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class pyemma.coordinates.pipelines.Discretizer(reader, transform=None, cluster=None, chunksize=None, param_stride=1)¶

A Discretizer gets a FeatureReader, which extracts features (distances, angles etc.) of given trajectory data and passes this data in a memory efficient way through the given pipeline of a StreamingTransformer and Clustering. The clustering object is responsible for assigning the data to the cluster centers.

Parameters:

reader (a FeatureReader object) – reads trajectory data and selects features.
transform (a StreamingTransformer object (optional)) – the StreamingTransformer will be used to e.g reduce dimensionality of inputs.
cluster (a clustering object) – used to assign input data to discrete states/ discrete trajectories.
chunksize (int, optional) – how many frames shall be processed at once.

add_element(e)¶

Appends a pipeline stage.

Appends the given element to the end of the current chain.

dtrajs¶: get discrete trajectories

logger¶: The logger for this class instance

name¶: The name of this instance

parametrize()¶: Reads all data and discretizes it into discrete trajectories.

save_dtrajs(prefix='', output_dir='.', output_format='ascii', extension='.dtraj')¶

Saves calculated discrete trajectories. Filenames are taken from given reader. If data comes from memory dtrajs are written to a default filename.

Parameters:	prefix (str) – prepend prefix to filenames. output_dir (str (optional)) – save files to this directory. Defaults to current working directory. output_format (str) – if format is ‘ascii’ dtrajs will be written as csv files, otherwise they will be written as NumPy .npy files. extension (str) – file extension to append (eg. ‘.itraj’)

set_element(index, e)¶

Replaces a pipeline stage.

Replace an element in chain and return replaced element.

class pyemma.coordinates.pipelines.Pipeline(chain, chunksize=None, param_stride=1)¶

Data processing pipeline.