pimlico.datatypes.arrays module

Wrappers around Numpy arrays and Scipy sparse matrices.

class NumpyArray(base_dir, pipeline, **kwargs)

Bases: pimlico.datatypes.files.NamedFileCollection

datatype_name = 'numpy_array'

filenames = ['array.npy']

array

get_software_dependencies()

Check that all software required to read this datatype is installed and locatable. This is separate to metadata config checks, so that you don’t need to satisfy the dependencies for all modules in order to be able to run one of them. You might, for example, want to run different modules on different machines. This is called when a module is about to be executed and each of the dependencies is checked.

Returns a list of instances of subclasses of :class:~pimlico.core.dependencies.base.SoftwareDependency, representing the libraries that this module depends on.

Take care when providing dependency classes that you don’t put any import statements at the top of the Python module that will make loading the dependency type itself dependent on runtime dependencies. You’ll want to run import checks by putting import statements within this method.

You should call the super method for checking superclass dependencies.

class NumpyArrayWriter(base_dir, additional_name=None)

Bases: pimlico.datatypes.base.PimlicoDatatypeWriter

set_array(array)

class ScipySparseMatrix(base_dir, pipeline, **kwargs)

Bases: pimlico.datatypes.base.PimlicoDatatype

Wrapper around Scipy sparse matrices. The matrix loaded is always in COO format – you probably want to convert to something else before using it. See scipy docs on sparse matrix conversions.

datatype_name = 'scipy_sparse_array'

filenames = ['array.mtx']

array

get_software_dependencies()

Check that all software required to read this datatype is installed and locatable. This is separate to metadata config checks, so that you don’t need to satisfy the dependencies for all modules in order to be able to run one of them. You might, for example, want to run different modules on different machines. This is called when a module is about to be executed and each of the dependencies is checked.

Returns a list of instances of subclasses of :class:~pimlico.core.dependencies.base.SoftwareDependency, representing the libraries that this module depends on.

Take care when providing dependency classes that you don’t put any import statements at the top of the Python module that will make loading the dependency type itself dependent on runtime dependencies. You’ll want to run import checks by putting import statements within this method.

You should call the super method for checking superclass dependencies.

class ScipySparseMatrixWriter(base_dir, additional_name=None)

Bases: pimlico.datatypes.base.PimlicoDatatypeWriter

set_matrix(mat)