>>> from sklearn.decomposition import PCA
>>> from sklearn.manifold import TSNE
>>> from techminer2.factor_analysis.co_occurrence import manifold_terms_by_dimension_map
>>> manifold_terms_by_dimension_map(
... #
... # PARAMS:
... field="author_keywords",
... association_index=None,
... #
... # ITEM PARAMS:
... top_n=20,
... occ_range=(None, None),
... gc_range=(None, None),
... custom_terms=None,
... #
... # DESOMPOSITION PARAMS:
... decomposition_estimator = PCA(
... n_components=5,
... whiten=False,
... svd_solver="auto",
... tol=0.0,
... iterated_power="auto",
... n_oversamples=10,
... power_iteration_normalizer="auto",
... random_state=0,
... ),
... #
... # MANIFOLD PARAMS:
... manifold_estimator=TSNE(
... perplexity=10.0,
... early_exaggeration=12.0,
... learning_rate="auto",
... max_iter=1000,
... n_iter_without_progress=300,
... min_grad_norm=1e-07,
... metric="euclidean",
... metric_params=None,
... init="pca",
... verbose=0,
... random_state=0,
... method="barnes_hut",
... angle=0.5,
... n_jobs=None,
... ),
... #
... # MAP PARAMS:
... node_color="#465c6b",
... node_size=10,
... textfont_size=8,
... textfont_color="#465c6b",
... xaxes_range=None,
... yaxes_range=None,
... #
... # DATABASE PARAMS:
... root_dir="example/",
... database="main",
... year_filter=(None, None),
... cited_by_filter=(None, None),
... ).write_html("sphinx/_static/factor_analysis/co_occurrence/manifold_terms_by_dimension_map.html")