asterism#

Subpackages#

Module contents#

class asterism.ATLAS(min_topics=1, *, channels=(128, 32), doc_size=16, topic_rate=8.0, kld_scale=0.1, optim='adam', desc='ATLAS', seed=None)#

Bases: Asterism, Module

fit(x, locs, y=None, *args, **kwargs)#
fit_predict(x, locs, y=None, *args, **kwargs)#

Perform clustering on X and returns cluster labels.

Parameters#

Xarray-like of shape (n_samples, n_features)

Input data.

yIgnored

Not used, present for API consistency by convention.

**kwargsdict

Arguments to be passed to fit.

Added in version 1.4.

Returns#

labelsndarray of shape (n_samples,), dtype=np.int64

Cluster labels.

set_fit_request(*, locs: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → ATLAS#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.

class asterism.GibbsLDA(n_topics=5, *, doc_size=32, vocab_size=16, dt_prior=1.0, tw_prior=1.0, desc='LDA', seed=None)#

Bases: Asterism

set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → GibbsLDA#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for display_rate parameter in fit.

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for n_steps parameter in fit.

verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for verbosity parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.

class asterism.GibbsSLDA(n_topics=5, *, n_docs=-16, doc_size=6.0, word_size=6.0, vocab_size=16, dt_prior=1.0, tw_prior=1.0, desc='SLDA', seed=None)#

Bases: Asterism

fit(x, locs, y=None, *args, **kwargs)#
fit_predict(x, locs, y=None, *args, **kwargs)#

Perform clustering on X and returns cluster labels.

Parameters#

Xarray-like of shape (n_samples, n_features)

Input data.

yIgnored

Not used, present for API consistency by convention.

**kwargsdict

Arguments to be passed to fit.

Added in version 1.4.

Returns#

labelsndarray of shape (n_samples,), dtype=np.int64

Cluster labels.

set_fit_request(*, locs: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → GibbsSLDA#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.

class asterism.NCP(*, wc_channels=(128, 128), bc_channels=(512, 512), lp_channels=(128, 128), optim='adam', desc='NCP', seed=None)#

Bases: Asterism, Module

set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → NCP#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for display_rate parameter in fit.

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for n_steps parameter in fit.

verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for verbosity parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.

class asterism.NTM(n_topics=5, *, channels=(128, 32), kld_scale=0.1, mode='softmax', optim='adam', desc='NTM', seed=None)#

Bases: Asterism, Module

set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → NTM#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for display_rate parameter in fit.

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for n_steps parameter in fit.

verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for verbosity parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.

class asterism.PyroLDA(n_topics=5, *, doc_size=32, vocab_size=16, dt_prior=1.0, tw_prior=1.0, desc='LDA', seed=None)#

Bases: Asterism, Module

set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → PyroLDA#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for display_rate parameter in fit.

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for n_steps parameter in fit.

verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for verbosity parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.

class asterism.RSB(min_topics=1, *, channels=(128, 32), topic_rate=16.0, kld_scale=0.1, optim='adam', desc='RSB', seed=None)#

Bases: Asterism, Module

set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → RSB#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for display_rate parameter in fit.

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for n_steps parameter in fit.

verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for verbosity parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.

class asterism.VQAE(n_topics=5, *, channels=(128, 32), optim='adam', desc='VQAE', seed=None)#

Bases: Asterism, Module

set_fit_request(*, display_rate: bool | None | str = '$UNCHANGED$', locs: bool | None | str = '$UNCHANGED$', n_steps: bool | None | str = '$UNCHANGED$', verbosity: bool | None | str = '$UNCHANGED$', x: bool | None | str = '$UNCHANGED$') → VQAE#

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters#

display_ratestr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for display_rate parameter in fit.

locsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for locs parameter in fit.

n_stepsstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for n_steps parameter in fit.

verbositystr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for verbosity parameter in fit.

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns#

selfobject

The updated object.