Datasets:
thisisanshgupta
/
Pycode

Dataset card Data Studio Files
xet
Community
text
stringlengths
0
828
\rho_0 \frac{\left[-m (\omega \tau)^c sin(\frac{c \pi}{2}
\right] \cdot \left[ 2 \omega^c c \tau^{c-1} cos(\frac{c
\pi}{2}) + 2 c \omega^{2 c} \tau^{2 c - 1}\right]}{\left[1 + 2 (\omega
\tau)^c cos(\frac{c \pi}{2}) + (\omega \tau)^{2 c}\right]^2}`
""""""
self._set_parameters(pars)
# term1
nom1 = - self.m * np.sin(self.ang) * self.w ** self.c *\
self.c * self.tau ** (self.c - 1)
term1 = nom1 / self.denom
# term2
nom2 = (self.m * self.otc * np.sin(self.ang)) *\
(2 * self.w ** self.c * self.c * self.tau ** (self.c - 1) *
np.cos(self.ang) + 2 * self.c * self.w ** (2 * self.c) *
self.tau ** (2 * self.c - 1))
term2 = nom2 / self.denom ** 2
result = term1 + term2
result *= self.rho0
return result"
255,"def dim_dc(self, pars):
r""""""
:math:`\frac{\partial \hat{\rho''}(\omega)}{\partial c} = \rho_0
\frac{-m sin(\frac{c \pi}{2}) ln(\omega \tau)(\omega \tau)^c - m
(\omega \tau)^c \frac{\pi}{2} cos(\frac{\pi}{2}}{1 + 2 (\omega \tau)^c
cos(\frac{c \pi}{2}) + (\omega \tau)^{2 c}} + \rho_0 \frac{\left[-m
(\omega \tau)^c cos(\frac{c \pi}{2}) \right] \cdot \left[ -2 ln(\omega
\tau) (\omega \tau)^c cos(\frac{c \pi}{2}) + 2 (\omega \tau)^c
\frac{\pi}{2} cos(\frac{c \pi}{2}) \right] + \left[2 ln(\omega \tau)
(\omega \tau)^{2 c}\right]}{\left[1 + 2 (\omega \tau)^c cos(\frac{c
\pi}{2}) + (\omega \tau)^{2 c}\right]^2}`
""""""
self._set_parameters(pars)
# term1
nom1a = - self.m * np.log(self.w * self.tau) * self.otc *\
np.sin(self.ang)
nom1b = - self.m * self.otc * (np.pi / 2.0) * np.cos(self.ang)
term1 = (nom1a + nom1b) / self.denom
# term2
nom2 = (self.m * self.otc * np.sin(self.ang)) *\
(2 * np.log(self.w * self.tau) * self.otc * np.cos(self.ang) -
2 * self.otc * (np.pi / 2.0) * np.sin(self.ang) +
2 * np.log(self.w * self.tau) * self.otc2)
term2 = nom2 / self.denom ** 2
result = term1 + term2
result *= self.rho0
return result"
256,"def Jacobian_re_im(self, pars):
r""""""
:math:`J`
>>> import sip_models.res.cc as cc
>>> import numpy as np
>>> f = np.logspace(-3, 3, 20)
>>> pars = [100, 0.1, 0.04, 0.8]
>>> obj = cc.cc(f)
>>> J = obj.Jacobian_re_im(pars)
""""""
partials = []
# partials.append(self.dre_dlog10rho0(pars)[:, np.newaxis, :])
partials.append(self.dre_drho0(pars)[:, np.newaxis])
partials.append(self.dre_dm(pars))
# partials.append(self.dre_dlog10tau(pars))
partials.append(self.dre_dtau(pars))
partials.append(self.dre_dc(pars))
# partials.append(self.dim_dlog10rho0(pars)[:, np.newaxis, :])
partials.append(self.dim_drho0(pars)[:, np.newaxis])
partials.append(self.dim_dm(pars))
# partials.append(self.dim_dlog10tau(pars))
partials.append(self.dim_dtau(pars))
partials.append(self.dim_dc(pars))
print('SHAPES')
for x in partials:
print(x.shape)
J = np.concatenate(partials, axis=1)
return J"
257,"def read_dict_or_list_from_json(desired_type: Type[dict], file_object: TextIOBase,
logger: Logger, conversion_finder: ConversionFinder, **kwargs) -> Dict[str, Any]:
""""""
Helper method to read a dictionary from a .json file using json library
:param file_object:
:return:
""""""
# lazy import in order not to force use of jprops
import json
res = json.load(file_object)
# convert if required
return ConversionFinder.convert_collection_values_according_to_pep(res, desired_type, conversion_finder, logger, **kwargs)"
258,"def get_default_collection_parsers(parser_finder: ParserFinder, conversion_finder: ConversionFinder) -> List[AnyParser]:
""""""
Utility method to return the default parsers able to parse a dictionary from a file.
:return:
""""""