = {}
for fileheader, filetrack in self.workingFrame.filestrack.items():
if filetrack.style in [typeOutput, typeRequired]:
filepath = os.path.join(self.containerworkingfolder,
filetrack.file_name)
filesToUpload[fileheader] = open(filepath, 'rb')
fileb = open(filepath, 'rb')
filetrack.md5 = hashlib.md5(fileb.read()).hexdigest()
headers = {'Authorization': 'Bearer ' + authtoken['auth_token']}
response = requests.request("POST",
url,
headers=headers,
data=payload,
files=filesToUpload)
if 'Container Made' == response.headers['response']:
resp = response.json()
returncontdict = resp['containerdictjson']
returnframedict = resp['framedictjson']
self.allowedUser = returncontdict['allowedUser']
self.workingFrame.FrameInstanceId = returnframedict[
'FrameInstanceId']
self.workingFrame.commitMessage = returnframedict['commitMessage']
self.workingFrame.commitUTCdatetime = returnframedict[
'commitUTCdatetime']
for filetrack in returnframedict['filestrack']:
fileheader = filetrack['FileHeader']
self.workingFrame.filestrack[
fileheader].commitUTCdatetime = filetrack[
'commitUTCdatetime']
if not self.workingFrame.filestrack[
fileheader].md5 == filetrack['md5']:
warnings('MD5 changed')
self.workingFrame.filestrack[
fileheader].committedby = filetrack['committedby']
self.workingFrame.filestrack[fileheader].file_id = filetrack[
'file_id']
frameyamlfn = os.path.join(self.containerworkingfolder,
self.currentbranch,
self.workingFrame.FrameName + '.yaml')
self.workingFrame.writeoutFrameYaml(frameyamlfn)
self.save()
return True
else:
return False
from enchant.errors import *
from enchant.utils import EnchantStr, get_default_language
from enchant.pypwl import PyPWL
# Due to the unfortunate name collision between the enchant "tokenize" module
# and the stdlib "tokenize" module, certain values of sys.path can cause
# the former to override the latter and break the "warnings" module.
# This hacks around it by making a dummy "warnings" module.
try:
import warnings
except ImportError:
class warnings(object):
def warn(self,*args,**kwds):
pass
warnings = warnings()
class ProviderDesc(object):
"""Simple class describing an Enchant provider.
Each provider has the following information associated with it:
* name: Internal provider name (e.g. "aspell")
* desc: Human-readable description (e.g. "Aspell Provider")
* file: Location of the library containing the provider
"""
_DOC_ERRORS = ["desc"]
def __init__(self,name,desc,file):
def copy(self):
warnings(NotImplemented)
return self
