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Description:
def get_a(values, n):
"""Extract the independent variables of the given values and return them as a matrix with n columns in a form suitable for the least squares approach applied in method |ARMA.update_ar_coefs|. """ |
m = len(values)-n
a = numpy.empty((m, n), dtype=float)
for i in range(m):
i0 = i-1 if i > 0 else None
i1 = i+n-1
a[i] = values[i1:i0:-1]
return numpy.array(a) |
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def update_ma_coefs(self):
"""Determine the MA coefficients. The number of MA coefficients is subsequently increased until the required precision |ARMA.max_dev_coefs| is reached. Otherwise, a |RuntimeError| is raised. """ |
self.ma_coefs = []
for ma_order in range(1, self.ma.order+1):
self.calc_next_ma_coef(ma_order, self.ma)
if self.dev_coefs < self.max_dev_coefs:
self.norm_coefs()
break
else:
with hydpy.pub.options.reprdigits(12):
raise RuntimeError(
f'Method `update_ma_coefs` is not able to determine the '
f'MA coefficients of the ARMA model with the desired '
f'accuracy. You can set the tolerance value '
f'´max_dev_coefs` to a higher value. An accuracy of '
f'`{objecttools.repr_(self.dev_coefs)}` has been reached '
f'using `{self.ma.order}` MA coefficients.')
if numpy.min(self.response) < 0.:
warnings.warn(
'Note that the smallest response to a standard impulse of the '
'determined ARMA model is negative (`%s`).'
% objecttools.repr_(numpy.min(self.response))) |
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def calc_next_ma_coef(self, ma_order, ma_model):
"""Determine the MA coefficients of the ARMA model based on its predetermined AR coefficients and the MA ordinates of the given |MA| model. The MA coefficients are determined one at a time, beginning with the first one. Each ARMA MA coefficient in set in a manner that allows for the exact reproduction of the equivalent pure MA coefficient with all relevant ARMA coefficients. """ |
idx = ma_order-1
coef = ma_model.coefs[idx]
for jdx, ar_coef in enumerate(self.ar_coefs):
zdx = idx-jdx-1
if zdx >= 0:
coef -= ar_coef*ma_model.coefs[zdx]
self.ma_coefs = numpy.concatenate((self.ma_coefs, [coef])) |
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def response(self):
"""Return the response to a standard dt impulse.""" |
values = []
sum_values = 0.
ma_coefs = self.ma_coefs
ar_coefs = self.ar_coefs
ma_order = self.ma_order
for idx in range(len(self.ma.delays)):
value = 0.
if idx < ma_order:
value += ma_coefs[idx]
for jdx, ar_coef in enumerate(ar_coefs):
zdx = idx-jdx-1
if zdx >= 0:
value += ar_coef*values[zdx]
values.append(value)
sum_values += value
return numpy.array(values) |
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def moments(self):
"""The first two time delay weighted statistical moments of the ARMA response.""" |
timepoints = self.ma.delays
response = self.response
moment1 = statstools.calc_mean_time(timepoints, response)
moment2 = statstools.calc_mean_time_deviation(
timepoints, response, moment1)
return numpy.array([moment1, moment2]) |
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def plot(self, threshold=None, **kwargs):
"""Barplot of the ARMA response.""" |
try:
# Works under matplotlib 3.
pyplot.bar(x=self.ma.delays+.5, height=self.response,
width=1., fill=False, **kwargs)
except TypeError: # pragma: no cover
# Works under matplotlib 2.
pyplot.bar(left=self.ma.delays+.5, height=self.response,
width=1., fill=False, **kwargs)
pyplot.xlabel('time')
pyplot.ylabel('response')
if threshold is not None:
cumsum = numpy.cumsum(self.response)
idx = numpy.where(cumsum > threshold*cumsum[-1])[0][0]
pyplot.xlim(0., idx) |
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def method_header(method_name, nogil=False, idx_as_arg=False):
"""Returns the Cython method header for methods without arguments except `self`.""" |
if not config.FASTCYTHON:
nogil = False
header = 'cpdef inline void %s(self' % method_name
header += ', int idx)' if idx_as_arg else ')'
header += ' nogil:' if nogil else ':'
return header |
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def decorate_method(wrapped):
"""The decorated method will return a |Lines| object including a method header. However, the |Lines| object will be empty if the respective model does not implement a method with the same name as the wrapped method. """ |
def wrapper(self):
lines = Lines()
if hasattr(self.model, wrapped.__name__):
print(' . %s' % wrapped.__name__)
lines.add(1, method_header(wrapped.__name__, nogil=True))
for line in wrapped(self):
lines.add(2, line)
return lines
functools.update_wrapper(wrapper, wrapped)
wrapper.__doc__ = 'Lines of model method %s.' % wrapped.__name__
return property(wrapper) |
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def add(self, indent, line):
"""Appends the given text line with prefixed spaces in accordance with the given number of indentation levels. """ |
if isinstance(line, str):
list.append(self, indent*4*' ' + line)
else:
for subline in line:
list.append(self, indent*4*' ' + subline) |
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def pyname(self):
"""Name of the compiled module.""" |
if self.pymodule.endswith('__init__'):
return self.pymodule.split('.')[-2]
else:
return self.pymodule.split('.')[-1] |
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def pyxwriter(self):
"""Update the pyx file.""" |
model = self.Model()
if hasattr(self, 'Parameters'):
model.parameters = self.Parameters(vars(self))
else:
model.parameters = parametertools.Parameters(vars(self))
if hasattr(self, 'Sequences'):
model.sequences = self.Sequences(model=model, **vars(self))
else:
model.sequences = sequencetools.Sequences(model=model,
**vars(self))
return PyxWriter(self, model, self.pyxfilepath) |
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def pysourcefiles(self):
"""All source files of the actual models Python classes and their respective base classes.""" |
sourcefiles = set()
for (name, child) in vars(self).items():
try:
parents = inspect.getmro(child)
except AttributeError:
continue
for parent in parents:
try:
sourcefile = inspect.getfile(parent)
except TypeError:
break
sourcefiles.add(sourcefile)
return Lines(*sourcefiles) |
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def outdated(self):
"""True if at least one of the |Cythonizer.pysourcefiles| is newer than the compiled file under |Cythonizer.pyxfilepath|, otherwise False. """ |
if hydpy.pub.options.forcecompiling:
return True
if os.path.split(hydpy.__path__[0])[-2].endswith('-packages'):
return False
if not os.path.exists(self.dllfilepath):
return True
cydate = os.stat(self.dllfilepath).st_mtime
for pysourcefile in self.pysourcefiles:
pydate = os.stat(pysourcefile).st_mtime
if pydate > cydate:
return True
return False |
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def compile_(self):
"""Translate cython code to C code and compile it.""" |
from Cython import Build
argv = copy.deepcopy(sys.argv)
sys.argv = [sys.argv[0], 'build_ext', '--build-lib='+self.buildpath]
exc_modules = [
distutils.extension.Extension(
'hydpy.cythons.autogen.'+self.cyname,
[self.pyxfilepath], extra_compile_args=['-O2'])]
distutils.core.setup(ext_modules=Build.cythonize(exc_modules),
include_dirs=[numpy.get_include()])
sys.argv = argv |
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def move_dll(self):
"""Try to find the resulting dll file and to move it into the `cythons` package. Things to be aware of: * The file extension either `pyd` (Window) or `so` (Linux). * The folder containing the dll file is system dependent, but is always a subfolder of the `cythons` package. * Under Linux, the filename might contain system information, e.g. """ |
dirinfos = os.walk(self.buildpath)
next(dirinfos)
system_dependent_filename = None
for dirinfo in dirinfos:
for filename in dirinfo[2]:
if (filename.startswith(self.cyname) and
filename.endswith(dllextension)):
system_dependent_filename = filename
break
if system_dependent_filename:
try:
shutil.move(os.path.join(dirinfo[0],
system_dependent_filename),
os.path.join(self.cydirpath,
self.cyname+dllextension))
break
except BaseException:
prefix = ('After trying to cythonize module %s, when '
'trying to move the final cython module %s '
'from directory %s to directory %s'
% (self.pyname, system_dependent_filename,
self.buildpath, self.cydirpath))
suffix = ('A likely error cause is that the cython module '
'%s does already exist in this directory and is '
'currently blocked by another Python process. '
'Maybe it helps to close all Python processes '
'and restart the cyhonization afterwards.'
% self.cyname+dllextension)
objecttools.augment_excmessage(prefix, suffix)
else:
raise IOError('After trying to cythonize module %s, the resulting '
'file %s could neither be found in directory %s nor '
'its subdirectories. The distul report should tell '
'whether the file has been stored somewhere else,'
'is named somehow else, or could not be build at '
'all.' % self.buildpath) |
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def constants(self):
"""Constants declaration lines.""" |
lines = Lines()
for (name, member) in vars(self.cythonizer).items():
if (name.isupper() and
(not inspect.isclass(member)) and
(type(member) in TYPE2STR)):
ndim = numpy.array(member).ndim
ctype = TYPE2STR[type(member)] + NDIM2STR[ndim]
lines.add(0, 'cdef public %s %s = %s'
% (ctype, name, member))
return lines |
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def parameters(self):
"""Parameter declaration lines.""" |
lines = Lines()
lines.add(0, '@cython.final')
lines.add(0, 'cdef class Parameters(object):')
for subpars in self.model.parameters:
if subpars:
lines.add(1, 'cdef public %s %s'
% (objecttools.classname(subpars), subpars.name))
for subpars in self.model.parameters:
if subpars:
print(' - %s' % subpars.name)
lines.add(0, '@cython.final')
lines.add(0, 'cdef class %s(object):'
% objecttools.classname(subpars))
for par in subpars:
try:
ctype = TYPE2STR[par.TYPE] + NDIM2STR[par.NDIM]
except KeyError:
ctype = par.TYPE + NDIM2STR[par.NDIM]
lines.add(1, 'cdef public %s %s' % (ctype, par.name))
return lines |
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def iosequence(seq):
"""Special declaration lines for the given |IOSequence| object. """ |
lines = Lines()
lines.add(1, 'cdef public bint _%s_diskflag' % seq.name)
lines.add(1, 'cdef public str _%s_path' % seq.name)
lines.add(1, 'cdef FILE *_%s_file' % seq.name)
lines.add(1, 'cdef public bint _%s_ramflag' % seq.name)
ctype = 'double' + NDIM2STR[seq.NDIM+1]
lines.add(1, 'cdef public %s _%s_array' % (ctype, seq.name))
return lines |
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def open_files(subseqs):
"""Open file statements.""" |
print(' . open_files')
lines = Lines()
lines.add(1, 'cpdef open_files(self, int idx):')
for seq in subseqs:
lines.add(2, 'if self._%s_diskflag:' % seq.name)
lines.add(3, 'self._%s_file = fopen(str(self._%s_path).encode(), '
'"rb+")' % (2*(seq.name,)))
if seq.NDIM == 0:
lines.add(3,
'fseek(self._%s_file, idx*8, SEEK_SET)' % seq.name)
else:
lines.add(3, 'fseek(self._%s_file, idx*self._%s_length*8, '
'SEEK_SET)' % (2*(seq.name,)))
return lines |
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def close_files(subseqs):
"""Close file statements.""" |
print(' . close_files')
lines = Lines()
lines.add(1, 'cpdef inline close_files(self):')
for seq in subseqs:
lines.add(2, 'if self._%s_diskflag:' % seq.name)
lines.add(3, 'fclose(self._%s_file)' % seq.name)
return lines |
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def load_data(subseqs):
"""Load data statements.""" |
print(' . load_data')
lines = Lines()
lines.add(1, 'cpdef inline void load_data(self, int idx) %s:' % _nogil)
lines.add(2, 'cdef int jdx0, jdx1, jdx2, jdx3, jdx4, jdx5')
for seq in subseqs:
lines.add(2, 'if self._%s_diskflag:' % seq.name)
if seq.NDIM == 0:
lines.add(3, 'fread(&self.%s, 8, 1, self._%s_file)'
% (2*(seq.name,)))
else:
lines.add(3, 'fread(&self.%s[0], 8, self._%s_length, '
'self._%s_file)' % (3*(seq.name,)))
lines.add(2, 'elif self._%s_ramflag:' % seq.name)
if seq.NDIM == 0:
lines.add(3, 'self.%s = self._%s_array[idx]' % (2*(seq.name,)))
else:
indexing = ''
for idx in range(seq.NDIM):
lines.add(3+idx, 'for jdx%d in range(self._%s_length_%d):'
% (idx, seq.name, idx))
indexing += 'jdx%d,' % idx
indexing = indexing[:-1]
lines.add(3+seq.NDIM, 'self.%s[%s] = self._%s_array[idx,%s]'
% (2*(seq.name, indexing)))
return lines |
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def set_pointer(self, subseqs):
"""Set_pointer functions for link sequences.""" |
lines = Lines()
for seq in subseqs:
if seq.NDIM == 0:
lines.extend(self.set_pointer0d(subseqs))
break
for seq in subseqs:
if seq.NDIM == 1:
lines.extend(self.alloc(subseqs))
lines.extend(self.dealloc(subseqs))
lines.extend(self.set_pointer1d(subseqs))
break
return lines |
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def set_pointer0d(subseqs):
"""Set_pointer function for 0-dimensional link sequences.""" |
print(' . set_pointer0d')
lines = Lines()
lines.add(1, 'cpdef inline set_pointer0d'
'(self, str name, pointerutils.PDouble value):')
for seq in subseqs:
lines.add(2, 'if name == "%s":' % seq.name)
lines.add(3, 'self.%s = value.p_value' % seq.name)
return lines |
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def alloc(subseqs):
"""Allocate memory for 1-dimensional link sequences.""" |
print(' . setlength')
lines = Lines()
lines.add(1, 'cpdef inline alloc(self, name, int length):')
for seq in subseqs:
lines.add(2, 'if name == "%s":' % seq.name)
lines.add(3, 'self._%s_length_0 = length' % seq.name)
lines.add(3, 'self.%s = <double**> '
'PyMem_Malloc(length * sizeof(double*))' % seq.name)
return lines |
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def dealloc(subseqs):
"""Deallocate memory for 1-dimensional link sequences.""" |
print(' . dealloc')
lines = Lines()
lines.add(1, 'cpdef inline dealloc(self):')
for seq in subseqs:
lines.add(2, 'PyMem_Free(self.%s)' % seq.name)
return lines |
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def set_pointer1d(subseqs):
"""Set_pointer function for 1-dimensional link sequences.""" |
print(' . set_pointer1d')
lines = Lines()
lines.add(1, 'cpdef inline set_pointer1d'
'(self, str name, pointerutils.PDouble value, int idx):')
for seq in subseqs:
lines.add(2, 'if name == "%s":' % seq.name)
lines.add(3, 'self.%s[idx] = value.p_value' % seq.name)
return lines |
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def numericalparameters(self):
"""Numeric parameter declaration lines.""" |
lines = Lines()
if self.model.NUMERICAL:
lines.add(0, '@cython.final')
lines.add(0, 'cdef class NumConsts(object):')
for name in ('nmb_methods', 'nmb_stages'):
lines.add(1, 'cdef public %s %s' % (TYPE2STR[int], name))
for name in ('dt_increase', 'dt_decrease'):
lines.add(1, 'cdef public %s %s' % (TYPE2STR[float], name))
lines.add(1, 'cdef public configutils.Config pub')
lines.add(1, 'cdef public double[:, :, :] a_coefs')
lines.add(0, 'cdef class NumVars(object):')
for name in ('nmb_calls', 'idx_method', 'idx_stage'):
lines.add(1, 'cdef public %s %s' % (TYPE2STR[int], name))
for name in ('t0', 't1', 'dt', 'dt_est',
'error', 'last_error', 'extrapolated_error'):
lines.add(1, 'cdef public %s %s' % (TYPE2STR[float], name))
lines.add(1, 'cdef public %s f0_ready' % TYPE2STR[bool])
return lines |
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def modeldeclarations(self):
"""Attribute declarations of the model class.""" |
lines = Lines()
lines.add(0, '@cython.final')
lines.add(0, 'cdef class Model(object):')
lines.add(1, 'cdef public int idx_sim')
lines.add(1, 'cdef public Parameters parameters')
lines.add(1, 'cdef public Sequences sequences')
if hasattr(self.model, 'numconsts'):
lines.add(1, 'cdef public NumConsts numconsts')
if hasattr(self.model, 'numvars'):
lines.add(1, 'cdef public NumVars numvars')
return lines |
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def modelstandardfunctions(self):
"""Standard functions of the model class.""" |
lines = Lines()
lines.extend(self.doit)
lines.extend(self.iofunctions)
lines.extend(self.new2old)
lines.extend(self.run)
lines.extend(self.update_inlets)
lines.extend(self.update_outlets)
lines.extend(self.update_receivers)
lines.extend(self.update_senders)
return lines |
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def modelnumericfunctions(self):
"""Numerical functions of the model class.""" |
lines = Lines()
lines.extend(self.solve)
lines.extend(self.calculate_single_terms)
lines.extend(self.calculate_full_terms)
lines.extend(self.get_point_states)
lines.extend(self.set_point_states)
lines.extend(self.set_result_states)
lines.extend(self.get_sum_fluxes)
lines.extend(self.set_point_fluxes)
lines.extend(self.set_result_fluxes)
lines.extend(self.integrate_fluxes)
lines.extend(self.reset_sum_fluxes)
lines.extend(self.addup_fluxes)
lines.extend(self.calculate_error)
lines.extend(self.extrapolate_error)
return lines |
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def calculate_single_terms(self):
"""Lines of model method with the same name.""" |
lines = self._call_methods('calculate_single_terms',
self.model.PART_ODE_METHODS)
if lines:
lines.insert(1, (' self.numvars.nmb_calls ='
'self.numvars.nmb_calls+1'))
return lines |
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def listofmodeluserfunctions(self):
"""User functions of the model class.""" |
lines = []
for (name, member) in vars(self.model.__class__).items():
if (inspect.isfunction(member) and
(name not in ('run', 'new2old')) and
('fastaccess' in inspect.getsource(member))):
lines.append((name, member))
run = vars(self.model.__class__).get('run')
if run is not None:
lines.append(('run', run))
for (name, member) in vars(self.model).items():
if (inspect.ismethod(member) and
('fastaccess' in inspect.getsource(member))):
lines.append((name, member))
return lines |
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def remove_linebreaks_within_equations(code):
r"""Remove line breaks within equations. This is not a exhaustive test, but shows how the method works: 'asdf = (a+b)' """ |
code = code.replace('\\\n', '')
chars = []
counter = 0
for char in code:
if char in ('(', '[', '{'):
counter += 1
elif char in (')', ']', '}'):
counter -= 1
if not (counter and (char == '\n')):
chars.append(char)
return ''.join(chars) |
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def remove_imath_operators(lines):
"""Remove mathematical expressions that require Pythons global interpreter locking mechanism. This is not a exhaustive test, but shows how the method works: [' x = x + (1*1)'] """ |
for idx, line in enumerate(lines):
for operator in ('+=', '-=', '**=', '*=', '//=', '/=', '%='):
sublines = line.split(operator)
if len(sublines) > 1:
indent = line.count(' ') - line.lstrip().count(' ')
sublines = [sl.strip() for sl in sublines]
line = ('%s%s = %s %s (%s)'
% (indent*' ', sublines[0], sublines[0],
operator[:-1], sublines[1]))
lines[idx] = line |
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def pyxlines(self):
"""Cython code lines. Assumptions: * Function shall be a method * Method shall be inlined * Method returns nothing * Method arguments are of type `int` (except self) * Local variables are generally of type `int` but of type `double` when their name starts with `d_` """ |
lines = [' '+line for line in self.cleanlines]
lines[0] = lines[0].replace('def ', 'cpdef inline void ')
lines[0] = lines[0].replace('):', ') %s:' % _nogil)
for name in self.untypedarguments:
lines[0] = lines[0].replace(', %s ' % name, ', int %s ' % name)
lines[0] = lines[0].replace(', %s)' % name, ', int %s)' % name)
for name in self.untypedinternalvarnames:
if name.startswith('d_'):
lines.insert(1, ' cdef double ' + name)
else:
lines.insert(1, ' cdef int ' + name)
return Lines(*lines) |
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def calc_smoothpar_logistic2(metapar):
"""Return the smoothing parameter corresponding to the given meta parameter when using |smooth_logistic2|. Calculate the smoothing parameter value corresponding the meta parameter value 2.5: Using this smoothing parameter value, the output of function |smooth_logistic2| differs by 1 % from the related `true` discontinuous step function for the input values -2.5 and 2.5 (which are located at a distance of 2.5 from the position of the discontinuity):
0.01 2.51 For zero or negative meta parameter values, a zero smoothing parameter value is returned: 0.0 0.0 """ |
if metapar <= 0.:
return 0.
return optimize.newton(_error_smoothpar_logistic2,
.3 * metapar**.84,
_smooth_logistic2_derivative,
args=(metapar,)) |
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def from_cfunits(cls, units) -> 'Date': """Return a |Date| object representing the reference date of the given `units` string agreeing with the NetCDF-CF conventions. The following example string is taken from the `Time Coordinate`_ chapter of the NetCDF-CF conventions documentation (modified). Note that the first entry (the unit) is ignored: Date('1992-10-08 22:15:42') Date('1992-10-08 15:15:00') Date('1992-10-08 07:00:00') Date('1992-10-08 00:00:00') Without modification, when "0" is included as the decimal fractions of a second, the example string from `Time Coordinate`_ can also be passed. However, fractions different from "0" result in an error: Date('1992-10-08 15:15:42') Date('1992-10-08 15:15:42') Date('1992-10-08 22:15:42') Date('1992-10-08 22:15:42') Traceback (most recent call last):
ValueError: While trying to parse the date of the NetCDF-CF "units" \ string `seconds since 1992-10-8 15:15:42.005 -6:00`, the following error \ occurred: No other decimal fraction of a second than "0" allowed. """ |
try:
string = units[units.find('since')+6:]
idx = string.find('.')
if idx != -1:
jdx = None
for jdx, char in enumerate(string[idx+1:]):
if not char.isnumeric():
break
if char != '0':
raise ValueError(
'No other decimal fraction of a second '
'than "0" allowed.')
else:
if jdx is None:
jdx = idx+1
else:
jdx += 1
string = f'{string[:idx]}{string[idx+jdx+1:]}'
return cls(string)
except BaseException:
objecttools.augment_excmessage(
f'While trying to parse the date of the NetCDF-CF "units" '
f'string `{units}`') |
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def to_cfunits(self, unit='hours', utcoffset=None):
"""Return a `units` string agreeing with the NetCDF-CF conventions. By default, |Date.to_cfunits| takes `hours` as time unit, and the the actual value of |Options.utcoffset| as time zone information: 'hours since 1992-10-08 15:15:42 +01:00' Other time units are allowed (no checks are performed, so select something useful):
'minutes since 1992-10-08 15:15:42 +01:00' For changing the time zone, pass the corresponding offset in minutes: 'sec since 1992-10-08 13:15:42 -01:00' """ |
if utcoffset is None:
utcoffset = hydpy.pub.options.utcoffset
string = self.to_string('iso2', utcoffset)
string = ' '.join((string[:-6], string[-6:]))
return f'{unit} since {string}' |
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def _set_thing(self, thing, value):
|
try:
value = int(value)
except (TypeError, ValueError):
raise TypeError(
f'Changing the {thing} of a `Date` instance is only '
f'allowed via numbers, but the given value `{value}` '
f'is of type `{type(value)}` instead.')
kwargs = {}
for unit in ('year', 'month', 'day', 'hour', 'minute', 'second'):
kwargs[unit] = getattr(self, unit)
kwargs[thing] = value
self.datetime = datetime.datetime(**kwargs) |
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def wateryear(self):
"""The actual hydrological year according to the selected reference month. The reference mont reference |Date.refmonth| defaults to November: 1996 1997 Note that changing |Date.refmonth| affects all |Date| objects: 1997 1997 1996 1997 """ |
if self.month < self._firstmonth_wateryear:
return self.year
return self.year + 1 |
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def fromseconds(cls, seconds):
"""Return a |Period| instance based on a given number of seconds.""" |
try:
seconds = int(seconds)
except TypeError:
seconds = int(seconds.flatten()[0])
return cls(datetime.timedelta(0, int(seconds))) |
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def _guessunit(self):
"""Guess the unit of the period as the largest one, which results in an integer duration. """ |
if not self.days % 1:
return 'd'
elif not self.hours % 1:
return 'h'
elif not self.minutes % 1:
return 'm'
elif not self.seconds % 1:
return 's'
else:
raise ValueError(
'The stepsize is not a multiple of one '
'second, which is not allowed.') |
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def from_array(cls, array):
"""Returns a |Timegrid| instance based on two date and one period information stored in the first 13 rows of a |numpy.ndarray| object. """ |
try:
return cls(Date.from_array(array[:6]),
Date.from_array(array[6:12]),
Period.fromseconds(array[12]))
except IndexError:
raise IndexError(
f'To define a Timegrid instance via an array, 13 '
f'numbers are required. However, the given array '
f'consist of {len(array)} entries/rows only.') |
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def to_array(self):
"""Returns a 1-dimensional |numpy| |numpy.ndarray| with thirteen entries first defining the start date, secondly defining the end date and thirdly the step size in seconds. """ |
values = numpy.empty(13, dtype=float)
values[:6] = self.firstdate.to_array()
values[6:12] = self.lastdate.to_array()
values[12] = self.stepsize.seconds
return values |
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def from_timepoints(cls, timepoints, refdate, unit='hours'):
"""Return a |Timegrid| object representing the given starting `timepoints` in relation to the given `refdate`. The following examples identical with the ones of |Timegrid.to_timepoints| but reversed. At least two given time points must be increasing and equidistant. By default, they are assumed in hours since the given reference date: Timegrid('01.01.2000 00:00:00', '02.01.2000 00:00:00', '6h') Timegrid('2000-01-01 00:00:00', '2000-01-02 00:00:00', '6h') Other time units (`days` or `min`) must be passed explicitely (only the first character counts):
Timegrid('01.01.2000 00:00:00', '02.01.2000 00:00:00', '6h') Timegrid('2000-01-01 00:00:00', '2000-01-02 00:00:00', '6h') """ |
refdate = Date(refdate)
unit = Period.from_cfunits(unit)
delta = timepoints[1]-timepoints[0]
firstdate = refdate+timepoints[0]*unit
lastdate = refdate+(timepoints[-1]+delta)*unit
stepsize = (lastdate-firstdate)/len(timepoints)
return cls(firstdate, lastdate, stepsize) |
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def to_timepoints(self, unit='hours', offset=None):
"""Return an |numpy.ndarray| representing the starting time points of the |Timegrid| object. The following examples identical with the ones of |Timegrid.from_timepoints| but reversed. By default, the time points are given in hours: array([ 0., 6., 12., 18.]) Other time units (`days` or `min`) can be defined (only the first character counts):
array([ 0. , 0.25, 0.5 , 0.75]) Additionally, one can pass an `offset` that must be of type |int| or an valid |Period| initialization argument: array([ 24., 30., 36., 42.]) array([ 24., 30., 36., 42.]) array([ 1. , 1.25, 1.5 , 1.75]) """ |
unit = Period.from_cfunits(unit)
if offset is None:
offset = 0.
else:
try:
offset = Period(offset)/unit
except TypeError:
offset = offset
step = self.stepsize/unit
nmb = len(self)
variable = numpy.linspace(offset, offset+step*(nmb-1), nmb)
return variable |
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def array2series(self, array):
"""Prefix the information of the actual Timegrid object to the given array and return it. The Timegrid information is stored in the first thirteen values of the first axis of the returned series. Initialize a Timegrid object and apply its `array2series` method on a simple list containing numbers: The first six entries contain the first date of the timegrid (year, month, day, hour, minute, second):
2000.0, 11.0, 1.0, 0.0, 0.0, 0.0 The six subsequent entries contain the last date: 2000.0, 11.0, 1.0, 4.0, 0.0, 0.0 The thirteens value is the step size in seconds: 3600.0 The last four value are the ones of the given vector: 1.0, 2.0, 3.5, 5.0 The given array can have an arbitrary number of dimensions: Now the timegrid information is stored in the first column: 2000.0, 11.0, 1.0, 0.0, 0.0, 0.0, 2000.0, 11.0, 1.0, 4.0, 0.0, 0.0, \ 3600.0 All other columns of the first thirteen rows contain nan values, e.g.: 3600.0, nan, nan, nan The original values are stored in the last four rows, e.g.: 1.0, 0.0, 0.0, 0.0 Inappropriate array objects result in error messages like: Traceback (most recent call last):
ValueError: While trying to prefix timegrid information to the given \ array, the following error occurred: setting an array element with a sequence. If the given array does not fit to the defined timegrid, a special error message is returned: Traceback (most recent call last):
ValueError: When converting an array to a sequence, the lengths of \ the timegrid and the given array must be equal, but the length of the \ timegrid object is `4` and the length of the array object is `2`. """ |
try:
array = numpy.array(array, dtype=float)
except BaseException:
objecttools.augment_excmessage(
'While trying to prefix timegrid information to the '
'given array')
if len(array) != len(self):
raise ValueError(
f'When converting an array to a sequence, the lengths of the '
f'timegrid and the given array must be equal, but the length '
f'of the timegrid object is `{len(self)}` and the length of '
f'the array object is `{len(array)}`.')
shape = list(array.shape)
shape[0] += 13
series = numpy.full(shape, numpy.nan)
slices = [slice(0, 13)]
subshape = [13]
for dummy in range(1, series.ndim):
slices.append(slice(0, 1))
subshape.append(1)
series[tuple(slices)] = self.to_array().reshape(subshape)
series[13:] = array
return series |
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def verify(self):
"""Raise an |ValueError| if the dates or the step size of the time frame are inconsistent. """ |
if self.firstdate >= self.lastdate:
raise ValueError(
f'Unplausible timegrid. The first given date '
f'{self.firstdate}, the second given date is {self.lastdate}.')
if (self.lastdate-self.firstdate) % self.stepsize:
raise ValueError(
f'Unplausible timegrid. The period span between the given '
f'dates {self.firstdate} and {self.lastdate} is not '
f'a multiple of the given step size {self.stepsize}.') |
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def assignrepr(self, prefix, style=None, utcoffset=None):
"""Return a |repr| string with an prefixed assignement. Without option arguments given, printing the returned string looks like: timegrid = Timegrid('1996-11-01 00:00:00', '1997-11-01 00:00:00', '1d') The optional arguments are passed to method |Date.to_repr| without any modifications: Timegrid('1996-11-01T01:00:00+02:00', '1997-11-01T01:00:00+02:00', '1d') """ |
skip = len(prefix) + 9
blanks = ' ' * skip
return (f"{prefix}Timegrid('"
f"{self.firstdate.to_string(style, utcoffset)}',\n"
f"{blanks}'{self.lastdate.to_string(style, utcoffset)}',\n"
f"{blanks}'{str(self.stepsize)}')") |
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def verify(self):
"""Raise an |ValueError| it the different time grids are inconsistent.""" |
self.init.verify()
self.sim.verify()
if self.init.firstdate > self.sim.firstdate:
raise ValueError(
f'The first date of the initialisation period '
f'({self.init.firstdate}) must not be later '
f'than the first date of the simulation period '
f'({self.sim.firstdate}).')
elif self.init.lastdate < self.sim.lastdate:
raise ValueError(
f'The last date of the initialisation period '
f'({self.init.lastdate}) must not be earlier '
f'than the last date of the simulation period '
f'({self.sim.lastdate}).')
elif self.init.stepsize != self.sim.stepsize:
raise ValueError(
f'The initialization stepsize ({self.init.stepsize}) '
f'must be identical with the simulation stepsize '
f'({self.sim.stepsize}).')
else:
try:
self.init[self.sim.firstdate]
except ValueError:
raise ValueError(
'The simulation time grid is not properly '
'alligned on the initialization time grid.') |
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def seconds_passed(self):
"""Amount of time passed in seconds since the beginning of the year. In the first example, the year is only one minute and thirty seconds old: 90 The second example shows that the 29th February is generally included: 5184000 """ |
return int((Date(self).datetime -
self._STARTDATE.datetime).total_seconds()) |
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def seconds_left(self):
"""Remaining part of the year in seconds. In the first example, only one minute and thirty seconds of the year remain: 90 The second example shows that the 29th February is generally included: 28944000 """ |
return int((self._ENDDATE.datetime -
Date(self).datetime).total_seconds()) |
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def centred_timegrid(cls, simulationstep):
"""Return a |Timegrid| object defining the central time points of the year 2000 for the given simulation step. Timegrid('2000-01-01 12:00:00', '2001-01-01 12:00:00', '1d') """ |
simulationstep = Period(simulationstep)
return Timegrid(
cls._STARTDATE+simulationstep/2,
cls._ENDDATE+simulationstep/2,
simulationstep) |
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def dir_(self):
"""The prefered way for HydPy objects to respond to |dir|. Note the depencence on the `pub.options.dirverbose`. If this option is set `True`, all attributes and methods of the given instance and its class (including those inherited from the parent classes) are returned: True If the option is set to `False`, only the `public` attributes and methods (which do need begin with `_`) are returned: ['only_public_attribute'] If none of those does exists, |dir_| returns a list with a single string containing a single empty space (which seems to work better for most IDEs than returning an emtpy list):
[' '] """ |
names = set()
for thing in list(inspect.getmro(type(self))) + [self]:
for key in vars(thing).keys():
if hydpy.pub.options.dirverbose or not key.startswith('_'):
names.add(key)
if names:
names = list(names)
else:
names = [' ']
return names |
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def classname(self):
"""Return the class name of the given instance object or class. float Options """ |
if inspect.isclass(self):
string = str(self)
else:
string = str(type(self))
try:
string = string.split("'")[1]
except IndexError:
pass
return string.split('.')[-1] |
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def name(self):
"""Name of the class of the given instance in lower case letters. This function is thought to be implemented as a property. Otherwise it would violate the principle not to access or manipulate private attributes ("_name"):
'test' 'test' The private attribute is added for performance reasons only. Note that it is a class attribute: 'test' """ |
cls = type(self)
try:
return cls.__dict__['_name']
except KeyError:
setattr(cls, '_name', instancename(self))
return cls.__dict__['_name'] |
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def valid_variable_identifier(string):
"""Raises an |ValueError| if the given name is not a valid Python identifier. Traceback (most recent call last):
ValueError: The given name string `test 1` does not define a valid \ variable identifier. Valid identifiers do not contain characters like \ `-` or empty spaces, do not start with numbers, cannot be mistaken with \ Also, names of Python built ins are not allowed: Traceback (most recent call last):
""" |
string = str(string)
try:
exec('%s = None' % string)
if string in dir(builtins):
raise SyntaxError()
except SyntaxError:
raise ValueError(
'The given name string `%s` does not define a valid variable '
'identifier. Valid identifiers do not contain characters like '
'`-` or empty spaces, do not start with numbers, cannot be '
'mistaken with Python built-ins like `for`...)'
% string) |
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def augment_excmessage(prefix=None, suffix=None) -> NoReturn: """Augment an exception message with additional information while keeping the original traceback. You can prefix and/or suffix text. If you prefix something (which happens much more often in the HydPy framework), the sub-clause ', the following error occurred:' is automatically included: Traceback (most recent call last):
TypeError: While showing how prefixing works, the following error \ occurred: unsupported operand type(s) for +: 'int' and 'str' \ (This is a final remark.) Some exceptions derived by site-packages do not support exception chaining due to requiring multiple initialisation arguments. In such cases, |augment_excmessage| generates an exception with the same name on the fly and raises it afterwards, which is pointed out by the exception name mentioning to the "objecttools" module: Traceback (most recent call last):
hydpy.core.objecttools.hydpy.core.objecttools.WrongError: While showing \ how prefixing works, the following error occurred: ('info 1', 'info 2') """ |
exc_old = sys.exc_info()[1]
message = str(exc_old)
if prefix is not None:
message = f'{prefix}, the following error occurred: {message}'
if suffix is not None:
message = f'{message} {suffix}'
try:
exc_new = type(exc_old)(message)
except BaseException:
exc_name = str(type(exc_old)).split("'")[1]
exc_type = type(exc_name, (BaseException,), {})
exc_type.__module = exc_old.__module__
raise exc_type(message) from exc_old
raise exc_new from exc_old |
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def excmessage_decorator(description) -> Callable: """Wrap a function with |augment_excmessage|. Function |excmessage_decorator| is a means to apply function |augment_excmessage| more efficiently. Suppose you would apply function |augment_excmessage| in a function that adds and returns to numbers: 3 Traceback (most recent call last):
TypeError: While trying to add `x` and `y`, the following error \ occurred: unsupported operand type(s) for +: 'int' and 'list' 3 Traceback (most recent call last):
TypeError: While trying to add `x` and `y`, the following error \ occurred: unsupported operand type(s) for +: 'int' and 'list' Additionally, exception messages related to wrong function calls are now also augmented: Traceback (most recent call last):
TypeError: While trying to add `x` and `y`, the following error \ occurred: add() missing 1 required positional argument: 'y' |excmessage_decorator| evaluates the given string like an f-string, allowing to mention the argument values of the called function and to make use of all string modification functions provided by modules |objecttools|: Traceback (most recent call last):
TypeError: While trying to add `x` (1.11) and `y` (wrong), the following \ error occurred: unsupported operand type(s) for +: 'float' and 'str' Traceback (most recent call last):
TypeError: While trying to add `x` (1) and `y` (?), the following error \ occurred: add() missing 1 required positional argument: 'y' Traceback (most recent call last):
TypeError: While trying to add `x` (?) and `y` (1), the following error \ occurred: add() missing 1 required positional argument: 'x' Apply |excmessage_decorator| on methods also works fine: 1 Traceback (most recent call last):
TypeError: While trying to add an instance of class `Adder` with value \ `wrong` of type `str`, the following error occurred: unsupported operand \ type(s) for +=: 'int' and 'str' It is made sure that no information of the decorated function is lost: 'add' """ |
@wrapt.decorator
def wrapper(wrapped, instance, args, kwargs):
"""Apply |augment_excmessage| when the wrapped function fails."""
# pylint: disable=unused-argument
try:
return wrapped(*args, **kwargs)
except BaseException:
info = kwargs.copy()
info['self'] = instance
argnames = inspect.getfullargspec(wrapped).args
if argnames[0] == 'self':
argnames = argnames[1:]
for argname, arg in zip(argnames, args):
info[argname] = arg
for argname in argnames:
if argname not in info:
info[argname] = '?'
message = eval(
f"f'While trying to {description}'", globals(), info)
augment_excmessage(message)
return wrapper |
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def print_values(values, width=70):
"""Print the given values in multiple lines with a certain maximum width. By default, each line contains at most 70 characters: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 You can change this default behaviour by passing an alternative number of characters: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 """ |
for line in textwrap.wrap(repr_values(values), width=width):
print(line) |
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def assignrepr_values(values, prefix, width=None, _fakeend=0):
"""Return a prefixed, wrapped and properly aligned string representation of the given values using function |repr|. test(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12) If no width is given, no wrapping is performed: test(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12) To circumvent defining too long string representations, make use of the ellipsis option: test(1, 2, 3, 4, 5, 11, 12) test(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12) """ |
ellipsis_ = hydpy.pub.options.ellipsis
if (ellipsis_ > 0) and (len(values) > 2*ellipsis_):
string = (repr_values(values[:ellipsis_]) +
', ...,' +
repr_values(values[-ellipsis_:]))
else:
string = repr_values(values)
blanks = ' '*len(prefix)
if width is None:
wrapped = [string]
_fakeend = 0
else:
width -= len(prefix)
wrapped = textwrap.wrap(string+'_'*_fakeend, width)
if not wrapped:
wrapped = ['']
lines = []
for (idx, line) in enumerate(wrapped):
if idx == 0:
lines.append('%s%s' % (prefix, line))
else:
lines.append('%s%s' % (blanks, line))
string = '\n'.join(lines)
return string[:len(string)-_fakeend] |
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def assignrepr_values2(values, prefix):
"""Return a prefixed and properly aligned string representation of the given 2-dimensional value matrix using function |repr|. test(1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0) Functions |assignrepr_values2| works also on empty iterables: test() """ |
lines = []
blanks = ' '*len(prefix)
for (idx, subvalues) in enumerate(values):
if idx == 0:
lines.append('%s%s,' % (prefix, repr_values(subvalues)))
else:
lines.append('%s%s,' % (blanks, repr_values(subvalues)))
lines[-1] = lines[-1][:-1]
return '\n'.join(lines) |
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def _assignrepr_bracketed2(assignrepr_bracketed1, values, prefix, width=None):
"""Return a prefixed, wrapped and properly aligned bracketed string representation of the given 2-dimensional value matrix using function |repr|.""" |
brackets = getattr(assignrepr_bracketed1, '_brackets')
prefix += brackets[0]
lines = []
blanks = ' '*len(prefix)
for (idx, subvalues) in enumerate(values):
if idx == 0:
lines.append(assignrepr_bracketed1(subvalues, prefix, width))
else:
lines.append(assignrepr_bracketed1(subvalues, blanks, width))
lines[-1] += ','
if (len(values) > 1) or (brackets != '()'):
lines[-1] = lines[-1][:-1]
lines[-1] += brackets[1]
return '\n'.join(lines) |
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def round_(values, decimals=None, width=0, lfill=None, rfill=None, **kwargs):
"""Prints values with a maximum number of digits in doctests. See the documentation on function |repr| for more details. And note thate the option keyword arguments are passed to the print function. Usually one would apply function |round_| on a single or a vector of numbers: 0.333333 0.5, 0.3333, 0.25 Additionally, one can supply a `width` and a `rfill` argument: 1.0000 Alternatively, one can use the `lfill` arguments, which might e.g. be usefull for aligning different strings: __test Using both the `lfill` and the `rfill` argument raises an error: Traceback (most recent call last):
ValueError: For function `round_` values are passed for both \ arguments `lfill` and `rfill`. This is not allowed. """ |
if decimals is None:
decimals = hydpy.pub.options.reprdigits
with hydpy.pub.options.reprdigits(decimals):
if isinstance(values, abctools.IterableNonStringABC):
string = repr_values(values)
else:
string = repr_(values)
if (lfill is not None) and (rfill is not None):
raise ValueError(
'For function `round_` values are passed for both arguments '
'`lfill` and `rfill`. This is not allowed.')
if (lfill is not None) or (rfill is not None):
width = max(width, len(string))
if lfill is not None:
string = string.rjust(width, lfill)
else:
string = string.ljust(width, rfill)
print(string, **kwargs) |
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def extract(values, types, skip=False):
"""Return a generator that extracts certain objects from `values`. This function is thought for supporting the definition of functions with arguments, that can be objects of of contain types or that can be iterables containing these objects. The following examples show that function |extract| basically implements a type specific flattening mechanism: ('str1',) ('str1', 'str2') ('str1', 'str2', 1) If an object is neither iterable nor of the required type, the following exception is raised: Traceback (most recent call last):
TypeError: The given value `None` is neither iterable nor \ an instance of the following classes: str and int. Optionally, |None| values can be skipped: () ('str1', 'str2', 1) """ |
if isinstance(values, types):
yield values
elif skip and (values is None):
return
else:
try:
for value in values:
for subvalue in extract(value, types, skip):
yield subvalue
except TypeError as exc:
if exc.args[0].startswith('The given value'):
raise exc
else:
raise TypeError(
f'The given value `{repr(values)}` is neither iterable '
f'nor an instance of the following classes: '
f'{enumeration(types, converter=instancename)}.') |
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def enumeration(values, converter=str, default=''):
"""Return an enumeration string based on the given values. The following four examples show the standard output of function |enumeration|: 'text, 3, and []' 'text and 3' 'text' '' All given objects are converted to strings by function |str|, as shown by the first two examples. This behaviour can be changed by another function expecting a single argument and returning a string: 'str, int, and list' Furthermore, you can define a default string that is returned in case an empty iterable is given: 'nothing' """ |
values = tuple(converter(value) for value in values)
if not values:
return default
if len(values) == 1:
return values[0]
if len(values) == 2:
return ' and '.join(values)
return ', and '.join((', '.join(values[:-1]), values[-1])) |
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def trim(self, lower=None, upper=None):
"""Trim negative value whenever there is no internal lake within the respective subbasin. lz(-1.0) lz(0.0) lz(1.0) """ |
if upper is None:
control = self.subseqs.seqs.model.parameters.control
if not any(control.zonetype.values == ILAKE):
lower = 0.
sequencetools.StateSequence.trim(self, lower, upper) |
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def load_data(self, idx):
"""Call method |InputSequences.load_data| of all handled |InputSequences| objects.""" |
for subseqs in self:
if isinstance(subseqs, abctools.InputSequencesABC):
subseqs.load_data(idx) |
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def save_data(self, idx):
"""Call method `save_data|` of all handled |IOSequences| objects registered under |OutputSequencesABC|.""" |
for subseqs in self:
if isinstance(subseqs, abctools.OutputSequencesABC):
subseqs.save_data(idx) |
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def conditions(self) -> Dict[str, Dict[str, Union[float, numpy.ndarray]]]: """Nested dictionary containing the values of all condition sequences. See the documentation on property |HydPy.conditions| for further information. """ |
conditions = {}
for subname in NAMES_CONDITIONSEQUENCES:
subseqs = getattr(self, subname, ())
subconditions = {seq.name: copy.deepcopy(seq.values)
for seq in subseqs}
if subconditions:
conditions[subname] = subconditions
return conditions |
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def dirpath_int(self):
"""Absolute path of the directory of the internal data file. Normally, each sequence queries its current "internal" directory path from the |SequenceManager| object stored in module |pub|: We overwrite |FileManager.basepath| and prepare a folder in teh `iotesting` directory to simplify the following examples: Generally, |SequenceManager.tempdirpath| is queried: 'test/temp' Alternatively, you can specify |IOSequence.dirpath_int| for each sequence object individually: ('', 'path') ('test', 'temp') If neither an individual definition nor |SequenceManager| is available, the following error is raised: Traceback (most recent call last):
RuntimeError: For sequence `inputsequence` the directory of \ the internal data file cannot be determined. Either set it manually \ or prepare `pub.sequencemanager` correctly. Remove the `basepath` mock: """ |
try:
return hydpy.pub.sequencemanager.tempdirpath
except RuntimeError:
raise RuntimeError(
f'For sequence {objecttools.devicephrase(self)} '
f'the directory of the internal data file cannot '
f'be determined. Either set it manually or prepare '
f'`pub.sequencemanager` correctly.') |
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def disk2ram(self):
"""Move internal data from disk to RAM.""" |
values = self.series
self.deactivate_disk()
self.ramflag = True
self.__set_array(values)
self.update_fastaccess() |
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def ram2disk(self):
"""Move internal data from RAM to disk.""" |
values = self.series
self.deactivate_ram()
self.diskflag = True
self._save_int(values)
self.update_fastaccess() |
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def numericshape(self):
"""Shape of the array of temporary values required for the numerical solver actually being selected.""" |
try:
numericshape = [self.subseqs.seqs.model.numconsts.nmb_stages]
except AttributeError:
objecttools.augment_excmessage(
'The `numericshape` of a sequence like `%s` depends on the '
'configuration of the actual integration algorithm. '
'While trying to query the required configuration data '
'`nmb_stages` of the model associated with element `%s`'
% (self.name, objecttools.devicename(self)))
# noinspection PyUnboundLocalVariable
numericshape.extend(self.shape)
return tuple(numericshape) |
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def series(self) -> InfoArray: """Internal time series data within an |numpy.ndarray|.""" |
if self.diskflag:
array = self._load_int()
elif self.ramflag:
array = self.__get_array()
else:
raise AttributeError(
f'Sequence {objecttools.devicephrase(self)} is not requested '
f'to make any internal data available to the user.')
return InfoArray(array, info={'type': 'unmodified'}) |
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def load_ext(self):
"""Read the internal data from an external data file.""" |
try:
sequencemanager = hydpy.pub.sequencemanager
except AttributeError:
raise RuntimeError(
'The time series of sequence %s cannot be loaded. Firstly, '
'you have to prepare `pub.sequencemanager` correctly.'
% objecttools.devicephrase(self))
sequencemanager.load_file(self) |
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def adjust_short_series(self, timegrid, values):
"""Adjust a short time series to a longer timegrid. Normally, time series data to be read from a external data files should span (at least) the whole initialization time period of a HydPy project. However, for some variables which are only used for comparison (e.g. observed runoff used for calibration), incomplete time series might also be helpful. This method it thought for adjusting such incomplete series to the public initialization time grid stored in module |pub|. It is automatically called in method |IOSequence.adjust_series| when necessary provided that the option |Options.checkseries| is disabled. Assume the initialization time period of a HydPy project spans five day: Prepare a node series object for observational data: Prepare a test function that expects the timegrid of the data and the data itself, which returns the ajdusted array by means of calling method |IOSequence.adjust_short_series|: The following calls to the test function shows the arrays returned for different kinds of misalignments: array([ 1., 1., 1., 1., 1.]) array([ nan, nan, 1., 1., 1.]) array([ nan, nan, 1., 1., 1.]) array([ 1., 1., 1., nan, nan]) array([ 1., 1., 1., nan, nan]) array([ nan, nan, 1., nan, nan]) array([ nan, nan, nan, nan, nan]) array([ nan, nan, nan, nan, nan]) array([ nan, nan, nan, nan, nan]) array([ nan, nan, nan, nan, nan]) Through enabling option |Options.usedefaultvalues| the missing values are initialised with zero instead of nan: array([ 0., 0., 1., 1., 1.]) """ |
idxs = [timegrid[hydpy.pub.timegrids.init.firstdate],
timegrid[hydpy.pub.timegrids.init.lastdate]]
valcopy = values
values = numpy.full(self.seriesshape, self.initinfo[0])
len_ = len(valcopy)
jdxs = []
for idx in idxs:
if idx < 0:
jdxs.append(0)
elif idx <= len_:
jdxs.append(idx)
else:
jdxs.append(len_)
valcopy = valcopy[jdxs[0]:jdxs[1]]
zdx1 = max(-idxs[0], 0)
zdx2 = zdx1+jdxs[1]-jdxs[0]
values[zdx1:zdx2] = valcopy
return values |
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def check_completeness(self):
"""Raise a |RuntimeError| if the |IOSequence.series| contains at least one |numpy.nan| value, if option |Options.checkseries| is enabled. Traceback (most recent call last):
RuntimeError: The series array of sequence `seq` contains 10 nan values. Traceback (most recent call last):
RuntimeError: The series array of sequence `seq` contains 1 nan value. """ |
if hydpy.pub.options.checkseries:
isnan = numpy.isnan(self.series)
if numpy.any(isnan):
nmb = numpy.sum(isnan)
valuestring = 'value' if nmb == 1 else 'values'
raise RuntimeError(
f'The series array of sequence '
f'{objecttools.devicephrase(self)} contains '
f'{nmb} nan {valuestring}.') |
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def save_ext(self):
"""Write the internal data into an external data file.""" |
try:
sequencemanager = hydpy.pub.sequencemanager
except AttributeError:
raise RuntimeError(
'The time series of sequence %s cannot be saved. Firstly,'
'you have to prepare `pub.sequencemanager` correctly.'
% objecttools.devicephrase(self))
sequencemanager.save_file(self) |
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def _load_int(self):
"""Load internal data from file and return it.""" |
values = numpy.fromfile(self.filepath_int)
if self.NDIM > 0:
values = values.reshape(self.seriesshape)
return values |
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def average_series(self, *args, **kwargs) -> InfoArray: """Average the actual time series of the |Variable| object for all time points. Method |IOSequence.average_series| works similarly as method |Variable.average_values| of class |Variable|, from which we borrow some examples. However, firstly, we have to prepare a |Timegrids| object to define the |IOSequence.series| length: As shown for method |Variable.average_values|, for 0-dimensional |IOSequence| objects the result of |IOSequence.average_series| equals |IOSequence.series| itself: InfoArray([ 190., 200., 210.]) For |IOSequence| objects with an increased dimensionality, a weighting parameter is required, again: InfoArray([ 390., 400., 410.]) The documentation on method |Variable.average_values| provides many examples on how to use different masks in different ways. Here we restrict ourselves to the first example, where a new mask enforces that |IOSequence.average_series| takes only the first two columns of the `series` into account: InfoArray([ 290., 300., 310.]) """ |
try:
if not self.NDIM:
array = self.series
else:
mask = self.get_submask(*args, **kwargs)
if numpy.any(mask):
weights = self.refweights[mask]
weights /= numpy.sum(weights)
series = self.series[:, mask]
axes = tuple(range(1, self.NDIM+1))
array = numpy.sum(weights*series, axis=axes)
else:
return numpy.nan
return InfoArray(array, info={'type': 'mean'})
except BaseException:
objecttools.augment_excmessage(
'While trying to calculate the mean value of '
'the internal time series of sequence %s'
% objecttools.devicephrase(self)) |
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def aggregate_series(self, *args, **kwargs) -> InfoArray: """Aggregates time series data based on the actual |FluxSequence.aggregation_ext| attribute of |IOSequence| subclasses. We prepare some nodes and elements with the help of method |prepare_io_example_1| and select a 1-dimensional flux sequence of type |lland_fluxes.NKor| as an example: If no |FluxSequence.aggregation_ext| is `none`, the original time series values are returned: 'none' InfoArray([[ 24., 25., 26.], [ 27., 28., 29.], [ 30., 31., 32.], [ 33., 34., 35.]]) If no |FluxSequence.aggregation_ext| is `mean`, function |IOSequence.aggregate_series| is called: InfoArray([ 25., 28., 31., 34.]) In case the state of the sequence is invalid: Traceback (most recent call last):
RuntimeError: Unknown aggregation mode `nonexistent` for \ sequence `nkor` of element `element3`. The following technical test confirms that all potential positional and keyword arguments are passed properly: """ |
mode = self.aggregation_ext
if mode == 'none':
return self.series
elif mode == 'mean':
return self.average_series(*args, **kwargs)
else:
raise RuntimeError(
'Unknown aggregation mode `%s` for sequence %s.'
% (mode, objecttools.devicephrase(self))) |
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def open_files(self, idx):
"""Open all files with an activated disk flag.""" |
for name in self:
if getattr(self, '_%s_diskflag' % name):
path = getattr(self, '_%s_path' % name)
file_ = open(path, 'rb+')
ndim = getattr(self, '_%s_ndim' % name)
position = 8*idx
for idim in range(ndim):
length = getattr(self, '_%s_length_%d' % (name, idim))
position *= length
file_.seek(position)
setattr(self, '_%s_file' % name, file_) |
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def close_files(self):
"""Close all files with an activated disk flag.""" |
for name in self:
if getattr(self, '_%s_diskflag' % name):
file_ = getattr(self, '_%s_file' % name)
file_.close() |
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def load_data(self, idx):
"""Load the internal data of all sequences. Load from file if the corresponding disk flag is activated, otherwise load from RAM.""" |
for name in self:
ndim = getattr(self, '_%s_ndim' % name)
diskflag = getattr(self, '_%s_diskflag' % name)
ramflag = getattr(self, '_%s_ramflag' % name)
if diskflag:
file_ = getattr(self, '_%s_file' % name)
length_tot = 1
shape = []
for jdx in range(ndim):
length = getattr(self, '_%s_length_%s' % (name, jdx))
length_tot *= length
shape.append(length)
raw = file_.read(length_tot*8)
values = struct.unpack(length_tot*'d', raw)
if ndim:
values = numpy.array(values).reshape(shape)
else:
values = values[0]
elif ramflag:
array = getattr(self, '_%s_array' % name)
values = array[idx]
if diskflag or ramflag:
if ndim == 0:
setattr(self, name, values)
else:
getattr(self, name)[:] = values |
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def save_data(self, idx):
"""Save the internal data of all sequences with an activated flag. Write to file if the corresponding disk flag is activated; store in working memory if the corresponding ram flag is activated.""" |
for name in self:
actual = getattr(self, name)
diskflag = getattr(self, '_%s_diskflag' % name)
ramflag = getattr(self, '_%s_ramflag' % name)
if diskflag:
file_ = getattr(self, '_%s_file' % name)
ndim = getattr(self, '_%s_ndim' % name)
length_tot = 1
for jdx in range(ndim):
length = getattr(self, '_%s_length_%s' % (name, jdx))
length_tot *= length
if ndim:
raw = struct.pack(length_tot*'d', *actual.flatten())
else:
raw = struct.pack('d', actual)
file_.write(raw)
elif ramflag:
array = getattr(self, '_%s_array' % name)
array[idx] = actual |
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def update(self):
"""Update |AbsFHRU| based on |FT| and |FHRU|. absfhru(20.0, 80.0) """ |
control = self.subpars.pars.control
self(control.ft*control.fhru) |
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def update(self):
"""Update |KInz| based on |HInz| and |LAI|. 0.2 0.4 """ |
con = self.subpars.pars.control
self(con.hinz*con.lai) |
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def update(self):
"""Update |WB| based on |RelWB| and |NFk|. wb(20.0, 40.0) """ |
con = self.subpars.pars.control
self(con.relwb*con.nfk) |
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def update(self):
"""Update |WZ| based on |RelWZ| and |NFk|. wz(80.0, 160.0) """ |
con = self.subpars.pars.control
self(con.relwz*con.nfk) |
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def update(self):
"""Update |KB| based on |EQB| and |TInd|. kb(100.0) """ |
con = self.subpars.pars.control
self(con.eqb*con.tind) |
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def update(self):
"""Update |KI1| based on |EQI1| and |TInd|. ki1(50.0) """ |
con = self.subpars.pars.control
self(con.eqi1*con.tind) |
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def update(self):
"""Update |KI2| based on |EQI2| and |TInd|. ki2(10.0) """ |
con = self.subpars.pars.control
self(con.eqi2*con.tind) |
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def update(self):
"""Update |KD1| based on |EQD1| and |TInd|. kd1(5.0) """ |
con = self.subpars.pars.control
self(con.eqd1*con.tind) |
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def update(self):
"""Update |KD2| based on |EQD2| and |TInd|. kd2(1.0) """ |
con = self.subpars.pars.control
self(con.eqd2*con.tind) |
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def update(self):
"""Update |QFactor| based on |FT| and the current simulation step size. qfactor(0.115741) """ |
con = self.subpars.pars.control
self(con.ft*1000./self.simulationstep.seconds) |
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def _router_numbers(self):
"""A tuple of the numbers of all "routing" basins.""" |
return tuple(up for up in self._up2down.keys()
if up in self._up2down.values()) |
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Description:
def supplier_elements(self):
"""A |Elements| collection of all "supplying" basins. (All river basins are assumed to supply something to the downstream basin.) The following elements are properly connected to the required outlet nodes already: Element("land_111", outlets="node_113") Element("land_1121", outlets="node_1123") Element("land_1122", outlets="node_1123") Element("land_1123", outlets="node_1125") Element("land_1124", outlets="node_1125") Element("land_1125", outlets="node_1129") Element("land_11261", outlets="node_11269") Element("land_11262", outlets="node_11269") Element("land_11269", outlets="node_1129") Element("land_1129", outlets="node_113") Element("land_113", outlets="node_outlet") It is both possible to change the prefix names of the elements and nodes, as long as it results in a valid variable name (e.g. does not start with a number):
Elements("a_111", "a_1121", "a_1122", "a_1123", "a_1124", "a_1125", "a_11261", "a_11262", "a_11269", "a_1129", "a_113") """ |
elements = devicetools.Elements()
for supplier in self._supplier_numbers:
element = self._get_suppliername(supplier)
try:
outlet = self._get_nodename(self._up2down[supplier])
except TypeError:
outlet = self.last_node
elements += devicetools.Element(element, outlets=outlet)
return elements |
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Description:
def router_elements(self):
"""A |Elements| collection of all "routing" basins. (Only river basins with a upstream basin are assumed to route something to the downstream basin.) The following elements are properly connected to the required inlet and outlet nodes already: Element("stream_1123", inlets="node_1123", outlets="node_1125") Element("stream_1125", inlets="node_1125", outlets="node_1129") Element("stream_11269", inlets="node_11269", outlets="node_1129") Element("stream_1129", inlets="node_1129", outlets="node_113") Element("stream_113", inlets="node_113", outlets="node_outlet") It is both possible to change the prefix names of the elements and nodes, as long as it results in a valid variable name (e.g. does not start with a number):
Elements("c_1123", "c_1125", "c_11269", "c_1129", "c_113") """ |
elements = devicetools.Elements()
for router in self._router_numbers:
element = self._get_routername(router)
inlet = self._get_nodename(router)
try:
outlet = self._get_nodename(self._up2down[router])
except TypeError:
outlet = self.last_node
elements += devicetools.Element(
element, inlets=inlet, outlets=outlet)
return elements |
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Description:
def nodes(self):
"""A |Nodes| collection of all required nodes. Note that the required outlet node is added: Nodes("node_1123", "node_1125", "node_11269", "node_1129", "node_113", "node_outlet") It is both possible to change the prefix names of the nodes and the name of the outlet node separately: Nodes("b_1123", "b_1125", "b_11269", "b_1129", "b_113", "l_node") """ |
return (
devicetools.Nodes(
self.node_prefix+routers for routers in self._router_numbers) +
devicetools.Node(self.last_node)) |
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