def __new__(cls, *args, **kwargs):
if Docorator.__instance__ is None:
Docorator.__instance__ = DocstringProcessor()
# Add custom parameter type sections
a = DocstringProcessor.param_like_sections
Docorator.__instance__.param_like_sections = a + [
] # ["Attributes", "Settings"]
# Add custom text type sections
a = Docorator.__instance__.text_sections
Docorator.__instance__.text_sections = a + []
# Create a single list of all section types
a = Docorator.__instance__.param_like_sections
b = Docorator.__instance__.text_sections
Docorator.__instance__.all_sections = a + b
return Docorator.__instance__
"""Indet the given string"""
str_indent = ' ' * num
return str_indent + ('\n' + str_indent).join(text.splitlines())
def append_original_doc(parent, num=0):
"""Return an iterator that append the docstring of the given `parent`
function to the applied function"""
def func(func):
func.__doc__ = func.__doc__ and func.__doc__ + indent(
parent.__doc__, num)
return func
return func
_docstrings = DocstringProcessor()
_docstrings.get_sectionsf('DocstringProcessor.get_sections')(
dedent(DocstringProcessor.get_sections))
class PsyplotDocstringProcessor(DocstringProcessor):
"""
A :class:`docrep.DocstringProcessor` subclass with possible types section
"""
param_like_sections = DocstringProcessor.param_like_sections + [
'Possible types']
@_docstrings.dedent
def get_sections(self, s, base, sections=[
def __new__(cls, *args, **kwargs):
if Docorator.__instance__ is None:
Docorator.__instance__ = DocstringProcessor()
return Docorator.__instance__
d = DocstringProcessor(
adata=_adata,
img_container=_img_container,
copy=_copy,
copy_cont=_copy_cont,
numba_parallel=_numba_parallel,
seed=_seed,
n_perms=_n_perms,
img_layer=_img_layer,
feature_name=_feature_name,
yx=_yx,
feature_ret=_feature_ret,
size=_size,
cluster_key=_cluster_key,
spatial_key=_spatial_key,
conn_key=_conn_key,
plotting=_plotting,
cat_plotting=_cat_plotting,
plotting_returns=_plotting_returns,
parallelize=_parallelize,
channels=_channels,
segment_kwargs=_segment_kwargs,
ligrec_test_returns=_ligrec_test_returns,
corr_method=_corr_method,
heatmap_plotting=_heatmap_plotting,
custom_fn=_custom_fn,
as_array=_as_array,
layer_added=_layer_added,
)
import re
import os.path as osp
import six
import inspect
from docrep import DocstringProcessor
docstrings = DocstringProcessor()
def dir_contains(dirname, path, exists=True):
"""Check if a file of directory is contained in another.
Parameters
----------
dirname: str
The base directory that should contain `path`
path: str
The name of a directory or file that should be in `dirname`
exists: bool
If True, the `path` and `dirname` must exist
Notes
-----
`path` and `dirname` must be either both absolute or both relative
paths"""
if exists:
dirname = osp.abspath(dirname)
path = osp.abspath(path)
if six.PY2 or six.PY34:
return osp.exists(path) and osp.samefile(
osp.commonprefix([dirname, path]), dirname)
d = DocstringProcessor(
plotting=_plotting,
n_jobs=_n_jobs,
parallel=_parallel,
model=_model,
adata=_adata,
adata_ret=_adata_ret,
just_plots=_just_plots,
backward=_backward,
initial=_initial,
terminal=_terminal,
final=_final,
eigen=_eigen,
initial_or_terminal=f"{_initial} or {_terminal}",
n_cells=_n_cells,
fit=_fit,
copy=_copy,
density_correction=_density_correction,
time_range=_time_range,
time_ranges=_time_ranges,
velocity_mode=_velocity_mode,
velocity_backward_mode=_velocity_backward_mode,
velocity_backward_mode_high_lvl=_velocity_backward_mode_high_lvl,
model_callback=_model_callback,
genes=_genes,
softmax_scale=_softmax_scale,
time_mode=_time_mode,
write_to_adata=_write_to_adata,
)
R_sort = r"""The ordered top left part of shape `(m, m)` of the real Schur matrix of `P`.
The ordered real partial Schur matrix `R` of `P` fulfills
.. math:: \tilde{P} Q = Q R
with the ordered real matrix of dominant Schur vectors `Q`."""
eigenvalues_m = """An array of shape `(m,)` containing the `m` dominant eigenvalues of `P`."""
eigenvalues_k = """An array of shape `(k,)` containing the `k` dominant eigenvalues of `P`."""
d = DocstringProcessor(
P=P,
m=m,
k=k,
m_optimize=m_optimize,
z=z,
z_P=z_P,
method=method,
tol_krylov=tol_krylov,
eta=eta,
chi_ret=chi_ret,
rot_matrix_ret=rot_matrix_ret,
crispness_ret=crispness_ret,
Q_sort=Q_sort,
R_sort=R_sort,
eigenvalues_m=eigenvalues_m,
eigenvalues_k=eigenvalues_k,
)
- :attr:`omnipath.constants.InteractionDataset.LIGREC_EXTRA`
- :attr:`omnipath.constants.InteractionDataset.DOROTHEA`
- :attr:`omnipath.constants.InteractionDataset.TF_TARGET`
- :attr:`omnipath.constants.InteractionDataset.TF_MIRNA`
- :attr:`omnipath.constants.InteractionDataset.TF_REGULONS`
- :attr:`omnipath.constants.InteractionDataset.MIRNA_TARGET`
- :attr:`omnipath.constants.InteractionDataset.LNCRNA_MRNA`"""
_validate = """
Validate the ``value`` for the :attr:`param`.
Parameters
----------
value
Value to validate.
Returns
-------
The valid values."""
_query_resources = """
Return the available resources for this query."""
_query_params = """
Return the available values for each parameter, if available."""
d = DocstringProcessor(
general_get=_general_get,
interaction_datasets=_interactions_datasets,
validate=_validate,
query_params=_query_params,
query_resources=_query_resources,
)
d = DocstringProcessor(
plotting=_plotting,
n_jobs=_n_jobs,
parallel=_parallel,
model=_model,
adata=_adata,
adata_ret=_adata_ret,
just_plots=_just_plots,
backward=_backward,
initial=_initial,
terminal=_terminal,
eigen=_eigen,
initial_or_terminal=f"{_initial} or {_terminal}",
n_cells=_n_cells,
fit=_fit,
copy=_copy,
density_correction=_density_correction,
time_range=_time_range,
velocity_mode=_velocity_mode,
velocity_backward_mode=_velocity_backward_mode,
velocity_backward_mode_high_lvl=_velocity_backward_mode_high_lvl,
model_callback=_model_callback,
genes=_genes,
softmax_scale=_softmax_scale,
time_mode=_time_mode,
write_to_adata=_write_to_adata,
en_cutoff_p_thresh=_en_cutoff_p_thresh,
return_models=_return_models,
plots_or_returns_models=_plots_or_returns_models,
basis=_basis,
velocity_scheme=_velocity_scheme,
cond_num=_cond_num,
soft_scheme=_soft_scheme_fmt.format("", "", ""),
soft_scheme_kernel=_soft_scheme_fmt.format(
*([" Only used when `threshold_scheme='soft'`."] * 3)),
rw_ixs=_rw_ixs,
)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
"""
from docrep import DocstringProcessor
docstrings = DocstringProcessor()
def rgba2rgb(image, color=(255, 255, 255)):
"""Alpha composite an RGBA Image with a specified color.
Source: http://stackoverflow.com/a/9459208/284318
Parameters
----------
image: PIL.Image
The PIL RGBA Image object
color: tuple
The rgb color for the background
Returns