Density#

class Density(data, origin=None, sampling_rate=None, metadata={})[source]#

Bases: object

Abstract representation of N-dimensional densities.

Parameters:

dataarray_like: Array of densities.
originarray_like, optional: Origin of the coordinate system, zero by default.
sampling_ratearray_like, optional: Sampling rate along data axis, one by default.
metadatadict, optional: Dictionary with metadata information, empty by default.

Raises:

ValueError

If metadata is not a dictionary.

If sampling rate / origin is not defined for a single or all axes.

Examples

The following achieves the minimal definition of a Density instance

>>> import numpy as np
>>> from tme import Density
>>> data = np.random.rand(50,70,40)
>>> Density(data=data)

Optional parameters origin correspond to the coordinate system reference, sampling_rate to the spatial length per axis element, and metadata to a dictionary with supplementary information. By default, Density.origin is set to zero, Density.sampling_rate to one, and Density.metadata is an empty dictionary. If provided, origin and sampling_rate either need to be a single value

>>> Density(data=data, origin=0, sampling_rate=1)

be specified along each data axis

>>> Density(data=data, origin=(0, 0, 0), sampling_rate=(1.5, 1.1, 1.2))

or be a combination of both

>>> Density(data=data, origin=0, sampling_rate=(1.5, 1.1, 1.2))

Attributes

`Density.data`	Returns the value of `Density.data`.
`Density.empty`	Returns a copy of the class instance with all elements in `Density.data` set to zero.
`Density.metadata`	Returns the instance's `Density.metadata` attribute.
`Density.origin`	Returns the value of the instance's `Density.origin` attribute.
`Density.sampling_rate`	Returns the value of the instance's `Density.sampling_rate` attribute.
`Density.shape`	Returns the dimensions of `Density.data`.

Methods

`Density.adjust_box`(box[, pad_kwargs])	Adjusts `Density.data` and `Density.origin` according to the provided box.
`Density.align_to_axis`([data, axis, flip])
`Density.center_of_mass`([arr, cutoff])	Computes the center of mass of a numpy ndarray instance.
`Density.centered`([cutoff, order])	Shifts the data center of mass to the center of the data array using linear interpolation.
`Density.copy`()	Create a copy of the class instance.
`Density.core_mask`()	Calculates a weighted core mask by performing iterative binary erosion on `Density.data`.
`Density.density_boundary`(weight[, ...])	Computes the density boundary of the class instance.
`Density.fourier_shell_correlation`(density1, ...)	Computes the Fourier Shell Correlation (FSC) between two instances of Density.
`Density.from_file`(filename[, subset, use_memmap])	Reads a file into a `Density` instance.
`Density.from_structure`(filename_or_structure)	Reads in an atomic structure and converts it into a `Density` instance.
`Density.match_densities`(target, template[, ...])	Aligns two `Density` instances target and template and returns the aligned template.
`Density.match_structure_to_density`(target, ...)	Aligns a `tme.structure.Structure` template to `Density` target and returns an aligned `tme.structure.Structure` instance.
`Density.minimum_enclosing_box`(cutoff[, ...])	Compute the enclosing box that holds all possible rotations of the internal data array.
`Density.normal_vectors`(coordinates)	Calculates the normal vectors for the given coordinates on the densities of the class instance.
`Density.pad`(new_shape[, center, padding_value])	`Density.pad()` extends the internal `Density.data` array of the current `Density` instance to `new_shape` and adapts `Density.origin` accordingly.
`Density.resample`(new_sampling_rate[, ...])	Resamples `Density.data` to `new_sampling_rate`.
`Density.rigid_transform`(rotation_matrix[, ...])	Performs a rigid transform of the class instance.
`Density.surface_coordinates`(density_boundaries)	Calculates the surface coordinates of the class instance using different boundary and surface detection methods.
`Density.to_file`(filename[, gzip])	Writes class instance to disk.
`Density.to_memmap`()	Converts `Density.data` to a `numpy.memmap`.
`Density.to_numpy`()	Converts `Density.data` to an in-memory `numpy.ndarray`.
`Density.to_pointcloud`([threshold])	Returns data indices that are larger than the given threshold.
`Density.trim_box`(cutoff[, margin])	Computes a rectangle with sufficient dimension that encloses all values of the internal data array larger than the specified cutoff, expanded by the specified margin.

Density#

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