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train | cublasZgemm | Matrix-matrix product for complex general matrix. | hebel/pycuda_ops/cublas.py | def cublasZgemm(handle, transa, transb, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Matrix-matrix product for complex general matrix.
"""
status = _libcublas.cublasZgemm_v2(handle,
_CUBLAS_OP[transa],
_CUBLAS_OP[trans... | def cublasZgemm(handle, transa, transb, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Matrix-matrix product for complex general matrix.
"""
status = _libcublas.cublasZgemm_v2(handle,
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train | cublasSsymm | Matrix-matrix product for symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasSsymm(handle, side, uplo, m, n, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Matrix-matrix product for symmetric matrix.
"""
status = _libcublas.cublasSsymm_v2(handle,
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"""
Matrix-matrix product for symmetric matrix.
"""
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train | cublasDsymm | Matrix-matrix product for real symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasDsymm(handle, side, uplo, m, n, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Matrix-matrix product for real symmetric matrix.
"""
status = _libcublas.cublasDsymm_v2(handle,
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_CUBLAS_FILL_M... | def cublasDsymm(handle, side, uplo, m, n, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Matrix-matrix product for real symmetric matrix.
"""
status = _libcublas.cublasDsymm_v2(handle,
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train | cublasCsymm | Matrix-matrix product for complex symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasCsymm(handle, side, uplo, m, n, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Matrix-matrix product for complex symmetric matrix.
"""
status = _libcublas.cublasCsymm_v2(handle,
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"""
Matrix-matrix product for complex symmetric matrix.
"""
status = _libcublas.cublasCsymm_v2(handle,
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train | cublasSsyrk | Rank-k operation on real symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasSsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on real symmetric matrix.
"""
status = _libcublas.cublasSsyrk_v2(handle,
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_CUBLAS_OP[trans],
... | def cublasSsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on real symmetric matrix.
"""
status = _libcublas.cublasSsyrk_v2(handle,
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train | cublasDsyrk | Rank-k operation on real symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasDsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on real symmetric matrix.
"""
status = _libcublas.cublasDsyrk_v2(handle,
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... | def cublasDsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on real symmetric matrix.
"""
status = _libcublas.cublasDsyrk_v2(handle,
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train | cublasZsyrk | Rank-k operation on complex symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasZsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on complex symmetric matrix.
"""
status = _libcublas.cublasZsyrk_v2(handle,
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... | def cublasZsyrk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on complex symmetric matrix.
"""
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train | cublasSsyr2k | Rank-2k operation on real symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasSsyr2k(handle, uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Rank-2k operation on real symmetric matrix.
"""
status = _libcublas.cublasSsyr2k_v2(handle,
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_CUBLAS_OP[tra... | def cublasSsyr2k(handle, uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc):
"""
Rank-2k operation on real symmetric matrix.
"""
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train | cublasDsyr2k | Rank-2k operation on real symmetric matrix. | hebel/pycuda_ops/cublas.py | def cublasDsyr2k(handle, uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc):
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Rank-2k operation on real symmetric matrix.
"""
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"""
Rank-2k operation on real symmetric matrix.
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train | cublasStrmm | Matrix-matrix product for real triangular matrix. | hebel/pycuda_ops/cublas.py | def cublasStrmm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb, C, ldc):
"""
Matrix-matrix product for real triangular matrix.
"""
status = _libcublas.cublasStrmm_v2(handle,
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_CUBLA... | def cublasStrmm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb, C, ldc):
"""
Matrix-matrix product for real triangular matrix.
"""
status = _libcublas.cublasStrmm_v2(handle,
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train | cublasZtrmm | Matrix-matrix product for complex triangular matrix. | hebel/pycuda_ops/cublas.py | def cublasZtrmm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb, C, ldc):
"""
Matrix-matrix product for complex triangular matrix.
"""
status = _libcublas.cublasZtrmm_v2(handle,
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_C... | def cublasZtrmm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb, C, ldc):
"""
Matrix-matrix product for complex triangular matrix.
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status = _libcublas.cublasZtrmm_v2(handle,
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train | cublasStrsm | Solve a real triangular system with multiple right-hand sides. | hebel/pycuda_ops/cublas.py | def cublasStrsm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb):
"""
Solve a real triangular system with multiple right-hand sides.
"""
status = _libcublas.cublasStrsm_v2(handle,
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... | def cublasStrsm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb):
"""
Solve a real triangular system with multiple right-hand sides.
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train | cublasDtrsm | Solve a real triangular system with multiple right-hand sides. | hebel/pycuda_ops/cublas.py | def cublasDtrsm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb):
"""
Solve a real triangular system with multiple right-hand sides.
"""
status = _libcublas.cublasDtrsm_v2(handle,
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... | def cublasDtrsm(handle, side, uplo, trans, diag, m, n, alpha, A, lda, B, ldb):
"""
Solve a real triangular system with multiple right-hand sides.
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train | cublasZtrsm | Solve complex triangular system with multiple right-hand sides. | hebel/pycuda_ops/cublas.py | def cublasZtrsm(handle, side, uplo, transa, diag, m, n, alpha, A, lda, B, ldb):
"""
Solve complex triangular system with multiple right-hand sides.
"""
status = _libcublas.cublasZtrsm_v2(handle,
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... | def cublasZtrsm(handle, side, uplo, transa, diag, m, n, alpha, A, lda, B, ldb):
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Solve complex triangular system with multiple right-hand sides.
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train | cublasZherk | Rank-k operation on Hermitian matrix. | hebel/pycuda_ops/cublas.py | def cublasZherk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on Hermitian matrix.
"""
status = _libcublas.cublasZherk_v2(handle,
_CUBLAS_FILL_MODE[uplo],
_CUBLAS_OP[trans],
... | def cublasZherk(handle, uplo, trans, n, k, alpha, A, lda, beta, C, ldc):
"""
Rank-k operation on Hermitian matrix.
"""
status = _libcublas.cublasZherk_v2(handle,
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_CUBLAS_OP[trans],
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train | cublasCher2k | Rank-2k operation on Hermitian matrix. | hebel/pycuda_ops/cublas.py | def cublasCher2k(handle, uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc):
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Rank-2k operation on Hermitian matrix.
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train | cublasSdgmm | Matrix-diagonal matrix product for real general matrix. | hebel/pycuda_ops/cublas.py | def cublasSdgmm(handle, mode, m, n, A, lda, x, incx, C, ldc):
"""
Matrix-diagonal matrix product for real general matrix.
"""
status = _libcublas.cublasSdgmm(handle,
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Matrix-diagonal matrix product for real general matrix.
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status = _libcublas.cublasSdgmm(handle,
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train | load_EROS_lc | Read an EROS light curve and return its data.
Parameters
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filename : str, optional
A light-curve filename.
Returns
-------
dates : numpy.ndarray
An array of dates.
magnitudes : numpy.ndarray
An array of magnitudes.
errors : numpy.ndarray
An arr... | upsilon/datasets/base.py | def load_EROS_lc(filename='lm0010n22323.time'):
"""
Read an EROS light curve and return its data.
Parameters
----------
filename : str, optional
A light-curve filename.
Returns
-------
dates : numpy.ndarray
An array of dates.
magnitudes : numpy.ndarray
An ar... | def load_EROS_lc(filename='lm0010n22323.time'):
"""
Read an EROS light curve and return its data.
Parameters
----------
filename : str, optional
A light-curve filename.
Returns
-------
dates : numpy.ndarray
An array of dates.
magnitudes : numpy.ndarray
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train | load_rf_model | Return the UPSILoN random forests classifier.
The classifier is trained using OGLE and EROS periodic variables
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Returns
-------
clf : sklearn.ensemble.RandomForestClassifier
The UPSILoN random forests classifier. | upsilon/datasets/base.py | def load_rf_model():
"""
Return the UPSILoN random forests classifier.
The classifier is trained using OGLE and EROS periodic variables
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Returns
-------
clf : sklearn.ensemble.RandomForestClassifier
The UPSILoN random forests classifier.
"""
import gzip
... | def load_rf_model():
"""
Return the UPSILoN random forests classifier.
The classifier is trained using OGLE and EROS periodic variables
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Returns
-------
clf : sklearn.ensemble.RandomForestClassifier
The UPSILoN random forests classifier.
"""
import gzip
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train | sample_dropout_mask | Samples a dropout mask and applies it in place | hebel/pycuda_ops/elementwise.py | def sample_dropout_mask(x, dropout_probability=.5, columns=None, stream=None, target=None,
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""" Samples a dropout mask and applies it in place"""
assert x.flags.c_contiguous
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""" Samples a dropout mask and applies it in place"""
assert x.flags.c_contiguous
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assert len(columns) == 2
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train | reads | Load but don't evaluate a GCL expression from a string. | gcl/__init__.py | def reads(s, filename=None, loader=None, implicit_tuple=True, allow_errors=False):
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return ast.reads(s,
filename=filename or '<input>',
loader=loader or default_loader,
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allow_errors=allow_errors) | def reads(s, filename=None, loader=None, implicit_tuple=True, allow_errors=False):
"""Load but don't evaluate a GCL expression from a string."""
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train | read | Load but don't evaluate a GCL expression from a file. | gcl/__init__.py | def read(filename, loader=None, implicit_tuple=True, allow_errors=False):
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train | loads | Load and evaluate a GCL expression from a string. | gcl/__init__.py | def loads(s, filename=None, loader=None, implicit_tuple=True, env={}, schema=None):
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train | load | Load and evaluate a GCL expression from a file. | gcl/__init__.py | def load(filename, loader=None, implicit_tuple=True, env={}, schema=None):
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train | linear_scheduler_up | Increases linearly and then stays flat | hebel/schedulers.py | def linear_scheduler_up(init_value, target_value, duration):
""" Increases linearly and then stays flat """
value = init_value
t = 0
while True:
yield value
t += 1
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value = init_value + t * (target_value - init_value) / duration
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t += 1
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value = init_value + t * (target_value - init_value) / duration
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train | linear_scheduler_up_down | Increases linearly to target_value, stays at target_value until
t_decrease and then decreases linearly | hebel/schedulers.py | def linear_scheduler_up_down(init_value, target_value, final_value,
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train | load | Loads a YAML configuration from a string or file-like object.
Parameters
----------
stream : str or object
Either a string containing valid YAML or a file-like object
supporting the .read() interface.
overrides : dict, optional
A dictionary containing overrides to apply. The loc... | hebel/config.py | def load(stream, overrides=None, **kwargs):
"""
Loads a YAML configuration from a string or file-like object.
Parameters
----------
stream : str or object
Either a string containing valid YAML or a file-like object
supporting the .read() interface.
overrides : dict, optional
... | def load(stream, overrides=None, **kwargs):
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Loads a YAML configuration from a string or file-like object.
Parameters
----------
stream : str or object
Either a string containing valid YAML or a file-like object
supporting the .read() interface.
overrides : dict, optional
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train | load_path | Convenience function for loading a YAML configuration from a file.
Parameters
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path : str
The path to the file to load on disk.
overrides : dict, optional
A dictionary containing overrides to apply. The location of
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Convenience function for loading a YAML configuration from a file.
Parameters
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The path to the file to load on disk.
overrides : dict, optional
A dictionary containing overrides to apply. The location of
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Convenience function for loading a YAML configuration from a file.
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The path to the file to load on disk.
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train | handle_overrides | Handle any overrides for this model configuration.
Parameters
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graph : dict or object
A dictionary (or an ObjectProxy) containing the object graph
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overrides : dict
A dictionary containing overrides to apply. The location of
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"""
Handle any overrides for this model configuration.
Parameters
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graph : dict or object
A dictionary (or an ObjectProxy) containing the object graph
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overrides : dict
A dictionary containing over... | def handle_overrides(graph, overrides):
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Handle any overrides for this model configuration.
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A dictionary (or an ObjectProxy) containing the object graph
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A dictionary (or an ObjectProxy) containing the object graph
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"""
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A dictionary (or an ObjectProxy) containing the object graph
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train | multi_constructor | Constructor function passed to PyYAML telling it how to construct
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Constructor function passed to PyYAML telling it how to construct
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train | multi_constructor_pkl | Constructor function passed to PyYAML telling it how to load
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train | initialize | Initialize the configuration system by installing YAML handlers.
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"""
Initialize the configuration system by installing YAML handlers.
Automatically done on first call to load() specified in this file.
"""
global is_initialized
# Add the custom multi-constructor
yaml.add_multi_constructor('!obj:', multi_constructor)
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train | ObjectProxy.instantiate | Instantiate this object with the supplied parameters in `self.kwds`,
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"""
Instantiate this object with the supplied parameters in `self.kwds`,
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"""
if self.instance is None:
self.instance = checked_call(self.cls, self.kwds)
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train | LinearRegressionLayer.feed_forward | Propagate forward through the layer.
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Inpute data to compute activations for.
prediction : bool, optional
Whether to use prediction model. Only relevant when using
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train | fasper | Given abscissas x (which need not be equally spaced) and ordinates
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train | Tuple.get_no_validate | Return an item without validating the schema. | gcl/runtime.py | def get_no_validate(self, key):
"""Return an item without validating the schema."""
x, env = self.get_thunk_env(key)
# Check if this is a Thunk that needs to be lazily evaluated before we
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train | Tuple.env | Return an environment that will look up in current_scope for keys in
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train | Tuple.get_thunk_env | Return the thunk AND environment for validating it in for the given key.
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environment bound on retrieval, that will be done here. | gcl/runtime.py | def get_thunk_env(self, k):
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train | Tuple.attach_schema | Add a tuple schema to this object (externally imposed) | gcl/runtime.py | def attach_schema(self, schem):
"""Add a tuple schema to this object (externally imposed)"""
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train | Tuple.get_schema_spec | Return the evaluated schema expression from a subkey. | gcl/runtime.py | def get_schema_spec(self, key):
"""Return the evaluated schema expression from a subkey."""
member_node = self._ast_node.member.get(key, None)
if not member_node:
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train | Tuple.get_required_fields | Return the names of fields that are required according to the schema. | gcl/runtime.py | def get_required_fields(self):
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return [m.name for m in self._ast_node.members if m.member_schema.required] | def get_required_fields(self):
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train | CompositeTuple.get_member_node | Return the AST node for the given member, from the first tuple that serves it. | gcl/runtime.py | def get_member_node(self, key):
"""Return the AST node for the given member, from the first tuple that serves it."""
for tup, _ in self.lookups:
if key in tup:
return tup.get_member_node(key)
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train | CompositeTuple.exportable_keys | Return a list of keys that are exportable from this tuple.
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train | OnDiskFiles.resolve | Search the filesystem. | gcl/runtime.py | def resolve(self, current_file, rel_path):
"""Search the filesystem."""
search_path = [path.dirname(current_file)] + self.search_path
target_path = None
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train | InMemoryFiles.resolve | Search the filesystem. | gcl/runtime.py | def resolve(self, current_file, rel_path):
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train | check_call_arguments | Check the call signature against a dictionary of proposed arguments,
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Parameters
----------
to_call : class or callable
Function or class to examine (in the case of classes, the
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"""
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----------
to_call : class or callable
Function or class to examine (in the case of classes, the
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Check the call signature against a dictionary of proposed arguments,
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to_call : class or callable
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train | predict | Return label and probability estimated.
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rf_model : sklearn.ensemble.RandomForestClassifier
The UPSILoN random forests model.
features : array_like
A list of features estimated by UPSILoN.
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Return label and probability estimated.
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rf_model : sklearn.ensemble.RandomForestClassifier
The UPSILoN random forests model.
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A list of features estimated by UPSILoN.
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train | fmt | fmt(string, [tuple]) -> string
Interpolate a string, replacing {patterns} with the variables with the same
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train | compose_all | Compose all given tuples together. | gcl/functions.py | def compose_all(tups):
"""Compose all given tuples together."""
from . import ast # I weep for humanity
return functools.reduce(lambda x, y: x.compose(y), map(ast.make_tuple, tups), ast.make_tuple({})) | def compose_all(tups):
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train | has_key | has(tuple, string) -> bool
Return whether a given tuple has a key and the key is bound. | gcl/functions.py | def has_key(tup, key):
"""has(tuple, string) -> bool
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train | flatten | flatten([[A]]) -> [A]
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"""
ret = []
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train | extract_dark | Extract superdark data from ``DARKFILE`` or ``DRKCFILE``.
Parameters
----------
prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
This is only used to extract subarray data.
Returns
-------
dark : ndarray or `None`
Super... | acstools/utils_calib.py | def extract_dark(prihdr, scihdu):
"""Extract superdark data from ``DARKFILE`` or ``DRKCFILE``.
Parameters
----------
prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
This is only used to extract subarray data.
Returns
-------
... | def extract_dark(prihdr, scihdu):
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----------
prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
This is only used to extract subarray data.
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-------
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train | extract_flash | Extract postflash data from ``FLSHFILE``.
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prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
This is only used to extract subarray data.
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Parameters
----------
prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
This is only used to extract subarray data.
Returns
-------
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FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
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train | extract_flatfield | Extract flatfield data from ``PFLTFILE``.
Parameters
----------
prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
This is only used to extract subarray data.
Returns
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"""Extract flatfield data from ``PFLTFILE``.
Parameters
----------
prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
This is only used to extract subarray data.
Returns
-------
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prihdr : obj
FITS primary header HDU.
scihdu : obj
Extension HDU of the science image.
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train | from_irafpath | Resolve IRAF path like ``jref$`` into actual file path.
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irafpath : str
Path containing IRAF syntax.
Returns
-------
realpath : str
Actual file path. If input does not follow ``path$filename``
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"""Resolve IRAF path like ``jref$`` into actual file path.
Parameters
----------
irafpath : str
Path containing IRAF syntax.
Returns
-------
realpath : str
Actual file path. If input does not follow ``path$filename``
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irafpath : str
Path containing IRAF syntax.
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train | extract_ref | Extract section of the reference image that
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scihdu, refhdu : obj
Extension HDU's of the science and reference image,
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... | acstools/utils_calib.py | def extract_ref(scihdu, refhdu):
"""Extract section of the reference image that
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This only returns a view, not a copy of the
reference image's array.
Parameters
----------
scihdu, refhdu : obj
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train | find_line | Obtain bin factors and corner location to extract
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train | get_corner | Obtain bin and corner information for a subarray.
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"""Obtain bin and corner information for a subarray.
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are extracted from the given extension header and converted
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... | def get_corner(hdr, rsize=1):
"""Obtain bin and corner information for a subarray.
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train | from_lt | Compute the corner location and pixel size in units
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Reference pixel size. Usually 1.
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Reference pixel size. Usually 1.
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root : str
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train | check_overscan | Check image for bias columns.
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Starting column of the readout in detector coordinates.
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Number of columns in the readout.
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Total prescan pixels for a single amplifier on a detector.
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"""Check image for bias columns.
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xstart : int
Starting column of the readout in detector coordinates.
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Number of columns in the readout.
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Starting column of the readout in detector coordinates.
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train | ModelAdminMiddleware.process_request | Ignore unnecessary actions for static file requests, posts, or ajax
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Ignore unnecessary actions for static file requests, posts, or ajax
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train | acs2d | r"""
Run the acs2d.e executable as from the shell.
Output is automatically named based on input suffix:
+--------------------+----------------+------------------------------+
| INPUT | OUTPUT | EXPECTED DATA |
+====================+================+=... | acstools/acs2d.py | def acs2d(input, exec_path='', time_stamps=False, verbose=False, quiet=False,
exe_args=None):
r"""
Run the acs2d.e executable as from the shell.
Output is automatically named based on input suffix:
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Run the acs2d.e executable as from the shell.
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train | Query._check_inputs | Check the inputs to ensure they are valid.
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status : bool
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Returns
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status : bool
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"""
valid_detector = True
valid_filter = True
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train | Query._check_date | Convenience method for determining if the input date is valid.
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Returns
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fmt : str
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----... | def _check_date(self, fmt='%Y-%m-%d'):
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The format of the date string. The default is ``%Y-%m-%d``, which
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Instantiates a class-based view to provide a view that allows a parent
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Instantiates a class-based view to provide 'edit' functionality for the
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Instantiates a class-based view to provide 'delete confirmation'
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Instantiates a class-based view that redirects to Wagtail's 'unpublish'
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Utilised by Wagtail's 'register_permissions' hook to allow permissions
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train | ModelAdminGroup.get_menu_item | Utilised by Wagtail's 'register_menu_item' hook to create a menu
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train | GroupMenuItem.is_shown | If there aren't any visible items in the submenu, don't bother to show
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train | run | TEAL interface for the `acscteforwardmodel` function. | acstools/acscteforwardmodel.py | def run(configobj=None):
"""
TEAL interface for the `acscteforwardmodel` function.
"""
acscteforwardmodel(configobj['input'],
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train | destripe_plus | r"""Calibrate post-SM4 ACS/WFC exposure(s) and use
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This takes a RAW image and generates a FLT file containing
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train | main | Command line driver. | acstools/acs_destripe_plus.py | def main():
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# Parse input parameters
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train | IndexView.get_search_results | Returns a tuple containing a queryset to implement the search,
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"""
# Apply keyword searches.
def construct_search(field_name):
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train | IndexView.get_filters_params | Returns all params except IGNORED_PARAMS | wagtailmodeladmin/views.py | def get_filters_params(self, params=None):
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params = self.params
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train | IndexView.get_ordering_field_columns | Returns an OrderedDict of ordering field column numbers and asc/desc | wagtailmodeladmin/views.py | def get_ordering_field_columns(self):
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train | InspectView.get_field_label | Return a label to display for a field | wagtailmodeladmin/views.py | def get_field_label(self, field_name, field=None):
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label = None
if field is not None:
label = getattr(field, 'verbose_name', None)
if label is None:
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train | InspectView.get_field_display_value | Return a display value for a field | wagtailmodeladmin/views.py | def get_field_display_value(self, field_name, field=None):
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"""
Firstly, check for a 'get_fieldname_display' property/method on
the model, and return the value of that, if present.
"""
val_funct = getattr(self.instance, 'get_%s_d... | def get_field_display_value(self, field_name, field=None):
""" Return a display value for a field """
"""
Firstly, check for a 'get_fieldname_display' property/method on
the model, and return the value of that, if present.
"""
val_funct = getattr(self.instance, 'get_%s_d... | [
"Return",
"a",
"display",
"value",
"for",
"a",
"field"
] | rkhleics/wagtailmodeladmin | python | https://github.com/rkhleics/wagtailmodeladmin/blob/7fddc853bab2ff3868b8c7a03329308c55f16358/wagtailmodeladmin/views.py#L743-L784 | [
"def",
"get_field_display_value",
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"\"\"\"\n Firstly, check for a 'get_fieldname_display' property/method on\n the model, and return the value of that, if present.\n \"\"\"",
"val_funct",
"=",
"get... | 7fddc853bab2ff3868b8c7a03329308c55f16358 |
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