diff --git a/README.rst b/README.rst index 99fd3d3..8aeb07b 100644 --- a/README.rst +++ b/README.rst @@ -14,8 +14,8 @@ Documentation Please read the `documentation `_ -and this -`basic tutorial `_. +or use this +`basic tutorial notebook `_. Basic Usage diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle index 6b35e1d..64218c6 100644 Binary files a/docs/build/doctrees/environment.pickle and b/docs/build/doctrees/environment.pickle differ diff --git a/docs/build/doctrees/index.doctree b/docs/build/doctrees/index.doctree index 0bdb8d1..4dbc9a0 100644 Binary files a/docs/build/doctrees/index.doctree and b/docs/build/doctrees/index.doctree differ diff --git a/docs/build/html/index.html b/docs/build/html/index.html index 28ad536..651f8cf 100644 --- a/docs/build/html/index.html +++ b/docs/build/html/index.html @@ -226,8 +226,8 @@

Installation#

Please read the documentation -and this -basic tutorial.

+or use this +basic tutorial notebook.

Basic Usage#

diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js index 342635a..3444fde 100644 --- a/docs/build/html/searchindex.js +++ b/docs/build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["cov", "index", "inference", "model", "notebooks/basic_tutorial", "parameters", "util"], "filenames": ["cov.rst", "index.rst", "inference.rst", "model.rst", "notebooks/basic_tutorial.ipynb", "parameters.rst", "util.rst"], "titles": ["Covariance Functions", "Installation", "Inference", "Model", "Basic Tutorial", "Parameter Selection", "Utilities"], "terms": {"thi": [0, 1, 3, 4], "section": 0, "show": [0, 4], "differ": 0, "wai": 0, "us": [0, 2, 3, 4], "suppli": [0, 3], "defin": [0, 2], "your": [0, 3, 4], "own": [0, 3, 4], "The": [0, 2, 3, 4, 5, 6], "cov_func_curri": [0, 3, 5], "argument": [0, 3], "model": [0, 1, 4], "class": [0, 3], "support": [0, 3, 5], "one": [0, 3], "type": [0, 2, 3, 5, 6], "return": [0, 2, 3, 4, 5, 6], "k": [0, 2, 3, 4, 5], "x": [0, 1, 2, 3, 4, 5, 6], "y": [0, 1, 2, 3, 4, 5, 6], "rightarrow": [0, 2, 3, 5], "float": [0, 2, 3, 5, 6], "In": [0, 4], "case": [0, 3], "length": [0, 3, 4, 5], "scale": [0, 3, 4, 5], "comput": [0, 2, 3, 5, 6], "automat": [0, 3, 4], "pass": [0, 3], "an": [0, 3, 4, 5], "altern": 0, "can": [0, 1, 2, 3, 4], "set": [0, 3, 4, 6], "cov_func": [0, 2, 3, 4, 5], "take": [0, 3], "two": 0, "arrai": [0, 2, 3, 5, 6], "cell": [0, 1, 3, 4], "state": [0, 1, 2, 3, 4], "similat": 0, "between": [0, 3, 4, 5, 6], "each": [0, 2, 3, 5, 6], "pair": 0, "predefin": 0, "default": [0, 2, 3, 4, 5, 6], "behavior": 0, "from": [0, 3, 4, 5], "mellon": [0, 1, 2, 3, 4, 5, 6], "import": [0, 1, 4], "matern52": [0, 3, 4], "cov_func_curi": 0, "length_scal": [0, 4], "write": 0, "variabl": [0, 3], "distanc": [0, 2, 3, 4, 5, 6], "point": [0, 2, 3, 5, 6], "def": [0, 4], "l": [0, 2, 3, 4, 5], "1": [0, 2, 3, 4, 5, 6], "0": [0, 2, 3, 4, 5], "r": 0, "similar": [0, 4], "sqrt": 0, "5": [0, 4], "squar": [0, 6], "3": [0, 4], "exp": 0, "inherit": 0, "base": [0, 1, 3, 4], "__call__": 0, "method": [0, 3, 5], "call": [0, 3], "__init__": 0, "self": [0, 3], "super": 0, "simialar": 0, "upport": 0, "ad": [0, 3, 4, 6], "multipli": 0, "power": 0, "oper": 0, "combin": 0, "expquad": 0, "7": [0, 4], "cov": [0, 3], "e": [0, 2, 3, 4], "frac": 0, "2": [0, 3, 4, 5, 6], "exponenti": [0, 2], "2l": 0, "matern32": 0, "cdot": [0, 3, 5, 6], "3l": 0, "ratquad": 0, "alpha": [0, 4], "i": [1, 2, 3, 4, 5], "non": [1, 3], "parametr": [1, 3], "densiti": [1, 2, 3, 6], "estim": [1, 3, 4, 6], "nearestneighbor": 1, "distribut": [1, 3, 4, 6], "To": 1, "pip": 1, "you": [1, 3, 4], "run": [1, 3], "pleas": 1, "read": [1, 4], "tutori": 1, "numpi": [1, 4], "np": [1, 4], "random": [1, 4], "rand": [1, 4], "100": [1, 2, 3, 4], "10": [1, 3, 4, 5], "dimension": [1, 2, 3, 4, 5, 6], "represent": [1, 3, 4], "arbitrari": [1, 3, 4], "test": [1, 3, 4], "data": [1, 2, 3, 5, 6], "densityestim": [1, 3, 4], "log_density_x": [1, 2, 3, 4], "fit_predict": [1, 3, 4], "log_density_i": 1, "predict": [1, 3, 4], "compute_conditional_mean": 2, "landmark": [2, 3, 4, 5], "mu": [2, 3, 4, 5], "sigma": [2, 3], "jitter": [2, 3, 5, 6], "1e": [2, 3, 5, 6], "06": [2, 3, 5, 6], "build": [2, 3], "mean": [2, 3, 4, 5], "function": [2, 3, 4, 5], "gaussian": [2, 3, 4, 5], "process": [2, 3, 4, 5], "condit": [2, 3], "valu": [2, 3, 4, 5], "g": [2, 4], "log": [2, 3, 4, 5, 6], "whole": 2, "domain": 2, "paramet": [2, 3, 6], "like": [2, 3, 4, 5, 6], "train": [2, 3, 4, 5], "instanc": [2, 3, 5], "fast": 2, "spars": 2, "none": [2, 3, 5], "origin": 2, "covari": [2, 3, 4, 5], "white": [2, 3], "mois": [2, 3], "verianc": 2, "A": [2, 3, 4, 5, 6], "small": [2, 3, 5, 6], "amount": [2, 3, 5, 6], "add": [2, 3, 5, 6], "diagon": [2, 3, 5, 6], "stabil": [2, 3, 6], "6": [2, 3, 4, 5, 6], "conditional_mean": 2, "compute_log_density_x": 2, "pre_transform": [2, 3, 4], "transform": [2, 3], "z": [2, 3, 5], "sim": [2, 3], "text": [2, 3, 5, 6], "normal": [2, 3], "f": [2, 4], "where": [2, 3, 4, 5], "ident": [2, 3], "matrix": [2, 3, 4, 5, 6], "approx": [2, 3, 5], "top": [2, 3, 4, 5], "compute_loss_func": 2, "nn_distanc": [2, 3, 4, 5, 6], "d": [2, 3, 4, 5, 6], "bayesian": [2, 3], "loss": [2, 3], "prior": [2, 3], "likelihood": [2, 3, 4, 6], "observ": [2, 5, 6], "nearest": [2, 3, 4, 5, 6], "neighbor": [2, 3, 4, 5, 6], "int": [2, 3, 5, 6], "map": [2, 3, 4], "dimens": [2, 4, 6], "input": [2, 4], "loss_func": [2, 3, 4], "compute_transform": 2, "minimize_adam": 2, "initial_valu": [2, 3, 4, 5], "n_iter": [2, 3], "init_learn_r": [2, 3], "jit": [2, 3], "fals": [2, 3, 4], "minim": [2, 3, 5], "start": 2, "guess": [2, 3], "adam": [2, 3], "decai": 2, "learn": [2, 3], "rate": [2, 3], "initi": [2, 3, 4, 5], "integ": [2, 4], "number": [2, 3, 4, 5], "optim": [2, 3, 4, 5], "iter": [2, 3, 4], "result": [2, 3, 4], "name": 2, "tupl": 2, "contain": 2, "opt_stat": [2, 3], "final": [2, 3], "histori": [2, 3], "object": [2, 3], "minimize_lbfgsb": 2, "baseestim": 3, "n_landmark": [3, 4, 5], "5000": [3, 4, 5], "rank": [3, 4, 5], "999": [3, 4, 5], "auto": [3, 5], "bfg": 3, "b": 3, "ls_factor": 3, "fit": [3, 4], "make": [3, 4], "gradient": [3, 4], "true": 3, "conput": 3, "line": 3, "bool": 3, "jax": 3, "just": 3, "time": [3, 4, 5], "compil": 3, "gradiant": 3, "shape": [3, 4], "hessian": [3, 4], "hessian_log_determin": 3, "logarirhm": 3, "determinat": 3, "sign": 3, "log_determin": 3, "determin": [3, 4], "logarithm": 3, "its": [3, 4, 5], "absolut": 3, "new": 3, "prepare_infer": [3, 4], "all": [3, 4], "attribut": 3, "prepar": 3, "It": 3, "necessari": 3, "befor": 3, "perform": 3, "infer": [3, 4], "intermedi": [3, 4], "ar": [3, 4], "cach": 3, "so": 3, "user": [3, 4], "view": 3, "save": 3, "precomput": 3, "gener": [3, 5], "must": 3, "curri": 3, "form": 3, "If": [3, 5], "less": [3, 4, 5], "than": [3, 5], "greater": [3, 5], "equal": [3, 5], "doe": 3, "induc": 3, "approxim": [3, 4, 5], "n": [3, 5], "exact": [3, 5], "le": [3, 5], "size": [3, 4, 5], "select": [3, 4], "includ": [3, 5], "eigenvalu": [3, 4, 5], "account": [3, 5], "specifi": [3, 5], "percentag": [3, 5], "sum": [3, 4, 5], "str": [3, 4, 5], "explicitli": [3, 5], "whether": [3, 5], "interpret": [3, 5], "fix": [3, 5], "eigenvector": [3, 4, 5], "percent": [3, 5], "low": [3, 4, 5], "provid": 3, "explict": 3, "clarifi": 3, "ambigu": 3, "v": 3, "bind": 3, "numer": [3, 6], "awai": [3, 4], "ensur": [3, 4], "stabilit": 3, "stochast": 3, "maximum": [3, 4, 5, 6], "posteriori": [3, 5], "quantiz": 3, "centroid": [3, 4, 5], "ignor": 3, "kdtree": 3, "20": [3, 4], "balltre": 3, "otherwis": 3, "local": [3, 4, 5, 6], "dimansion": 3, "embed": 3, "manifold": [3, 4], "axi": [3, 4, 5], "1th": [3, 5], "percentil": [3, 5], "mle": [3, 5, 6], "nn": [3, 5, 6], "_": [3, 5, 6], "gamma": [3, 5, 6], "pi": [3, 5, 6], "geometr": [3, 5], "constant": [3, 5], "explictli": 3, "ha": 3, "effect": 3, "find": 3, "lz": [3, 5], "dure": 3, "when": 3, "factor": [3, 4], "latent": 3, "throughout": 3, "log_density_func": 3, "build_predict": 3, "end": 3, "log_dens": [3, 4], "do": 3, "process_infer": [3, 4], "also": [3, 4], "store": 3, "run_infer": [3, 4], "would": [3, 4], "procedur": 3, "loss_funct": 3, "functionestim": 3, "smoothen": 3, "extend": 3, "abstract": 3, "standard": 3, "deviat": 3, "nois": 3, "compute_condit": 3, "condition_mean_funct": 3, "smooth": [3, 4], "condition_mean": 3, "notebook": 4, "illustr": 4, "applic": 4, "scrna": 4, "seq": 4, "panda": 4, "pd": 4, "matplotlib": 4, "pyplot": 4, "plt": 4, "palantir": 4, "scanpi": 4, "sc": 4, "inlin": 4, "rcparam": 4, "figur": 4, "figsiz": 4, "4": 4, "dpi": 4, "imag": 4, "cmap": 4, "spectral_r": 4, "bound": 4, "box": 4, "ax": 4, "spine": 4, "bottom": 4, "off": 4, "left": 4, "right": 4, "we": 4, "public": 4, "avail": 4, "dataset": 4, "t": 4, "deplet": 4, "bone": 4, "marrow": 4, "ad_url": 4, "http": 4, "zenodo": 4, "org": 4, "record": 4, "6383269": 4, "file": 4, "bm_multiome_rna": 4, "h5ad": 4, "backup_url": 4, "anndata": 4, "wa": 4, "alreadi": 4, "raw": 4, "gene": 4, "count": 4, "accord": 4, "github": 4, "com": 4, "settylab": 4, "singl": 4, "primer": 4, "blob": 4, "main": 4, "pbmc": 4, "rna": 4, "standalon": 4, "ipynb": 4, "come": 4, "celltyp": 4, "annot": 4, "pca": 4, "umap": 4, "diffus": 4, "clean": 4, "up": 4, "dm_re": 4, "util": 4, "run_diffusion_map": 4, "datafram": 4, "obsm": 4, "x_pca": 4, "index": 4, "obs_nam": 4, "obsp": 4, "dm_kernel": 4, "kernel": 4, "dm_eigenvector": 4, "un": 4, "dmeigenvalu": 4, "determ": 4, "graph": 4, "requir": 4, "howeev": 4, "insight": 4, "investig": 4, "fluctuat": 4, "along": 4, "tempor": 4, "trajectori": 4, "differenti": 4, "hspc": 4, "dcomp": 4, "rang": 4, "ec": 4, "argmax": 4, "ob": 4, "mm": 4, "break": 4, "argmin": [4, 5], "minimum": 4, "els": 4, "rais": 4, "except": 4, "No": 4, "valid": 4, "compon": 4, "found": 4, "early_cel": 4, "print": 4, "earli": 4, "which": 4, "im": 4, "1393_bonemarrow_tcelldep_2_multiom": 4, "agccgctagacaagtg": 4, "ms_data": 4, "determine_multiscale_spac": 4, "pl_re": 4, "core": 4, "run_palantir": 4, "palantir_pseudotim": 4, "pl": 4, "scatter": 4, "basi": 4, "color": 4, "sampl": 4, "flock": 4, "waypoint": 4, "015990734100341797": 4, "minut": 4, "shortest": 4, "path": 4, "30": 4, "26976213455200193": 4, "refin": 4, "correl": 4, "9997": 4, "0000": 4, "entropi": 4, "branch": 4, "probabl": 4, "markov": 4, "chain": 4, "construct": 4, "identif": 4, "termin": 4, "fundament": 4, "absorpt": 4, "project": 4, "log_density_clip": 4, "clip": 4, "quantil": 4, "05": 4, "cpu": 4, "3min": 4, "29": 4, "sy": 4, "13": 4, "": 4, "total": 4, "42": 4, "wall": 4, "21": 4, "8": 4, "9": 4, "12": 4, "fig": 4, "ax1": 4, "ax2": 4, "subplot": 4, "width_ratio": 4, "boxplot": 4, "grid": 4, "rot": 4, "45": 4, "fontsiz": 4, "suptitl": 4, "set_titl": 4, "set_ylabel": 4, "mep": 4, "erypr": 4, "eri": 4, "ct_color": 4, "get": 4, "dict": 4, "zip": 4, "cat": 4, "categori": 4, "celltype_color": 4, "sct_color": 4, "ct": 4, "dddddd": 4, "idx": 4, "isin": 4, "color_vec": 4, "loc": 4, "selected_celltyp": 4, "astyp": 4, "selected_celltypes_color": 4, "c": 4, "set_xlabel": 4, "abov": 4, "follow": 4, "equival": 4, "code": 4, "chang": 4, "desir": 4, "11": 4, "compute_nn_dist": [4, 5], "regul": 4, "lower": 4, "produc": 4, "faster": 4, "more": 4, "detail": 4, "therefor": 4, "stabl": 4, "By": 4, "hurist": 4, "aim": 4, "maximix": 4, "posterio": 4, "compute_l": [4, 5], "structur": 4, "henc": 4, "proxi": 4, "while": 4, "ani": 4, "cluster": 4, "preform": 4, "best": 4, "our": 4, "limit": 4, "k_mean": 4, "n_init": 4, "34": 4, "01": 4, "35": 4, "22": 4, "further": 4, "reduc": 4, "improv": 4, "nystr\u00f6m": 4, "either": 4, "fraction": 4, "varianc": 4, "preserv": 4, "choleski": 4, "14": 4, "2min": 4, "37": 4, "50": 4, "assum": 4, "vari": 4, "howev": 4, "known": 4, "onli": 4, "subspac": 4, "tangenti": 4, "phenotyp": 4, "should": 4, "correctli": 4, "relat": 4, "15": 4, "suggest": 4, "invari": 4, "drop": 4, "quickli": 4, "16": 4, "compute_mu": [4, 5], "ridg": [4, 5], "regress": [4, 5], "speed": 4, "17": 4, "initial_paramet": 4, "compute_initial_valu": [4, 5], "43": 4, "44": 4, "55": 4, "19": 4, "instead": 4, "mai": 4, "split": 4, "three": 4, "allow": 4, "For": 4, "o": 4, "replac": 4, "optimal_paramet": 4, "after": 4, "Of": 4, "cours": 4, "work": 4, "full": 5, "decompost": 5, "compute_cov_func": 5, "compute_d": 5, "compute_landmark": 5, "landmark_point": 5, "given": 6}, "objects": {"mellon": [[0, 0, 0, "-", "cov"], [2, 0, 0, "-", "inference"], [3, 0, 0, "-", "model"], [5, 0, 0, "-", "parameters"], [6, 0, 0, "-", "util"]], "mellon.cov": [[0, 1, 1, "", "ExpQuad"], [0, 1, 1, "", "Exponential"], [0, 1, 1, "", "Matern32"], [0, 1, 1, "", "Matern52"], [0, 1, 1, "", "RatQuad"]], "mellon.cov.ExpQuad": [[0, 2, 1, "", "k"]], "mellon.cov.Exponential": [[0, 2, 1, "", "k"]], "mellon.cov.Matern32": [[0, 2, 1, "", "k"]], "mellon.cov.Matern52": [[0, 2, 1, "", "k"]], "mellon.cov.RatQuad": [[0, 2, 1, "", "k"]], "mellon.inference": [[2, 3, 1, "", "compute_conditional_mean"], [2, 3, 1, "", "compute_log_density_x"], [2, 3, 1, "", "compute_loss_func"], [2, 3, 1, "", "compute_transform"], [2, 3, 1, "", "minimize_adam"], [2, 3, 1, "", "minimize_lbfgsb"]], "mellon.model": [[3, 1, 1, "", "BaseEstimator"], [3, 1, 1, "", "DensityEstimator"], [3, 1, 1, "", "FunctionEstimator"]], "mellon.model.BaseEstimator": [[3, 2, 1, "", "fit"], [3, 2, 1, "", "fit_predict"], [3, 2, 1, "", "gradient"], [3, 2, 1, "", "hessian"], [3, 2, 1, "", "hessian_log_determinant"], [3, 2, 1, "", "predict"], [3, 2, 1, "", "prepare_inference"]], "mellon.model.DensityEstimator": [[3, 2, 1, "", "fit"], [3, 2, 1, "", "fit_predict"], [3, 2, 1, "", "predict"], [3, 2, 1, "", "prepare_inference"], [3, 2, 1, "", "process_inference"], [3, 2, 1, "", "run_inference"]], "mellon.model.FunctionEstimator": [[3, 2, 1, "", "compute_conditional"], [3, 2, 1, "", "fit"], [3, 2, 1, "", "fit_predict"], [3, 2, 1, "", "predict"], [3, 2, 1, "", "prepare_inference"]], "mellon.parameters": [[5, 3, 1, "", "compute_L"], [5, 3, 1, "", "compute_cov_func"], [5, 3, 1, "", "compute_d"], [5, 3, 1, "", "compute_initial_value"], [5, 3, 1, "", "compute_landmarks"], [5, 3, 1, "", "compute_ls"], [5, 3, 1, "", "compute_mu"], [5, 3, 1, "", "compute_nn_distances"]], "mellon.util": [[6, 3, 1, "", "distance"], [6, 3, 1, "", "mle"], [6, 3, 1, "", "stabilize"]]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:method", "3": "py:function"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "method", "Python method"], "3": ["py", "function", "Python function"]}, "titleterms": {"covari": 0, "function": 0, "implement": 0, "instal": 1, "document": 1, "basic": [1, 4], "usag": 1, "index": 1, "infer": 2, "model": 3, "tutori": 4, "load": 4, "data": 4, "preprocess": 4, "comput": 4, "pseudotim": 4, "option": 4, "densiti": 4, "exampl": 4, "analysi": 4, "adjust": 4, "paramet": [4, 5], "stage": 4, "api": 4, "deriv": 4, "select": 5, "util": 6}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 8, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "nbsphinx": 4, "sphinx": 57}, "alltitles": {"Covariance Functions": [[0, "covariance-functions"]], "Implemented Covariance Functions": [[0, "module-mellon.cov"]], "Installation": [[1, "installation"]], "Documentation": [[1, "documentation"]], "Basic Usage": [[1, "basic-usage"]], "Index": [[1, "index"]], "Inference": [[2, "module-mellon.inference"]], "Model": [[3, "module-mellon.model"]], "Basic Tutorial": [[4, "Basic-Tutorial"]], "Loading the data": [[4, "Loading-the-data"]], "Preprocessing": [[4, "Preprocessing"]], "Compute pseudotime (optional)": [[4, "Compute-pseudotime-(optional)"]], "Density computation": [[4, "Density-computation"]], "Example analysis": [[4, "Example-analysis"]], "Adjustable parameters": [[4, "Adjustable-parameters"]], "Stages API": [[4, "Stages-API"]], "Derivatives": [[4, "Derivatives"]], "Parameter Selection": [[5, "module-mellon.parameters"]], "Utilities": [[6, "module-mellon.util"]]}, "indexentries": {"expquad (class in mellon.cov)": [[0, "mellon.cov.ExpQuad"]], "exponential (class in mellon.cov)": [[0, "mellon.cov.Exponential"]], "matern32 (class in mellon.cov)": [[0, "mellon.cov.Matern32"]], "matern52 (class in mellon.cov)": [[0, "mellon.cov.Matern52"]], "ratquad (class in mellon.cov)": [[0, "mellon.cov.RatQuad"]], "k() (mellon.cov.expquad method)": [[0, "mellon.cov.ExpQuad.k"]], "k() (mellon.cov.exponential method)": [[0, "mellon.cov.Exponential.k"]], "k() (mellon.cov.matern32 method)": [[0, "mellon.cov.Matern32.k"]], "k() (mellon.cov.matern52 method)": [[0, "mellon.cov.Matern52.k"]], "k() (mellon.cov.ratquad method)": [[0, "mellon.cov.RatQuad.k"]], "mellon.cov": [[0, "module-mellon.cov"]], "module": [[0, "module-mellon.cov"], [2, "module-mellon.inference"], [3, "module-mellon.model"], [5, "module-mellon.parameters"], [6, "module-mellon.util"]], "compute_conditional_mean() (in module mellon.inference)": [[2, "mellon.inference.compute_conditional_mean"]], "compute_log_density_x() (in module mellon.inference)": [[2, "mellon.inference.compute_log_density_x"]], "compute_loss_func() (in module mellon.inference)": [[2, "mellon.inference.compute_loss_func"]], "compute_transform() (in module mellon.inference)": [[2, "mellon.inference.compute_transform"]], "mellon.inference": [[2, "module-mellon.inference"]], "minimize_adam() (in module mellon.inference)": [[2, "mellon.inference.minimize_adam"]], "minimize_lbfgsb() (in module mellon.inference)": [[2, "mellon.inference.minimize_lbfgsb"]], "baseestimator (class in mellon.model)": [[3, "mellon.model.BaseEstimator"]], "densityestimator (class in mellon.model)": [[3, "mellon.model.DensityEstimator"]], "functionestimator (class in mellon.model)": [[3, "mellon.model.FunctionEstimator"]], "compute_conditional() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.compute_conditional"]], "fit() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.fit"]], "fit() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.fit"]], "fit() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.fit"]], "fit_predict() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.fit_predict"]], "fit_predict() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.fit_predict"]], "fit_predict() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.fit_predict"]], "gradient() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.gradient"]], "hessian() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.hessian"]], "hessian_log_determinant() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.hessian_log_determinant"]], "mellon.model": [[3, "module-mellon.model"]], "predict() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.predict"]], "predict() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.predict"]], "predict() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.predict"]], "prepare_inference() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.prepare_inference"]], "prepare_inference() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.prepare_inference"]], "prepare_inference() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.prepare_inference"]], "process_inference() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.process_inference"]], "run_inference() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.run_inference"]], "compute_l() (in module mellon.parameters)": [[5, "mellon.parameters.compute_L"]], "compute_cov_func() (in module mellon.parameters)": [[5, "mellon.parameters.compute_cov_func"]], "compute_d() (in module mellon.parameters)": [[5, "mellon.parameters.compute_d"]], "compute_initial_value() (in module mellon.parameters)": [[5, "mellon.parameters.compute_initial_value"]], "compute_landmarks() (in module mellon.parameters)": [[5, "mellon.parameters.compute_landmarks"]], "compute_ls() (in module mellon.parameters)": [[5, "mellon.parameters.compute_ls"]], "compute_mu() (in module mellon.parameters)": [[5, "mellon.parameters.compute_mu"]], "compute_nn_distances() (in module mellon.parameters)": [[5, "mellon.parameters.compute_nn_distances"]], "mellon.parameters": [[5, "module-mellon.parameters"]], "distance() (in module mellon.util)": [[6, "mellon.util.distance"]], "mellon.util": [[6, "module-mellon.util"]], "mle() (in module mellon.util)": [[6, "mellon.util.mle"]], "stabilize() (in module mellon.util)": [[6, "mellon.util.stabilize"]]}}) \ No newline at end of file +Search.setIndex({"docnames": ["cov", "index", "inference", "model", "notebooks/basic_tutorial", "parameters", "util"], "filenames": ["cov.rst", "index.rst", "inference.rst", "model.rst", "notebooks/basic_tutorial.ipynb", "parameters.rst", "util.rst"], "titles": ["Covariance Functions", "Installation", "Inference", "Model", "Basic Tutorial", "Parameter Selection", "Utilities"], "terms": {"thi": [0, 1, 3, 4], "section": 0, "show": [0, 4], "differ": 0, "wai": 0, "us": [0, 1, 2, 3, 4], "suppli": [0, 3], "defin": [0, 2], "your": [0, 3, 4], "own": [0, 3, 4], "The": [0, 2, 3, 4, 5, 6], "cov_func_curri": [0, 3, 5], "argument": [0, 3], "model": [0, 1, 4], "class": [0, 3], "support": [0, 3, 5], "one": [0, 3], "type": [0, 2, 3, 5, 6], "return": [0, 2, 3, 4, 5, 6], "k": [0, 2, 3, 4, 5], "x": [0, 1, 2, 3, 4, 5, 6], "y": [0, 1, 2, 3, 4, 5, 6], "rightarrow": [0, 2, 3, 5], "float": [0, 2, 3, 5, 6], "In": [0, 4], "case": [0, 3], "length": [0, 3, 4, 5], "scale": [0, 3, 4, 5], "comput": [0, 2, 3, 5, 6], "automat": [0, 3, 4], "pass": [0, 3], "an": [0, 3, 4, 5], "altern": 0, "can": [0, 1, 2, 3, 4], "set": [0, 3, 4, 6], "cov_func": [0, 2, 3, 4, 5], "take": [0, 3], "two": 0, "arrai": [0, 2, 3, 5, 6], "cell": [0, 1, 3, 4], "state": [0, 1, 2, 3, 4], "similat": 0, "between": [0, 3, 4, 5, 6], "each": [0, 2, 3, 5, 6], "pair": 0, "predefin": 0, "default": [0, 2, 3, 4, 5, 6], "behavior": 0, "from": [0, 3, 4, 5], "mellon": [0, 1, 2, 3, 4, 5, 6], "import": [0, 1, 4], "matern52": [0, 3, 4], "cov_func_curi": 0, "length_scal": [0, 4], "write": 0, "variabl": [0, 3], "distanc": [0, 2, 3, 4, 5, 6], "point": [0, 2, 3, 5, 6], "def": [0, 4], "l": [0, 2, 3, 4, 5], "1": [0, 2, 3, 4, 5, 6], "0": [0, 2, 3, 4, 5], "r": 0, "similar": [0, 4], "sqrt": 0, "5": [0, 4], "squar": [0, 6], "3": [0, 4], "exp": 0, "inherit": 0, "base": [0, 1, 3, 4], "__call__": 0, "method": [0, 3, 5], "call": [0, 3], "__init__": 0, "self": [0, 3], "super": 0, "simialar": 0, "upport": 0, "ad": [0, 3, 4, 6], "multipli": 0, "power": 0, "oper": 0, "combin": 0, "expquad": 0, "7": [0, 4], "cov": [0, 3], "e": [0, 2, 3, 4], "frac": 0, "2": [0, 3, 4, 5, 6], "exponenti": [0, 2], "2l": 0, "matern32": 0, "cdot": [0, 3, 5, 6], "3l": 0, "ratquad": 0, "alpha": [0, 4], "i": [1, 2, 3, 4, 5], "non": [1, 3], "parametr": [1, 3], "densiti": [1, 2, 3, 6], "estim": [1, 3, 4, 6], "nearestneighbor": 1, "distribut": [1, 3, 4, 6], "To": 1, "pip": 1, "you": [1, 3, 4], "run": [1, 3], "pleas": 1, "read": [1, 4], "tutori": 1, "notebook": [1, 4], "numpi": [1, 4], "np": [1, 4], "random": [1, 4], "rand": [1, 4], "100": [1, 2, 3, 4], "10": [1, 3, 4, 5], "dimension": [1, 2, 3, 4, 5, 6], "represent": [1, 3, 4], "arbitrari": [1, 3, 4], "test": [1, 3, 4], "data": [1, 2, 3, 5, 6], "densityestim": [1, 3, 4], "log_density_x": [1, 2, 3, 4], "fit_predict": [1, 3, 4], "log_density_i": 1, "predict": [1, 3, 4], "compute_conditional_mean": 2, "landmark": [2, 3, 4, 5], "mu": [2, 3, 4, 5], "sigma": [2, 3], "jitter": [2, 3, 5, 6], "1e": [2, 3, 5, 6], "06": [2, 3, 5, 6], "build": [2, 3], "mean": [2, 3, 4, 5], "function": [2, 3, 4, 5], "gaussian": [2, 3, 4, 5], "process": [2, 3, 4, 5], "condit": [2, 3], "valu": [2, 3, 4, 5], "g": [2, 4], "log": [2, 3, 4, 5, 6], "whole": 2, "domain": 2, "paramet": [2, 3, 6], "like": [2, 3, 4, 5, 6], "train": [2, 3, 4, 5], "instanc": [2, 3, 5], "fast": 2, "spars": 2, "none": [2, 3, 5], "origin": 2, "covari": [2, 3, 4, 5], "white": [2, 3], "mois": [2, 3], "verianc": 2, "A": [2, 3, 4, 5, 6], "small": [2, 3, 5, 6], "amount": [2, 3, 5, 6], "add": [2, 3, 5, 6], "diagon": [2, 3, 5, 6], "stabil": [2, 3, 6], "6": [2, 3, 4, 5, 6], "conditional_mean": 2, "compute_log_density_x": 2, "pre_transform": [2, 3, 4], "transform": [2, 3], "z": [2, 3, 5], "sim": [2, 3], "text": [2, 3, 5, 6], "normal": [2, 3], "f": [2, 4], "where": [2, 3, 4, 5], "ident": [2, 3], "matrix": [2, 3, 4, 5, 6], "approx": [2, 3, 5], "top": [2, 3, 4, 5], "compute_loss_func": 2, "nn_distanc": [2, 3, 4, 5, 6], "d": [2, 3, 4, 5, 6], "bayesian": [2, 3], "loss": [2, 3], "prior": [2, 3], "likelihood": [2, 3, 4, 6], "observ": [2, 5, 6], "nearest": [2, 3, 4, 5, 6], "neighbor": [2, 3, 4, 5, 6], "int": [2, 3, 5, 6], "map": [2, 3, 4], "dimens": [2, 4, 6], "input": [2, 4], "loss_func": [2, 3, 4], "compute_transform": 2, "minimize_adam": 2, "initial_valu": [2, 3, 4, 5], "n_iter": [2, 3], "init_learn_r": [2, 3], "jit": [2, 3], "fals": [2, 3, 4], "minim": [2, 3, 5], "start": 2, "guess": [2, 3], "adam": [2, 3], "decai": 2, "learn": [2, 3], "rate": [2, 3], "initi": [2, 3, 4, 5], "integ": [2, 4], "number": [2, 3, 4, 5], "optim": [2, 3, 4, 5], "iter": [2, 3, 4], "result": [2, 3, 4], "name": 2, "tupl": 2, "contain": 2, "opt_stat": [2, 3], "final": [2, 3], "histori": [2, 3], "object": [2, 3], "minimize_lbfgsb": 2, "baseestim": 3, "n_landmark": [3, 4, 5], "5000": [3, 4, 5], "rank": [3, 4, 5], "999": [3, 4, 5], "auto": [3, 5], "bfg": 3, "b": 3, "ls_factor": 3, "fit": [3, 4], "make": [3, 4], "gradient": [3, 4], "true": 3, "conput": 3, "line": 3, "bool": 3, "jax": 3, "just": 3, "time": [3, 4, 5], "compil": 3, "gradiant": 3, "shape": [3, 4], "hessian": [3, 4], "hessian_log_determin": 3, "logarirhm": 3, "determinat": 3, "sign": 3, "log_determin": 3, "determin": [3, 4], "logarithm": 3, "its": [3, 4, 5], "absolut": 3, "new": 3, "prepare_infer": [3, 4], "all": [3, 4], "attribut": 3, "prepar": 3, "It": 3, "necessari": 3, "befor": 3, "perform": 3, "infer": [3, 4], "intermedi": [3, 4], "ar": [3, 4], "cach": 3, "so": 3, "user": [3, 4], "view": 3, "save": 3, "precomput": 3, "gener": [3, 5], "must": 3, "curri": 3, "form": 3, "If": [3, 5], "less": [3, 4, 5], "than": [3, 5], "greater": [3, 5], "equal": [3, 5], "doe": 3, "induc": 3, "approxim": [3, 4, 5], "n": [3, 5], "exact": [3, 5], "le": [3, 5], "size": [3, 4, 5], "select": [3, 4], "includ": [3, 5], "eigenvalu": [3, 4, 5], "account": [3, 5], "specifi": [3, 5], "percentag": [3, 5], "sum": [3, 4, 5], "str": [3, 4, 5], "explicitli": [3, 5], "whether": [3, 5], "interpret": [3, 5], "fix": [3, 5], "eigenvector": [3, 4, 5], "percent": [3, 5], "low": [3, 4, 5], "provid": 3, "explict": 3, "clarifi": 3, "ambigu": 3, "v": 3, "bind": 3, "numer": [3, 6], "awai": [3, 4], "ensur": [3, 4], "stabilit": 3, "stochast": 3, "maximum": [3, 4, 5, 6], "posteriori": [3, 5], "quantiz": 3, "centroid": [3, 4, 5], "ignor": 3, "kdtree": 3, "20": [3, 4], "balltre": 3, "otherwis": 3, "local": [3, 4, 5, 6], "dimansion": 3, "embed": 3, "manifold": [3, 4], "axi": [3, 4, 5], "1th": [3, 5], "percentil": [3, 5], "mle": [3, 5, 6], "nn": [3, 5, 6], "_": [3, 5, 6], "gamma": [3, 5, 6], "pi": [3, 5, 6], "geometr": [3, 5], "constant": [3, 5], "explictli": 3, "ha": 3, "effect": 3, "find": 3, "lz": [3, 5], "dure": 3, "when": 3, "factor": [3, 4], "latent": 3, "throughout": 3, "log_density_func": 3, "build_predict": 3, "end": 3, "log_dens": [3, 4], "do": 3, "process_infer": [3, 4], "also": [3, 4], "store": 3, "run_infer": [3, 4], "would": [3, 4], "procedur": 3, "loss_funct": 3, "functionestim": 3, "smoothen": 3, "extend": 3, "abstract": 3, "standard": 3, "deviat": 3, "nois": 3, "compute_condit": 3, "condition_mean_funct": 3, "smooth": [3, 4], "condition_mean": 3, "illustr": 4, "applic": 4, "scrna": 4, "seq": 4, "panda": 4, "pd": 4, "matplotlib": 4, "pyplot": 4, "plt": 4, "palantir": 4, "scanpi": 4, "sc": 4, "inlin": 4, "rcparam": 4, "figur": 4, "figsiz": 4, "4": 4, "dpi": 4, "imag": 4, "cmap": 4, "spectral_r": 4, "bound": 4, "box": 4, "ax": 4, "spine": 4, "bottom": 4, "off": 4, "left": 4, "right": 4, "we": 4, "public": 4, "avail": 4, "dataset": 4, "t": 4, "deplet": 4, "bone": 4, "marrow": 4, "ad_url": 4, "http": 4, "zenodo": 4, "org": 4, "record": 4, "6383269": 4, "file": 4, "bm_multiome_rna": 4, "h5ad": 4, "backup_url": 4, "anndata": 4, "wa": 4, "alreadi": 4, "raw": 4, "gene": 4, "count": 4, "accord": 4, "github": 4, "com": 4, "settylab": 4, "singl": 4, "primer": 4, "blob": 4, "main": 4, "pbmc": 4, "rna": 4, "standalon": 4, "ipynb": 4, "come": 4, "celltyp": 4, "annot": 4, "pca": 4, "umap": 4, "diffus": 4, "clean": 4, "up": 4, "dm_re": 4, "util": 4, "run_diffusion_map": 4, "datafram": 4, "obsm": 4, "x_pca": 4, "index": 4, "obs_nam": 4, "obsp": 4, "dm_kernel": 4, "kernel": 4, "dm_eigenvector": 4, "un": 4, "dmeigenvalu": 4, "determ": 4, "graph": 4, "requir": 4, "howeev": 4, "insight": 4, "investig": 4, "fluctuat": 4, "along": 4, "tempor": 4, "trajectori": 4, "differenti": 4, "hspc": 4, "dcomp": 4, "rang": 4, "ec": 4, "argmax": 4, "ob": 4, "mm": 4, "break": 4, "argmin": [4, 5], "minimum": 4, "els": 4, "rais": 4, "except": 4, "No": 4, "valid": 4, "compon": 4, "found": 4, "early_cel": 4, "print": 4, "earli": 4, "which": 4, "im": 4, "1393_bonemarrow_tcelldep_2_multiom": 4, "agccgctagacaagtg": 4, "ms_data": 4, "determine_multiscale_spac": 4, "pl_re": 4, "core": 4, "run_palantir": 4, "palantir_pseudotim": 4, "pl": 4, "scatter": 4, "basi": 4, "color": 4, "sampl": 4, "flock": 4, "waypoint": 4, "015990734100341797": 4, "minut": 4, "shortest": 4, "path": 4, "30": 4, "26976213455200193": 4, "refin": 4, "correl": 4, "9997": 4, "0000": 4, "entropi": 4, "branch": 4, "probabl": 4, "markov": 4, "chain": 4, "construct": 4, "identif": 4, "termin": 4, "fundament": 4, "absorpt": 4, "project": 4, "log_density_clip": 4, "clip": 4, "quantil": 4, "05": 4, "cpu": 4, "3min": 4, "29": 4, "sy": 4, "13": 4, "": 4, "total": 4, "42": 4, "wall": 4, "21": 4, "8": 4, "9": 4, "12": 4, "fig": 4, "ax1": 4, "ax2": 4, "subplot": 4, "width_ratio": 4, "boxplot": 4, "grid": 4, "rot": 4, "45": 4, "fontsiz": 4, "suptitl": 4, "set_titl": 4, "set_ylabel": 4, "mep": 4, "erypr": 4, "eri": 4, "ct_color": 4, "get": 4, "dict": 4, "zip": 4, "cat": 4, "categori": 4, "celltype_color": 4, "sct_color": 4, "ct": 4, "dddddd": 4, "idx": 4, "isin": 4, "color_vec": 4, "loc": 4, "selected_celltyp": 4, "astyp": 4, "selected_celltypes_color": 4, "c": 4, "set_xlabel": 4, "abov": 4, "follow": 4, "equival": 4, "code": 4, "chang": 4, "desir": 4, "11": 4, "compute_nn_dist": [4, 5], "regul": 4, "lower": 4, "produc": 4, "faster": 4, "more": 4, "detail": 4, "therefor": 4, "stabl": 4, "By": 4, "hurist": 4, "aim": 4, "maximix": 4, "posterio": 4, "compute_l": [4, 5], "structur": 4, "henc": 4, "proxi": 4, "while": 4, "ani": 4, "cluster": 4, "preform": 4, "best": 4, "our": 4, "limit": 4, "k_mean": 4, "n_init": 4, "34": 4, "01": 4, "35": 4, "22": 4, "further": 4, "reduc": 4, "improv": 4, "nystr\u00f6m": 4, "either": 4, "fraction": 4, "varianc": 4, "preserv": 4, "choleski": 4, "14": 4, "2min": 4, "37": 4, "50": 4, "assum": 4, "vari": 4, "howev": 4, "known": 4, "onli": 4, "subspac": 4, "tangenti": 4, "phenotyp": 4, "should": 4, "correctli": 4, "relat": 4, "15": 4, "suggest": 4, "invari": 4, "drop": 4, "quickli": 4, "16": 4, "compute_mu": [4, 5], "ridg": [4, 5], "regress": [4, 5], "speed": 4, "17": 4, "initial_paramet": 4, "compute_initial_valu": [4, 5], "43": 4, "44": 4, "55": 4, "19": 4, "instead": 4, "mai": 4, "split": 4, "three": 4, "allow": 4, "For": 4, "o": 4, "replac": 4, "optimal_paramet": 4, "after": 4, "Of": 4, "cours": 4, "work": 4, "full": 5, "decompost": 5, "compute_cov_func": 5, "compute_d": 5, "compute_landmark": 5, "landmark_point": 5, "given": 6}, "objects": {"mellon": [[0, 0, 0, "-", "cov"], [2, 0, 0, "-", "inference"], [3, 0, 0, "-", "model"], [5, 0, 0, "-", "parameters"], [6, 0, 0, "-", "util"]], "mellon.cov": [[0, 1, 1, "", "ExpQuad"], [0, 1, 1, "", "Exponential"], [0, 1, 1, "", "Matern32"], [0, 1, 1, "", "Matern52"], [0, 1, 1, "", "RatQuad"]], "mellon.cov.ExpQuad": [[0, 2, 1, "", "k"]], "mellon.cov.Exponential": [[0, 2, 1, "", "k"]], "mellon.cov.Matern32": [[0, 2, 1, "", "k"]], "mellon.cov.Matern52": [[0, 2, 1, "", "k"]], "mellon.cov.RatQuad": [[0, 2, 1, "", "k"]], "mellon.inference": [[2, 3, 1, "", "compute_conditional_mean"], [2, 3, 1, "", "compute_log_density_x"], [2, 3, 1, "", "compute_loss_func"], [2, 3, 1, "", "compute_transform"], [2, 3, 1, "", "minimize_adam"], [2, 3, 1, "", "minimize_lbfgsb"]], "mellon.model": [[3, 1, 1, "", "BaseEstimator"], [3, 1, 1, "", "DensityEstimator"], [3, 1, 1, "", "FunctionEstimator"]], "mellon.model.BaseEstimator": [[3, 2, 1, "", "fit"], [3, 2, 1, "", "fit_predict"], [3, 2, 1, "", "gradient"], [3, 2, 1, "", "hessian"], [3, 2, 1, "", "hessian_log_determinant"], [3, 2, 1, "", "predict"], [3, 2, 1, "", "prepare_inference"]], "mellon.model.DensityEstimator": [[3, 2, 1, "", "fit"], [3, 2, 1, "", "fit_predict"], [3, 2, 1, "", "predict"], [3, 2, 1, "", "prepare_inference"], [3, 2, 1, "", "process_inference"], [3, 2, 1, "", "run_inference"]], "mellon.model.FunctionEstimator": [[3, 2, 1, "", "compute_conditional"], [3, 2, 1, "", "fit"], [3, 2, 1, "", "fit_predict"], [3, 2, 1, "", "predict"], [3, 2, 1, "", "prepare_inference"]], "mellon.parameters": [[5, 3, 1, "", "compute_L"], [5, 3, 1, "", "compute_cov_func"], [5, 3, 1, "", "compute_d"], [5, 3, 1, "", "compute_initial_value"], [5, 3, 1, "", "compute_landmarks"], [5, 3, 1, "", "compute_ls"], [5, 3, 1, "", "compute_mu"], [5, 3, 1, "", "compute_nn_distances"]], "mellon.util": [[6, 3, 1, "", "distance"], [6, 3, 1, "", "mle"], [6, 3, 1, "", "stabilize"]]}, "objtypes": {"0": "py:module", "1": "py:class", "2": "py:method", "3": "py:function"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "method", "Python method"], "3": ["py", "function", "Python function"]}, "titleterms": {"covari": 0, "function": 0, "implement": 0, "instal": 1, "document": 1, "basic": [1, 4], "usag": 1, "index": 1, "infer": 2, "model": 3, "tutori": 4, "load": 4, "data": 4, "preprocess": 4, "comput": 4, "pseudotim": 4, "option": 4, "densiti": 4, "exampl": 4, "analysi": 4, "adjust": 4, "paramet": [4, 5], "stage": 4, "api": 4, "deriv": 4, "select": 5, "util": 6}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 8, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "nbsphinx": 4, "sphinx": 57}, "alltitles": {"Covariance Functions": [[0, "covariance-functions"]], "Implemented Covariance Functions": [[0, "module-mellon.cov"]], "Installation": [[1, "installation"]], "Documentation": [[1, "documentation"]], "Basic Usage": [[1, "basic-usage"]], "Index": [[1, "index"]], "Inference": [[2, "module-mellon.inference"]], "Model": [[3, "module-mellon.model"]], "Basic Tutorial": [[4, "Basic-Tutorial"]], "Loading the data": [[4, "Loading-the-data"]], "Preprocessing": [[4, "Preprocessing"]], "Compute pseudotime (optional)": [[4, "Compute-pseudotime-(optional)"]], "Density computation": [[4, "Density-computation"]], "Example analysis": [[4, "Example-analysis"]], "Adjustable parameters": [[4, "Adjustable-parameters"]], "Stages API": [[4, "Stages-API"]], "Derivatives": [[4, "Derivatives"]], "Parameter Selection": [[5, "module-mellon.parameters"]], "Utilities": [[6, "module-mellon.util"]]}, "indexentries": {"expquad (class in mellon.cov)": [[0, "mellon.cov.ExpQuad"]], "exponential (class in mellon.cov)": [[0, "mellon.cov.Exponential"]], "matern32 (class in mellon.cov)": [[0, "mellon.cov.Matern32"]], "matern52 (class in mellon.cov)": [[0, "mellon.cov.Matern52"]], "ratquad (class in mellon.cov)": [[0, "mellon.cov.RatQuad"]], "k() (mellon.cov.expquad method)": [[0, "mellon.cov.ExpQuad.k"]], "k() (mellon.cov.exponential method)": [[0, "mellon.cov.Exponential.k"]], "k() (mellon.cov.matern32 method)": [[0, "mellon.cov.Matern32.k"]], "k() (mellon.cov.matern52 method)": [[0, "mellon.cov.Matern52.k"]], "k() (mellon.cov.ratquad method)": [[0, "mellon.cov.RatQuad.k"]], "mellon.cov": [[0, "module-mellon.cov"]], "module": [[0, "module-mellon.cov"], [2, "module-mellon.inference"], [3, "module-mellon.model"], [5, "module-mellon.parameters"], [6, "module-mellon.util"]], "compute_conditional_mean() (in module mellon.inference)": [[2, "mellon.inference.compute_conditional_mean"]], "compute_log_density_x() (in module mellon.inference)": [[2, "mellon.inference.compute_log_density_x"]], "compute_loss_func() (in module mellon.inference)": [[2, "mellon.inference.compute_loss_func"]], "compute_transform() (in module mellon.inference)": [[2, "mellon.inference.compute_transform"]], "mellon.inference": [[2, "module-mellon.inference"]], "minimize_adam() (in module mellon.inference)": [[2, "mellon.inference.minimize_adam"]], "minimize_lbfgsb() (in module mellon.inference)": [[2, "mellon.inference.minimize_lbfgsb"]], "baseestimator (class in mellon.model)": [[3, "mellon.model.BaseEstimator"]], "densityestimator (class in mellon.model)": [[3, "mellon.model.DensityEstimator"]], "functionestimator (class in mellon.model)": [[3, "mellon.model.FunctionEstimator"]], "compute_conditional() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.compute_conditional"]], "fit() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.fit"]], "fit() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.fit"]], "fit() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.fit"]], "fit_predict() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.fit_predict"]], "fit_predict() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.fit_predict"]], "fit_predict() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.fit_predict"]], "gradient() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.gradient"]], "hessian() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.hessian"]], "hessian_log_determinant() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.hessian_log_determinant"]], "mellon.model": [[3, "module-mellon.model"]], "predict() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.predict"]], "predict() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.predict"]], "predict() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.predict"]], "prepare_inference() (mellon.model.baseestimator method)": [[3, "mellon.model.BaseEstimator.prepare_inference"]], "prepare_inference() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.prepare_inference"]], "prepare_inference() (mellon.model.functionestimator method)": [[3, "mellon.model.FunctionEstimator.prepare_inference"]], "process_inference() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.process_inference"]], "run_inference() (mellon.model.densityestimator method)": [[3, "mellon.model.DensityEstimator.run_inference"]], "compute_l() (in module mellon.parameters)": [[5, "mellon.parameters.compute_L"]], "compute_cov_func() (in module mellon.parameters)": [[5, "mellon.parameters.compute_cov_func"]], "compute_d() (in module mellon.parameters)": [[5, "mellon.parameters.compute_d"]], "compute_initial_value() (in module mellon.parameters)": [[5, "mellon.parameters.compute_initial_value"]], "compute_landmarks() (in module mellon.parameters)": [[5, "mellon.parameters.compute_landmarks"]], "compute_ls() (in module mellon.parameters)": [[5, "mellon.parameters.compute_ls"]], "compute_mu() (in module mellon.parameters)": [[5, "mellon.parameters.compute_mu"]], "compute_nn_distances() (in module mellon.parameters)": [[5, "mellon.parameters.compute_nn_distances"]], "mellon.parameters": [[5, "module-mellon.parameters"]], "distance() (in module mellon.util)": [[6, "mellon.util.distance"]], "mellon.util": [[6, "module-mellon.util"]], "mle() (in module mellon.util)": [[6, "mellon.util.mle"]], "stabilize() (in module mellon.util)": [[6, "mellon.util.stabilize"]]}}) \ No newline at end of file