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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.from_other | def from_other(cls, ori, **kwargs):
""" Creates a new instance with an existing one as a template.
Parameters
----------
ori : SymbolicSys instance
\\*\\*kwargs:
Keyword arguments used to create the new instance.
Returns
-------
A new instanc... | python | def from_other(cls, ori, **kwargs):
""" Creates a new instance with an existing one as a template.
Parameters
----------
ori : SymbolicSys instance
\\*\\*kwargs:
Keyword arguments used to create the new instance.
Returns
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.from_other_new_params | def from_other_new_params(cls, ori, par_subs, new_pars, new_par_names=None,
new_latex_par_names=None, **kwargs):
""" Creates a new instance with an existing one as a template (with new parameters)
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new_latex_par_names=None, **kwargs):
""" Creates a new instance with an existing one as a template (with new parameters)
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.from_other_new_params_by_name | def from_other_new_params_by_name(cls, ori, par_subs, new_par_names=(), **kwargs):
""" Creates a new instance with an existing one as a template (with new parameters)
Calls ``.from_other_new_params`` but first it creates the new instances from user provided
callbacks generating the expressions ... | python | def from_other_new_params_by_name(cls, ori, par_subs, new_par_names=(), **kwargs):
""" Creates a new instance with an existing one as a template (with new parameters)
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.get_jac | def get_jac(self):
""" Derives the jacobian from ``self.exprs`` and ``self.dep``. """
if self._jac is True:
if self.sparse is True:
self._jac, self._colptrs, self._rowvals = self.be.sparse_jacobian_csc(self.exprs, self.dep)
elif self.band is not None: # Banded
... | python | def get_jac(self):
""" Derives the jacobian from ``self.exprs`` and ``self.dep``. """
if self._jac is True:
if self.sparse is True:
self._jac, self._colptrs, self._rowvals = self.be.sparse_jacobian_csc(self.exprs, self.dep)
elif self.band is not None: # Banded
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.get_jtimes | def get_jtimes(self):
""" Derive the jacobian-vector product from ``self.exprs`` and ``self.dep``"""
if self._jtimes is False:
return False
if self._jtimes is True:
r = self.be.Dummy('r')
v = tuple(self.be.Dummy('v_{0}'.format(i)) for i in range(self.ny))
... | python | def get_jtimes(self):
""" Derive the jacobian-vector product from ``self.exprs`` and ``self.dep``"""
if self._jtimes is False:
return False
if self._jtimes is True:
r = self.be.Dummy('r')
v = tuple(self.be.Dummy('v_{0}'.format(i)) for i in range(self.ny))
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.jacobian_singular | def jacobian_singular(self):
""" Returns True if Jacobian is singular, else False. """
cses, (jac_in_cses,) = self.be.cse(self.get_jac())
if jac_in_cses.nullspace():
return True
else:
return False | python | def jacobian_singular(self):
""" Returns True if Jacobian is singular, else False. """
cses, (jac_in_cses,) = self.be.cse(self.get_jac())
if jac_in_cses.nullspace():
return True
else:
return False | [
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.get_dfdx | def get_dfdx(self):
""" Calculates 2nd derivatives of ``self.exprs`` """
if self._dfdx is True:
if self.indep is None:
zero = 0*self.be.Dummy()**0
self._dfdx = self.be.Matrix(1, self.ny, [zero]*self.ny)
else:
self._dfdx = self.be.Ma... | python | def get_dfdx(self):
""" Calculates 2nd derivatives of ``self.exprs`` """
if self._dfdx is True:
if self.indep is None:
zero = 0*self.be.Dummy()**0
self._dfdx = self.be.Matrix(1, self.ny, [zero]*self.ny)
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.get_f_ty_callback | def get_f_ty_callback(self):
""" Generates a callback for evaluating ``self.exprs``. """
cb = self._callback_factory(self.exprs)
lb = self.lower_bounds
ub = self.upper_bounds
if lb is not None or ub is not None:
def _bounds_wrapper(t, y, p=(), be=None):
... | python | def get_f_ty_callback(self):
""" Generates a callback for evaluating ``self.exprs``. """
cb = self._callback_factory(self.exprs)
lb = self.lower_bounds
ub = self.upper_bounds
if lb is not None or ub is not None:
def _bounds_wrapper(t, y, p=(), be=None):
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.get_j_ty_callback | def get_j_ty_callback(self):
""" Generates a callback for evaluating the jacobian. """
j_exprs = self.get_jac()
if j_exprs is False:
return None
cb = self._callback_factory(j_exprs)
if self.sparse:
from scipy.sparse import csc_matrix
def spars... | python | def get_j_ty_callback(self):
""" Generates a callback for evaluating the jacobian. """
j_exprs = self.get_jac()
if j_exprs is False:
return None
cb = self._callback_factory(j_exprs)
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.get_dfdx_callback | def get_dfdx_callback(self):
""" Generate a callback for evaluating derivative of ``self.exprs`` """
dfdx_exprs = self.get_dfdx()
if dfdx_exprs is False:
return None
return self._callback_factory(dfdx_exprs) | python | def get_dfdx_callback(self):
""" Generate a callback for evaluating derivative of ``self.exprs`` """
dfdx_exprs = self.get_dfdx()
if dfdx_exprs is False:
return None
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bjodah/pyodesys | pyodesys/symbolic.py | SymbolicSys.get_jtimes_callback | def get_jtimes_callback(self):
""" Generate a callback fro evaluating the jacobian-vector product."""
jtimes = self.get_jtimes()
if jtimes is False:
return None
v, jtimes_exprs = jtimes
return _Callback(self.indep, tuple(self.dep) + tuple(v), self.params,
... | python | def get_jtimes_callback(self):
""" Generate a callback fro evaluating the jacobian-vector product."""
jtimes = self.get_jtimes()
if jtimes is False:
return None
v, jtimes_exprs = jtimes
return _Callback(self.indep, tuple(self.dep) + tuple(v), self.params,
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bjodah/pyodesys | pyodesys/symbolic.py | TransformedSys.from_callback | def from_callback(cls, cb, ny=None, nparams=None, dep_transf_cbs=None,
indep_transf_cbs=None, roots_cb=None, **kwargs):
"""
Create an instance from a callback.
Analogous to :func:`SymbolicSys.from_callback`.
Parameters
----------
cb : callable
... | python | def from_callback(cls, cb, ny=None, nparams=None, dep_transf_cbs=None,
indep_transf_cbs=None, roots_cb=None, **kwargs):
"""
Create an instance from a callback.
Analogous to :func:`SymbolicSys.from_callback`.
Parameters
----------
cb : callable
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bjodah/pyodesys | pyodesys/symbolic.py | ScaledSys.from_callback | def from_callback(cls, cb, ny=None, nparams=None, dep_scaling=1, indep_scaling=1,
**kwargs):
"""
Create an instance from a callback.
Analogous to :func:`SymbolicSys.from_callback`.
Parameters
----------
cb : callable
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**kwargs):
"""
Create an instance from a callback.
Analogous to :func:`SymbolicSys.from_callback`.
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cb : callable
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bjodah/pyodesys | pyodesys/symbolic.py | PartiallySolvedSystem.from_linear_invariants | def from_linear_invariants(cls, ori_sys, preferred=None, **kwargs):
""" Reformulates the ODE system in fewer variables.
Given linear invariant equations one can always reduce the number
of dependent variables in the system by the rank of the matrix describing
this linear system.
... | python | def from_linear_invariants(cls, ori_sys, preferred=None, **kwargs):
""" Reformulates the ODE system in fewer variables.
Given linear invariant equations one can always reduce the number
of dependent variables in the system by the rank of the matrix describing
this linear system.
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bjodah/pyodesys | pyodesys/core.py | integrate_auto_switch | def integrate_auto_switch(odes, kw, x, y0, params=(), **kwargs):
""" Auto-switching between formulations of ODE system.
In case one has a formulation of a system of ODEs which is preferential in
the beginning of the integration, this function allows the user to run the
integration with this system wher... | python | def integrate_auto_switch(odes, kw, x, y0, params=(), **kwargs):
""" Auto-switching between formulations of ODE system.
In case one has a formulation of a system of ODEs which is preferential in
the beginning of the integration, this function allows the user to run the
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bjodah/pyodesys | pyodesys/core.py | chained_parameter_variation | def chained_parameter_variation(subject, durations, y0, varied_params, default_params=None,
integrate_kwargs=None, x0=None, npoints=1, numpy=None):
""" Integrate an ODE-system for a serie of durations with some parameters changed in-between
Parameters
----------
subject ... | python | def chained_parameter_variation(subject, durations, y0, varied_params, default_params=None,
integrate_kwargs=None, x0=None, npoints=1, numpy=None):
""" Integrate an ODE-system for a serie of durations with some parameters changed in-between
Parameters
----------
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bjodah/pyodesys | pyodesys/core.py | ODESys.pre_process | def pre_process(self, xout, y0, params=()):
""" Transforms input to internal values, used internally. """
for pre_processor in self.pre_processors:
xout, y0, params = pre_processor(xout, y0, params)
return [self.numpy.atleast_1d(arr) for arr in (xout, y0, params)] | python | def pre_process(self, xout, y0, params=()):
""" Transforms input to internal values, used internally. """
for pre_processor in self.pre_processors:
xout, y0, params = pre_processor(xout, y0, params)
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bjodah/pyodesys | pyodesys/core.py | ODESys.post_process | def post_process(self, xout, yout, params):
""" Transforms internal values to output, used internally. """
for post_processor in self.post_processors:
xout, yout, params = post_processor(xout, yout, params)
return xout, yout, params | python | def post_process(self, xout, yout, params):
""" Transforms internal values to output, used internally. """
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xout, yout, params = post_processor(xout, yout, params)
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bjodah/pyodesys | pyodesys/core.py | ODESys.adaptive | def adaptive(self, y0, x0, xend, params=(), **kwargs):
""" Integrate with integrator chosen output.
Parameters
----------
integrator : str
See :meth:`integrate`.
y0 : array_like
See :meth:`integrate`.
x0 : float
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""" Integrate with integrator chosen output.
Parameters
----------
integrator : str
See :meth:`integrate`.
y0 : array_like
See :meth:`integrate`.
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bjodah/pyodesys | pyodesys/core.py | ODESys.predefined | def predefined(self, y0, xout, params=(), **kwargs):
""" Integrate with user chosen output.
Parameters
----------
integrator : str
See :meth:`integrate`.
y0 : array_like
See :meth:`integrate`.
xout : array_like
params : array_like
... | python | def predefined(self, y0, xout, params=(), **kwargs):
""" Integrate with user chosen output.
Parameters
----------
integrator : str
See :meth:`integrate`.
y0 : array_like
See :meth:`integrate`.
xout : array_like
params : array_like
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bjodah/pyodesys | pyodesys/core.py | ODESys.integrate | def integrate(self, x, y0, params=(), atol=1e-8, rtol=1e-8, **kwargs):
""" Integrate the system of ordinary differential equations.
Solves the initial value problem (IVP).
Parameters
----------
x : array_like or pair (start and final time) or float
if float:
... | python | def integrate(self, x, y0, params=(), atol=1e-8, rtol=1e-8, **kwargs):
""" Integrate the system of ordinary differential equations.
Solves the initial value problem (IVP).
Parameters
----------
x : array_like or pair (start and final time) or float
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bjodah/pyodesys | pyodesys/core.py | ODESys._integrate_scipy | def _integrate_scipy(self, intern_xout, intern_y0, intern_p,
atol=1e-8, rtol=1e-8, first_step=None, with_jacobian=None,
force_predefined=False, name=None, **kwargs):
""" Do not use directly (use ``integrate('scipy', ...)``).
Uses `scipy.integrate.ode <h... | python | def _integrate_scipy(self, intern_xout, intern_y0, intern_p,
atol=1e-8, rtol=1e-8, first_step=None, with_jacobian=None,
force_predefined=False, name=None, **kwargs):
""" Do not use directly (use ``integrate('scipy', ...)``).
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bjodah/pyodesys | pyodesys/core.py | ODESys._integrate_gsl | def _integrate_gsl(self, *args, **kwargs):
""" Do not use directly (use ``integrate(..., integrator='gsl')``).
Uses `GNU Scientific Library <http://www.gnu.org/software/gsl/>`_
(via `pygslodeiv2 <https://pypi.python.org/pypi/pygslodeiv2>`_)
to integrate the ODE system.
Paramete... | python | def _integrate_gsl(self, *args, **kwargs):
""" Do not use directly (use ``integrate(..., integrator='gsl')``).
Uses `GNU Scientific Library <http://www.gnu.org/software/gsl/>`_
(via `pygslodeiv2 <https://pypi.python.org/pypi/pygslodeiv2>`_)
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bjodah/pyodesys | pyodesys/core.py | ODESys._integrate_odeint | def _integrate_odeint(self, *args, **kwargs):
""" Do not use directly (use ``integrate(..., integrator='odeint')``).
Uses `Boost.Numeric.Odeint <http://www.odeint.com>`_
(via `pyodeint <https://pypi.python.org/pypi/pyodeint>`_) to integrate
the ODE system.
"""
import pyo... | python | def _integrate_odeint(self, *args, **kwargs):
""" Do not use directly (use ``integrate(..., integrator='odeint')``).
Uses `Boost.Numeric.Odeint <http://www.odeint.com>`_
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bjodah/pyodesys | pyodesys/core.py | ODESys._integrate_cvode | def _integrate_cvode(self, *args, **kwargs):
""" Do not use directly (use ``integrate(..., integrator='cvode')``).
Uses CVode from CVodes in
`SUNDIALS <https://computation.llnl.gov/casc/sundials/>`_
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to integrate the ODE s... | python | def _integrate_cvode(self, *args, **kwargs):
""" Do not use directly (use ``integrate(..., integrator='cvode')``).
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bjodah/pyodesys | pyodesys/core.py | ODESys.plot_phase_plane | def plot_phase_plane(self, indices=None, **kwargs):
""" Plots a phase portrait from last integration.
This method will be deprecated. Please use :meth:`Result.plot_phase_plane`.
See :func:`pyodesys.plotting.plot_phase_plane`
"""
return self._plot(plot_phase_plane, indices=indice... | python | def plot_phase_plane(self, indices=None, **kwargs):
""" Plots a phase portrait from last integration.
This method will be deprecated. Please use :meth:`Result.plot_phase_plane`.
See :func:`pyodesys.plotting.plot_phase_plane`
"""
return self._plot(plot_phase_plane, indices=indice... | [
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bjodah/pyodesys | pyodesys/core.py | ODESys.stiffness | def stiffness(self, xyp=None, eigenvals_cb=None):
""" [DEPRECATED] Use :meth:`Result.stiffness`, stiffness ration
Running stiffness ratio from last integration.
Calculate sittness ratio, i.e. the ratio between the largest and
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neon-jungle/wagtailnews | wagtailnews/views/editor.py | build_dummy_request | def build_dummy_request(newsitem):
"""
Construct a HttpRequest object that is, as far as possible,
representative of ones that would receive this page as a response. Used
for previewing / moderation and any other place where we want to
display a view of this page in the admin interface without going... | python | def build_dummy_request(newsitem):
"""
Construct a HttpRequest object that is, as far as possible,
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neon-jungle/wagtailnews | wagtailnews/permissions.py | user_can_edit_news | def user_can_edit_news(user):
"""
Check if the user has permission to edit any of the registered NewsItem
types.
"""
newsitem_models = [model.get_newsitem_model()
for model in NEWSINDEX_MODEL_CLASSES]
if user.is_active and user.is_superuser:
# admin can edit news ... | python | def user_can_edit_news(user):
"""
Check if the user has permission to edit any of the registered NewsItem
types.
"""
newsitem_models = [model.get_newsitem_model()
for model in NEWSINDEX_MODEL_CLASSES]
if user.is_active and user.is_superuser:
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neon-jungle/wagtailnews | wagtailnews/permissions.py | user_can_edit_newsitem | def user_can_edit_newsitem(user, NewsItem):
"""
Check if the user has permission to edit a particular NewsItem type.
"""
for perm in format_perms(NewsItem, ['add', 'change', 'delete']):
if user.has_perm(perm):
return True
return False | python | def user_can_edit_newsitem(user, NewsItem):
"""
Check if the user has permission to edit a particular NewsItem type.
"""
for perm in format_perms(NewsItem, ['add', 'change', 'delete']):
if user.has_perm(perm):
return True
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neon-jungle/wagtailnews | wagtailnews/models.py | get_date_or_404 | def get_date_or_404(year, month, day):
"""Try to make a date from the given inputs, raising Http404 on error"""
try:
return datetime.date(int(year), int(month), int(day))
except ValueError:
raise Http404 | python | def get_date_or_404(year, month, day):
"""Try to make a date from the given inputs, raising Http404 on error"""
try:
return datetime.date(int(year), int(month), int(day))
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neon-jungle/wagtailnews | wagtailnews/models.py | NewsIndexMixin.respond | def respond(self, request, view, newsitems, extra_context={}):
"""A helper that takes some news items and returns an HttpResponse"""
context = self.get_context(request, view=view)
context.update(self.paginate_newsitems(request, newsitems))
context.update(extra_context)
template =... | python | def respond(self, request, view, newsitems, extra_context={}):
"""A helper that takes some news items and returns an HttpResponse"""
context = self.get_context(request, view=view)
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neon-jungle/wagtailnews | wagtailnews/views/chooser.py | get_newsitem_model | def get_newsitem_model(model_string):
"""
Get the NewsItem model from a model string. Raises ValueError if the model
string is invalid, or references a model that is not a NewsItem.
"""
try:
NewsItem = apps.get_model(model_string)
assert issubclass(NewsItem, AbstractNewsItem)
exc... | python | def get_newsitem_model(model_string):
"""
Get the NewsItem model from a model string. Raises ValueError if the model
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"""
try:
NewsItem = apps.get_model(model_string)
assert issubclass(NewsItem, AbstractNewsItem)
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geometalab/pyGeoTile | pygeotile/point.py | Point.from_latitude_longitude | def from_latitude_longitude(cls, latitude=0.0, longitude=0.0):
"""Creates a point from lat/lon in WGS84"""
assert -180.0 <= longitude <= 180.0, 'Longitude needs to be a value between -180.0 and 180.0.'
assert -90.0 <= latitude <= 90.0, 'Latitude needs to be a value between -90.0 and 90.0.'
... | python | def from_latitude_longitude(cls, latitude=0.0, longitude=0.0):
"""Creates a point from lat/lon in WGS84"""
assert -180.0 <= longitude <= 180.0, 'Longitude needs to be a value between -180.0 and 180.0.'
assert -90.0 <= latitude <= 90.0, 'Latitude needs to be a value between -90.0 and 90.0.'
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geometalab/pyGeoTile | pygeotile/point.py | Point.from_pixel | def from_pixel(cls, pixel_x=0, pixel_y=0, zoom=None):
"""Creates a point from pixels X Y Z (zoom) in pyramid"""
max_pixel = (2 ** zoom) * TILE_SIZE
assert 0 <= pixel_x <= max_pixel, 'Point X needs to be a value between 0 and (2^zoom) * 256.'
assert 0 <= pixel_y <= max_pixel, 'Point Y nee... | python | def from_pixel(cls, pixel_x=0, pixel_y=0, zoom=None):
"""Creates a point from pixels X Y Z (zoom) in pyramid"""
max_pixel = (2 ** zoom) * TILE_SIZE
assert 0 <= pixel_x <= max_pixel, 'Point X needs to be a value between 0 and (2^zoom) * 256.'
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geometalab/pyGeoTile | pygeotile/point.py | Point.from_meters | def from_meters(cls, meter_x=0.0, meter_y=0.0):
"""Creates a point from X Y Z (zoom) meters in Spherical Mercator EPSG:900913"""
assert -ORIGIN_SHIFT <= meter_x <= ORIGIN_SHIFT, \
'Meter X needs to be a value between -{0} and {0}.'.format(ORIGIN_SHIFT)
assert -ORIGIN_SHIFT <= meter_y... | python | def from_meters(cls, meter_x=0.0, meter_y=0.0):
"""Creates a point from X Y Z (zoom) meters in Spherical Mercator EPSG:900913"""
assert -ORIGIN_SHIFT <= meter_x <= ORIGIN_SHIFT, \
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assert -ORIGIN_SHIFT <= meter_y... | [
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geometalab/pyGeoTile | pygeotile/point.py | Point.pixels | def pixels(self, zoom=None):
"""Gets pixels of the EPSG:4326 pyramid by a specific zoom, converted from lat/lon in WGS84"""
meter_x, meter_y = self.meters
pixel_x = (meter_x + ORIGIN_SHIFT) / resolution(zoom=zoom)
pixel_y = (meter_y - ORIGIN_SHIFT) / resolution(zoom=zoom)
return ... | python | def pixels(self, zoom=None):
"""Gets pixels of the EPSG:4326 pyramid by a specific zoom, converted from lat/lon in WGS84"""
meter_x, meter_y = self.meters
pixel_x = (meter_x + ORIGIN_SHIFT) / resolution(zoom=zoom)
pixel_y = (meter_y - ORIGIN_SHIFT) / resolution(zoom=zoom)
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geometalab/pyGeoTile | pygeotile/point.py | Point.meters | def meters(self):
"""Gets the XY meters in Spherical Mercator EPSG:900913, converted from lat/lon in WGS84"""
latitude, longitude = self.latitude_longitude
meter_x = longitude * ORIGIN_SHIFT / 180.0
meter_y = math.log(math.tan((90.0 + latitude) * math.pi / 360.0)) / (math.pi / 180.0)
... | python | def meters(self):
"""Gets the XY meters in Spherical Mercator EPSG:900913, converted from lat/lon in WGS84"""
latitude, longitude = self.latitude_longitude
meter_x = longitude * ORIGIN_SHIFT / 180.0
meter_y = math.log(math.tan((90.0 + latitude) * math.pi / 360.0)) / (math.pi / 180.0)
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geometalab/pyGeoTile | pygeotile/tile.py | Tile.from_quad_tree | def from_quad_tree(cls, quad_tree):
"""Creates a tile from a Microsoft QuadTree"""
assert bool(re.match('^[0-3]*$', quad_tree)), 'QuadTree value can only consists of the digits 0, 1, 2 and 3.'
zoom = len(str(quad_tree))
offset = int(math.pow(2, zoom)) - 1
google_x, google_y = [re... | python | def from_quad_tree(cls, quad_tree):
"""Creates a tile from a Microsoft QuadTree"""
assert bool(re.match('^[0-3]*$', quad_tree)), 'QuadTree value can only consists of the digits 0, 1, 2 and 3.'
zoom = len(str(quad_tree))
offset = int(math.pow(2, zoom)) - 1
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geometalab/pyGeoTile | pygeotile/tile.py | Tile.from_tms | def from_tms(cls, tms_x, tms_y, zoom):
"""Creates a tile from Tile Map Service (TMS) X Y and zoom"""
max_tile = (2 ** zoom) - 1
assert 0 <= tms_x <= max_tile, 'TMS X needs to be a value between 0 and (2^zoom) -1.'
assert 0 <= tms_y <= max_tile, 'TMS Y needs to be a value between 0 and (2... | python | def from_tms(cls, tms_x, tms_y, zoom):
"""Creates a tile from Tile Map Service (TMS) X Y and zoom"""
max_tile = (2 ** zoom) - 1
assert 0 <= tms_x <= max_tile, 'TMS X needs to be a value between 0 and (2^zoom) -1.'
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geometalab/pyGeoTile | pygeotile/tile.py | Tile.from_google | def from_google(cls, google_x, google_y, zoom):
"""Creates a tile from Google format X Y and zoom"""
max_tile = (2 ** zoom) - 1
assert 0 <= google_x <= max_tile, 'Google X needs to be a value between 0 and (2^zoom) -1.'
assert 0 <= google_y <= max_tile, 'Google Y needs to be a value betw... | python | def from_google(cls, google_x, google_y, zoom):
"""Creates a tile from Google format X Y and zoom"""
max_tile = (2 ** zoom) - 1
assert 0 <= google_x <= max_tile, 'Google X needs to be a value between 0 and (2^zoom) -1.'
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geometalab/pyGeoTile | pygeotile/tile.py | Tile.for_point | def for_point(cls, point, zoom):
"""Creates a tile for given point"""
latitude, longitude = point.latitude_longitude
return cls.for_latitude_longitude(latitude=latitude, longitude=longitude, zoom=zoom) | python | def for_point(cls, point, zoom):
"""Creates a tile for given point"""
latitude, longitude = point.latitude_longitude
return cls.for_latitude_longitude(latitude=latitude, longitude=longitude, zoom=zoom) | [
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geometalab/pyGeoTile | pygeotile/tile.py | Tile.for_pixels | def for_pixels(cls, pixel_x, pixel_y, zoom):
"""Creates a tile from pixels X Y Z (zoom) in pyramid"""
tms_x = int(math.ceil(pixel_x / float(TILE_SIZE)) - 1)
tms_y = int(math.ceil(pixel_y / float(TILE_SIZE)) - 1)
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"""Creates a tile from pixels X Y Z (zoom) in pyramid"""
tms_x = int(math.ceil(pixel_x / float(TILE_SIZE)) - 1)
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geometalab/pyGeoTile | pygeotile/tile.py | Tile.for_meters | def for_meters(cls, meter_x, meter_y, zoom):
"""Creates a tile from X Y meters in Spherical Mercator EPSG:900913"""
point = Point.from_meters(meter_x=meter_x, meter_y=meter_y)
pixel_x, pixel_y = point.pixels(zoom=zoom)
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"""Creates a tile from X Y meters in Spherical Mercator EPSG:900913"""
point = Point.from_meters(meter_x=meter_x, meter_y=meter_y)
pixel_x, pixel_y = point.pixels(zoom=zoom)
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david-cortes/costsensitive | costsensitive/__init__.py | WeightedOneVsRest.fit | def fit(self, X, C):
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Fit one regressor per class
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Parameters
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this option requires the ixmp package as a dependency
kwargs: arguments passed to ixmp.TimeSeries.timeseries()
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"""Read timeseries data from an ixmp object
Parameters
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ix: ixmp.TimeSeries or ixmp.Scenario
this option requires the ixmp package as a dependency
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pkg : imported package object
msg : string
Message to show to user with error_type
error_type : python error class
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Parameters
----------
writer: pandas.ExcelWriter
an instance of a pandas ExcelWriter
name: string
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IAMconsortium/pyam | pyam/utils.py | read_pandas | def read_pandas(fname, *args, **kwargs):
"""Read a file and return a pd.DataFrame"""
if not os.path.exists(fname):
raise ValueError('no data file `{}` found!'.format(fname))
if fname.endswith('csv'):
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else:
xl = pd.ExcelFile(fname)
... | python | def read_pandas(fname, *args, **kwargs):
"""Read a file and return a pd.DataFrame"""
if not os.path.exists(fname):
raise ValueError('no data file `{}` found!'.format(fname))
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IAMconsortium/pyam | pyam/utils.py | read_file | def read_file(fname, *args, **kwargs):
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"""
if not isstr(fname):
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IAMconsortium/pyam | pyam/utils.py | format_data | def format_data(df, **kwargs):
"""Convert a `pd.Dataframe` or `pd.Series` to the required format"""
if isinstance(df, pd.Series):
df = df.to_frame()
# Check for R-style year columns, converting where necessary
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"""Convert a `pd.Dataframe` or `pd.Series` to the required format"""
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remove leading `s` from any variable in `data`
level : int or str, default None
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IAMconsortium/pyam | pyam/utils.py | pattern_match | def pattern_match(data, values, level=None, regexp=False, has_nan=True):
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IAMconsortium/pyam | pyam/utils.py | _escape_regexp | def _escape_regexp(s):
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.replace('(', '\(')
.replace(')', '\)')
.r... | python | def _escape_regexp(s):
"""escape characters with specific regexp use"""
return (
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.replace('|', '\\|')
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IAMconsortium/pyam | pyam/utils.py | years_match | def years_match(data, years):
"""
matching of year columns for data filtering
"""
years = [years] if isinstance(years, int) else years
dt = datetime.datetime
if isinstance(years, dt) or isinstance(years[0], dt):
error_msg = "`year` can only be filtered with ints or lists of ints"
... | python | def years_match(data, years):
"""
matching of year columns for data filtering
"""
years = [years] if isinstance(years, int) else years
dt = datetime.datetime
if isinstance(years, dt) or isinstance(years[0], dt):
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IAMconsortium/pyam | pyam/utils.py | hour_match | def hour_match(data, hours):
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matching of days in time columns for data filtering
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matching of days in time columns for data filtering
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IAMconsortium/pyam | pyam/core.py | _aggregate | def _aggregate(df, by):
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IAMconsortium/pyam | pyam/core.py | _check_rows | def _check_rows(rows, check, in_range=True, return_test='any'):
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IAMconsortium/pyam | pyam/core.py | _apply_criteria | def _apply_criteria(df, criteria, **kwargs):
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for var, check in criteria.items():
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IAMconsortium/pyam | pyam/core.py | validate | def validate(df, criteria={}, exclude_on_fail=False, **kwargs):
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Parameters
----------
df: IamDataFrame instance
args: see `IamDataFrame.validate()` for details
kwargs: passed to `df.filter()`
"""
fdf = df.filter(**kwargs)
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args: see `IamDataFrame.validate()` for details
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IAMconsortium/pyam | pyam/core.py | require_variable | def require_variable(df, variable, unit=None, year=None, exclude_on_fail=False,
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IAMconsortium/pyam | pyam/core.py | categorize | def categorize(df, name, value, criteria,
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df: IamDataFrame instance
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IAMconsortium/pyam | pyam/core.py | filter_by_meta | def filter_by_meta(data, df, join_meta=False, **kwargs):
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Parameters
----------
data: pd.DataFrame instance
DataFrame to which meta columns are to be joined,
index or columns must include `['model', 'scenario']`
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IAMconsortium/pyam | pyam/core.py | compare | def compare(left, right, left_label='left', right_label='right',
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Parameters
----------
left, right: IamDataFrames
the IamDataFrames to be compared
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IAMconsortium/pyam | pyam/core.py | concat | def concat(dfs):
"""Concatenate a series of `pyam.IamDataFrame`-like objects together"""
if isstr(dfs) or not hasattr(dfs, '__iter__'):
msg = 'Argument must be a non-string iterable (e.g., list or tuple)'
raise TypeError(msg)
_df = None
for df in dfs:
df = df if isinstance(df, I... | python | def concat(dfs):
"""Concatenate a series of `pyam.IamDataFrame`-like objects together"""
if isstr(dfs) or not hasattr(dfs, '__iter__'):
msg = 'Argument must be a non-string iterable (e.g., list or tuple)'
raise TypeError(msg)
_df = None
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.variables | def variables(self, include_units=False):
"""Get a list of variables
Parameters
----------
include_units: boolean, default False
include the units
"""
if include_units:
return self.data[['variable', 'unit']].drop_duplicates()\
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"""Get a list of variables
Parameters
----------
include_units: boolean, default False
include the units
"""
if include_units:
return self.data[['variable', 'unit']].drop_duplicates()\
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.append | def append(self, other, ignore_meta_conflict=False, inplace=False,
**kwargs):
"""Append any castable object to this IamDataFrame.
Columns in `other.meta` that are not in `self.meta` are always merged,
duplicate region-variable-unit-year rows raise a ValueError.
Parameters... | python | def append(self, other, ignore_meta_conflict=False, inplace=False,
**kwargs):
"""Append any castable object to this IamDataFrame.
Columns in `other.meta` that are not in `self.meta` are always merged,
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.pivot_table | def pivot_table(self, index, columns, values='value',
aggfunc='count', fill_value=None, style=None):
"""Returns a pivot table
Parameters
----------
index: str or list of strings
rows for Pivot table
columns: str or list of strings
colu... | python | def pivot_table(self, index, columns, values='value',
aggfunc='count', fill_value=None, style=None):
"""Returns a pivot table
Parameters
----------
index: str or list of strings
rows for Pivot table
columns: str or list of strings
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.interpolate | def interpolate(self, year):
"""Interpolate missing values in timeseries (linear interpolation)
Parameters
----------
year: int
year to be interpolated
"""
df = self.pivot_table(index=IAMC_IDX, columns=['year'],
values='value', ... | python | def interpolate(self, year):
"""Interpolate missing values in timeseries (linear interpolation)
Parameters
----------
year: int
year to be interpolated
"""
df = self.pivot_table(index=IAMC_IDX, columns=['year'],
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.as_pandas | def as_pandas(self, with_metadata=False):
"""Return this as a pd.DataFrame
Parameters
----------
with_metadata : bool, default False or dict
if True, join data with all meta columns; if a dict, discover
meaningful meta columns from values (in key-value)
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"""Return this as a pd.DataFrame
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IAMconsortium/pyam | pyam/core.py | IamDataFrame._discover_meta_cols | def _discover_meta_cols(self, **kwargs):
"""Return the subset of `kwargs` values (not keys!) matching
a `meta` column name"""
cols = set(['exclude'])
for arg, value in kwargs.items():
if isstr(value) and value in self.meta.columns:
cols.add(value)
retu... | python | def _discover_meta_cols(self, **kwargs):
"""Return the subset of `kwargs` values (not keys!) matching
a `meta` column name"""
cols = set(['exclude'])
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.timeseries | def timeseries(self, iamc_index=False):
"""Returns a pd.DataFrame in wide format (years or timedate as columns)
Parameters
----------
iamc_index: bool, default False
if True, use `['model', 'scenario', 'region', 'variable', 'unit']`;
else, use all `data` columns
... | python | def timeseries(self, iamc_index=False):
"""Returns a pd.DataFrame in wide format (years or timedate as columns)
Parameters
----------
iamc_index: bool, default False
if True, use `['model', 'scenario', 'region', 'variable', 'unit']`;
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.set_meta | def set_meta(self, meta, name=None, index=None):
"""Add metadata columns as pd.Series, list or value (int/float/str)
Parameters
----------
meta: pd.Series, list, int, float or str
column to be added to metadata
(by `['model', 'scenario']` index if possible)
... | python | def set_meta(self, meta, name=None, index=None):
"""Add metadata columns as pd.Series, list or value (int/float/str)
Parameters
----------
meta: pd.Series, list, int, float or str
column to be added to metadata
(by `['model', 'scenario']` index if possible)
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.categorize | def categorize(self, name, value, criteria,
color=None, marker=None, linestyle=None):
"""Assign scenarios to a category according to specific criteria
or display the category assignment
Parameters
----------
name: str
category column name
v... | python | def categorize(self, name, value, criteria,
color=None, marker=None, linestyle=None):
"""Assign scenarios to a category according to specific criteria
or display the category assignment
Parameters
----------
name: str
category column name
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IAMconsortium/pyam | pyam/core.py | IamDataFrame._new_meta_column | def _new_meta_column(self, name):
"""Add a column to meta if it doesn't exist, set to value `np.nan`"""
if name is None:
raise ValueError('cannot add a meta column `{}`'.format(name))
if name not in self.meta:
self.meta[name] = np.nan | python | def _new_meta_column(self, name):
"""Add a column to meta if it doesn't exist, set to value `np.nan`"""
if name is None:
raise ValueError('cannot add a meta column `{}`'.format(name))
if name not in self.meta:
self.meta[name] = np.nan | [
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.require_variable | def require_variable(self, variable, unit=None, year=None,
exclude_on_fail=False):
"""Check whether all scenarios have a required variable
Parameters
----------
variable: str
required variable
unit: str, default None
name of unit ... | python | def require_variable(self, variable, unit=None, year=None,
exclude_on_fail=False):
"""Check whether all scenarios have a required variable
Parameters
----------
variable: str
required variable
unit: str, default None
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IAMconsortium/pyam | pyam/core.py | IamDataFrame.validate | def validate(self, criteria={}, exclude_on_fail=False):
"""Validate scenarios using criteria on timeseries values
Parameters
----------
criteria: dict
dictionary with variable keys and check values
('up' and 'lo' for respective bounds, 'year' for years)
ex... | python | def validate(self, criteria={}, exclude_on_fail=False):
"""Validate scenarios using criteria on timeseries values
Parameters
----------
criteria: dict
dictionary with variable keys and check values
('up' and 'lo' for respective bounds, 'year' for years)
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