diff --git a/.pylintrc b/.pylintrc index a93ff7b..a5c5493 100644 --- a/.pylintrc +++ b/.pylintrc @@ -15,7 +15,7 @@ ignore-patterns= # Python code to execute, usually for sys.path manipulation such as # pygtk.require(). -#init-hook= +init-hook="import sys; import os; sys.path.append(os.path.abspath('.'));" # Use multiple processes to speed up Pylint. jobs=1 @@ -62,6 +62,7 @@ disable=missing-docstring, too-many-branches, too-many-statements, too-few-public-methods, + import-error, diff --git a/docs/examples/quick-start.ipynb b/docs/examples/quick-start.ipynb index 7618cbb..a38be5c 100644 --- a/docs/examples/quick-start.ipynb +++ b/docs/examples/quick-start.ipynb @@ -31,7 +31,7 @@ }, { "cell_type": "markdown", - "id": "7ffc669a", + "id": "bbfbe167", "metadata": {}, "source": [ "## Data\n", @@ -49,61 +49,10 @@ "# define the data\n", "RANDOM_SEED = 453\n", "np.random.seed(RANDOM_SEED)\n", - "x = np.random.normal(0, 0.25, 121)\n", - "y = np.random.normal(0, 1, 121)\n", - "z = np.random.normal(2 * x + 3, 0.1)\n", - "data = pd.DataFrame({\"x\": x, \"y\": y, \"z\": z})" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "4d34d403", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Marginal of y in terms of z')" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# plot the data\n", - "fig = plt.figure(figsize=(18, 6))\n", - "\n", - "ax = fig.add_subplot(1, 3, 1, projection=\"3d\")\n", - "ax.plot(data[\"x\"], data[\"y\"], data[\"z\"], \"o\")\n", - "ax.set_xlabel(\"x\")\n", - "ax.set_ylabel(\"y\")\n", - "ax.set_zlabel(\"z\")\n", - "ax.set_title(\"3D plot of the toy dataset\")\n", - "\n", - "ax = fig.add_subplot(1, 3, 2)\n", - "ax.plot(data[\"x\"], data[\"y\"], \"o\")\n", - "ax.set_xlabel(\"x\")\n", - "ax.set_ylabel(\"y\")\n", - "ax.set_title(\"Marginal of y in terms of x\")\n", - "\n", - "ax = fig.add_subplot(1, 3, 3)\n", - "ax.plot(data[\"z\"], data[\"y\"], \"o\")\n", - "ax.set_xlabel(\"z\")\n", - "ax.set_ylabel(\"y\")\n", - "ax.set_title(\"Marginal of y in terms of z\")" + "x1 = np.random.normal(0, 0.5, 121)\n", + "x2 = np.random.normal(0, 1, 121)\n", + "y = np.random.normal(2 * x1 + 3, 0.25)\n", + "data = pd.DataFrame({\"x1\": x1, \"x2\": x2, \"y\": y})" ] }, { @@ -111,20 +60,20 @@ "id": "5d3fbe1b", "metadata": {}, "source": [ - "### The model\n", + "## The model\n", "\n", "We presently look to fit a linear regression to these data, namely the model \n", "\n", "$$\n", - "z \\sim \\mathcal{N} (\\beta_0 + \\beta_1 x + \\beta_2 y, \\sigma)\n", + "y \\sim \\mathcal{N} (\\beta_0 + \\beta_1 x_1 + \\beta_2 x_2, \\sigma)\n", "$$\n", "\n", - "with $\\sigma>0$ and $\\beta_i \\in \\mathbb{R}$, in which we treat $z$ as our variate, and $x$ and $y$ as the covariates. This is cleanly communicated to `bambi` in the following formula, and we fit the model with Markov Chain Monte Carlo (MCMC) methods. We will use the default `bambi` priors over $\\beta_i$ and $\\sigma$, on which more information can be found in [the `bambi` docs](https://bambinos.github.io/bambi/main/index.html)." + "with $\\sigma>0$ and $\\beta_i \\in \\mathbb{R}$, in which we treat $y$ as our variate, and $x_1$ and $x_2$ as the covariates. This is cleanly communicated to `bambi` in the following formula, and we fit the model with Markov Chain Monte Carlo (MCMC) methods. We will use the default `bambi` priors over $\\beta_i$ and $\\sigma$, on which more information can be found in [the `bambi` docs](https://bambinos.github.io/bambi/main/index.html)." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "92ef6fe8", "metadata": { "scrolled": false @@ -137,7 +86,7 @@ "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Multiprocess sampling (4 chains in 4 jobs)\n", - "NUTS: [z_sigma, Intercept, x, y]\n" + "NUTS: [y_sigma, Intercept, x1, x2]\n" ] }, { @@ -173,7 +122,7 @@ "\n", "
\n", " \n", - " 100.00% [8000/8000 00:07<00:00 Sampling 4 chains, 0 divergences]\n", + " 100.00% [8000/8000 00:02<00:00 Sampling 4 chains, 0 divergences]\n", "
\n", " " ], @@ -188,14 +137,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 8 seconds.\n" + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 3 seconds.\n" ] } ], "source": [ "# fit the reference model\n", - "model = bmb.Model(\"z ~ x + y\", data)\n", - "idata = model.fit(random_seed=RANDOM_SEED, idata_kwargs={'log_likelihood': True})" + "model = bmb.Model(\"y ~ x1 + x2\", data)\n", + "idata = model.fit(random_seed=RANDOM_SEED, idata_kwargs={\"log_likelihood\": True})" ] }, { @@ -203,20 +152,19 @@ "id": "22321fdb", "metadata": {}, "source": [ - "### Projection predictive model selection\n", + "## Projection predictive model selection\n", "\n", - "We now perform the model selection procedure provided by `kulprit`. Our linear regression model is considered as the _reference model_, and we look to identify subsets of its parameters that achieve similar predictive performance. To begin with, let us build this core `ReferenceModel` object from the `bambi` model." + "We now perform the model selection procedure provided by `kulprit`. Our linear regression model is considered as the _reference model_, and we look to identify subsets of its parameters that achieve similar predictive performance. To begin with, let us instanciate `ProjectionPredictive` class." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "8f4cd748", "metadata": {}, "outputs": [], "source": [ - "# build reference model object\n", - "ref_model = kpt.ReferenceModel(model, idata)" + "ppi = kpt.ProjectionPredictive(model, idata)" ] }, { @@ -236,24 +184,24 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "cd0aafa2", "metadata": {}, "outputs": [], "source": [ "# perform the search procedure\n", - "ref_model.search()" + "ppi.search()" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "272f5a38", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -264,7 +212,7 @@ ], "source": [ "# compare the projected posterior densities of the submodels\n", - "ax = ref_model.plot_densities();" + "ax = ppi.plot_densities();" ] }, { @@ -277,13 +225,13 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "70dcd723", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -294,7 +242,7 @@ ], "source": [ "# compare submodels found in the search by LOO-CV ELPD\n", - "cmp, ax = ref_model.loo_compare(plot=True, figsize=(10, 4));" + "cmp, ax = ppi.plot_compare(plot=True, figsize=(10, 4));" ] }, { @@ -302,28 +250,30 @@ "id": "43c0a9ca", "metadata": {}, "source": [ - "From these results we can see that the difference between the reference model and the model with only one parameter is very small. Thus we may want to keep this smaller model. In the following cell we can see that the model is `z-x`" + "From these results we can see that the difference between the reference model and the model with only one parameter is very small. Thus we may want to keep this smaller model. In the following cell we can see that the model is `y ~ x1`." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "b54d4b37", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Formula(z ~ 1)\n", - "Formula(z ~ x)\n", - "Formula(z ~ x + y)\n" - ] + "data": { + "text/plain": [ + " 0 y ~ 1\n", + " 1 y ~ x1\n", + " 2 y ~ x1 + x2" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "for value in ref_model.path.values(): \n", - " print(value.model.formula)" + "ppi" ] }, { @@ -331,18 +281,44 @@ "id": "36784f28", "metadata": {}, "source": [ - "We can obtain the submodel as follows." + "We can obtain the submodel by specifying its size." ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "0e293770", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "SubModel(model= Formula: y ~ x1\n", + " Family: gaussian\n", + " Link: mu = identity\n", + " Observations: 121\n", + " Priors: \n", + " target = mu\n", + " Common-level effects\n", + " Intercept ~ Normal(mu: 3.073, sigma: 2.0801)\n", + " x1 ~ Normal(mu: 0.0, sigma: 4.9941)\n", + " \n", + " Auxiliary parameters\n", + " sigma ~ HalfStudentT(nu: 4.0, sigma: 0.8306), idata=Inference data with groups:\n", + "\t> posterior\n", + "\t> log_likelihood\n", + "\t> observed_data, loss=1.7920088583588454, size=1, term_names=['x1'])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# project the reference model onto a chosen submodel size\n", - "submodel = ref_model.project(\"x\")" + "submodel = ppi.project(1)\n", + "submodel" ] }, { @@ -355,15 +331,15 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "id": "477f3ad4", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -371,9 +347,17 @@ } ], "source": [ - "# visualise projected parameters\n", - "ax = az.plot_posterior(submodel.idata, var_names=[\"Intercept\", \"x\"]);" + "# visualize projected parameters\n", + "ax = az.plot_posterior(submodel.idata);" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "877d5e68", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/kulprit/__init__.py b/kulprit/__init__.py index 0153f59..0ac9044 100644 --- a/kulprit/__init__.py +++ b/kulprit/__init__.py @@ -4,11 +4,11 @@ Kullback-Leibler projections for Bayesian model selection. """ -from kulprit.reference import ReferenceModel +from kulprit.reference import ProjectionPredictive from kulprit.datasets import * __version__ = "0.0.1" -__all__ = ["ReferenceModel"] +__all__ = ["ProjectionPredictive"] diff --git a/kulprit/projection/projector.py b/kulprit/projection/projector.py index 9d5fffd..3575f90 100644 --- a/kulprit/projection/projector.py +++ b/kulprit/projection/projector.py @@ -38,7 +38,7 @@ def __init__( The inference data object corresponding to the reference model. path : dict An optional search path dictionary, initialized to None and assigned by the - ReferenceModel parent object following a search for efficient submodel retrieval. + ProjectionPredictive parent object following a search for efficient submodel retrieval. """ # log reference model and reference inference data object diff --git a/kulprit/projection/solver.py b/kulprit/projection/solver.py index 5969f49..7ebb3db 100644 --- a/kulprit/projection/solver.py +++ b/kulprit/projection/solver.py @@ -1,6 +1,7 @@ -"""Optimisation module.""" +"""optimization module.""" from typing import List, Optional +import warnings import arviz as az import bambi as bmb @@ -55,43 +56,7 @@ def pps(self): ).values.T return pps - def linear_predict( - self, - beta_x: np.ndarray, - X: Optional[np.ndarray] = None, - ) -> np.ndarray: - """Predict the latent predictor of the submodel. - - Parameters: - ---------- - beta_x : np.ndarray - The model's projected posterior - X : np.ndarray - The model's common design matrix - - Returns - ------- - np.ndarray: Point estimate of the latent predictor using the single draw from the - posterior and the model's design matrix - """ - - linear_predictor = np.zeros(shape=(X.shape[0],)) - - # Contribution due to common terms - if X is not None: - - if len(beta_x.shape) > 1: # pragma: no cover - raise NotImplementedError("Currently this method only works for single samples.") - - # 'contribution' is of shape: - # * (obs_n, ) for univariate - contribution = np.dot(X, beta_x.T).T - linear_predictor += contribution - - # return the latent predictor - return linear_predictor - - def _init_optimisation(self, term_names: List[str]) -> List[float]: + def _init_optimization(self, term_names: List[str]) -> List[float]: """Initialise the optimization with the reference posterior means.""" return np.hstack( @@ -101,24 +66,26 @@ def _init_optimisation(self, term_names: List[str]) -> List[float]: def _build_bounds(self, init: List[float]) -> list: """Build bounds for the parameters in the optimization. - This method is used to ensure that dispersion or other auxiliary - parameters present in certain families remain within their valid regions. + This method is used to ensure that dispersion or other auxiliary parameters present + in certain families remain within their valid regions. Parameters: ---------- - init : (List[float]) + init : List[float] The list of initial parameter values Returns: ------- - List : [Tuple(float)]The upper and lower bounds for each initialized parameter in - the optimization + List : [Tuple(float)] + The upper and lower bounds for each initialized parameter in the optimization """ + eps = np.finfo(np.float64).eps - # build bounds based on family + # build bounds based on family, we are assuming that the last parameter is the dispersion + # and that the other parameters are unbounded (like when using Gaussian priors) if self.ref_family in ["gaussian"]: # account for the dispersion parameter - bounds = [(None, None)] * (init.size - 1) + [(0, None)] + bounds = [(None, None)] * (init.size - 1) + [(eps, None)] elif self.ref_family in ["binomial", "poisson"]: # no dispersion parameter, so no bounds bounds = [(None, None)] * (init.size) @@ -140,7 +107,7 @@ def objective( Parameters: ---------- params : array_like - The optimisation parameters mean values + The optimization parameters mean values obs : array_like One sample from the posterior predictive distribution of the reference model X : array_like @@ -153,19 +120,19 @@ def objective( # Gaussian observation likelihood if self.ref_family == "gaussian": - linear_predictor = self.linear_predict(beta_x=params[:-1], X=X) + linear_predictor = _linear_predict(beta_x=params[:-1], X=X) neg_llk = self.neg_log_likelihood(points=obs, mean=linear_predictor, sigma=params[-1]) # Binomial observation likelihood elif self.ref_family == "binomial": trials = self.ref_model.response.data[:, 1] - linear_predictor = self.linear_predict(beta_x=params, X=X) + linear_predictor = _linear_predict(beta_x=params, X=X) probs = self.ref_model.family.link.linkinv(linear_predictor) neg_llk = self.neg_log_likelihood(points=obs, probs=probs, trials=trials) # Poisson observation likelihood elif self.ref_family == "poisson": - linear_predictor = self.linear_predict(beta_x=params, X=X) + linear_predictor = _linear_predict(beta_x=params, X=X) lam = self.ref_model.family.link.linkinv(linear_predictor) neg_llk = self.neg_log_likelihood(points=obs, lam=lam) return neg_llk @@ -191,25 +158,29 @@ def solve(self, term_names: List[str], X: np.ndarray, slices: dict) -> SubModel: SubModel: The projected submodel object """ - # initialise the optimisation - init = self._init_optimisation(term_names=term_names) + # use reference model posterior as initial guess + init = self._init_optimization(term_names=term_names) - # build the optimisation parameter bounds + # build the optimization parameter bounds bounds = self._build_bounds(init) # perform mean-field variational projection predictive inference res_posterior = [] objectives = [] - for obs in self.pps: - opt = minimize( - self.objective, - args=(obs, X), - x0=init, # use reference model posterior as initial guess - bounds=bounds, # apply bounds - method="powell", - ) - res_posterior.append(opt.x) - objectives.append(opt.fun) + with warnings.catch_warnings(): + warnings.filterwarnings("ignore", message="Values in x were outside bounds") + for obs in self.pps: + opt = minimize( + self.objective, + args=(obs, X), + x0=init, + tol=0.0001, + bounds=bounds, + # This is the fastest method and the projected posterior looks Gaussian-like + method="SLSQP", + ) + res_posterior.append(opt.x) + objectives.append(opt.fun) # compile the projected posterior res_samples = np.vstack(res_posterior) @@ -243,3 +214,38 @@ def solve(self, term_names: List[str], X: np.ndarray, slices: dict) -> SubModel: # compute the average loss loss = np.mean(objectives) return posterior, loss + + +def _linear_predict( + beta_x: np.ndarray, + X: Optional[np.ndarray] = None, +) -> np.ndarray: + """Predict the latent predictor of the submodel. + + Parameters: + ---------- + beta_x : np.ndarray + The model's projected posterior + X : np.ndarray + The model's common design matrix + + Returns + ------- + np.ndarray: Point estimate of the latent predictor using the single draw from the + posterior and the model's design matrix + """ + + linear_predictor = np.zeros(shape=(X.shape[0],)) + + # Contribution due to common terms + if X is not None: + + if len(beta_x.shape) > 1: + raise NotImplementedError("Currently this method only works for single samples.") + + # 'contribution' is of shape * (obs_n, ) for univariate + contribution = np.dot(X, beta_x.T).T + linear_predictor += contribution + + # return the latent predictor + return linear_predictor diff --git a/kulprit/reference.py b/kulprit/reference.py index 38a60dc..6fb978c 100644 --- a/kulprit/reference.py +++ b/kulprit/reference.py @@ -11,13 +11,14 @@ import pandas as pd from kulprit.data.submodel import SubModel +from kulprit.plots.plots import plot_compare from kulprit.projection.projector import Projector from kulprit.search.searcher import Searcher -class ReferenceModel: +class ProjectionPredictive: """ - Reference model class from which we perform the model selection procedure. + Projection Predictive class from which we perform the model selection procedure. """ def __init__( @@ -25,25 +26,22 @@ def __init__( model: bmb.models.Model, idata: Optional[az.InferenceData] = None, ) -> None: - """Reference model builder for projection predictive model selection. + """Builder for projection predictive model selection. - This object initialises the reference model and handles the core - projection and variable search methods of the model selection procedure. + This object initializes the reference model and handles the core projection, variable search + methods and submodel comparison. - Note that throughout the procedure, variables with names of the form - ``*_ast`` belong to the reference model while variables with names like - ``*_perp`` belong to the restricted model. This is to preserve notation - choices from previous papers on the topic. - - Args: - model (bmb.models.Model): The referemce GLM model to project - idata (az.InferenceData): The ArviZ InferenceData object - of the fitted reference model + Parameters: + ---------- + model : Bambi model + The reference GLM model to project + idata : InferenceData + The ArviZ InferenceData object of the fitted reference model """ # test that the reference model has an intercept term if model.response_component.intercept_term is None: raise UserWarning( - "The procedure currently requires reference models to have an" + " intercept term." + "The procedure currently requires reference models to have an intercept term." ) # test that the reference model does not admit any hierarchical structure @@ -60,32 +58,53 @@ def __init__( ) # test compatibility between model and idata - if not test_model_idata_compatability(model=model, idata=idata): + if not check_model_idata_compatability(model=model, idata=idata): raise UserWarning("Incompatible model and inference data.") # log reference model and inference data self.model = model self.idata = idata - # instantiate projector, search, and search path classes + # instantiate projector, searcher classes self.projector = Projector(model=self.model, idata=self.idata) self.searcher = Searcher(self.projector) + # we have not yet run a search self.path = None + def __repr__(self) -> str: + """String representation of the reference model.""" + + # return the formular for the reference model if no search has been run + if self.path is None: + return ( + f"ReferenceModel(" + f"{', '.join([self.model.formula.main] + list(self.model.formula.additionals))})" + ) + + # otherwise return the formulas for the submodels + else: + str_of_submodels = "\n".join( + f"{idx:>3}" + f"{', '.join([value.model.formula.main] + list(value.model.formula.additionals))}" + for idx, value in enumerate(self.path.values()) + ) + return str_of_submodels + def project( self, terms: Union[List[str], Tuple[str], int], ) -> SubModel: """Projection the reference model onto a variable subset. - Args: - terms (Union[List[str], Tuple[str], int]): Collection of strings - containing the names of the parameters to include the submodel, - or the number of parameters to include in the submodel, **not** - including the intercept term + Parameters: + ----------- + terms : Union[List[str], Tuple[str], int] + Collection of strings containing the names of the parameters to include the submodel, + or the number of parameters to include in the submodel, not including the intercept term Returns: - kulprit.data.SubModel: Projected submodel object + -------- + kulprit.data.SubModel: Projected submodel object """ # project the reference model onto a subset of covariates @@ -96,26 +115,25 @@ def search( self, max_terms: Optional[int] = None, method: Literal["forward", "l1"] = "forward", - return_path: Optional[bool] = False, ) -> Optional[dict]: """Model search method through parameter space. - If ``max_terms`` is not provided, then the search path runs from the - intercept-only model up to but not including the full model, in other - words we set ``max_terms = data.num_terms - 1``. + If ``max_terms`` is not provided, then the search path runs from the intercept-only model + up to but not including the full model. - Args: - max_terms (int): The number of parameters of the largest submodel in - the search path, **not** including the intercept term - method (str): The search method to employ, either "forward" to - employ a forward search heuristic through the space, or "l1" to - use the L1-regularised search path - return_path (bool): Whether or not to return the search path as a - dictionary object to the user + Parameters: + ----------- + max_terms : int + The number of parameters of the largest submodel in the search path, not including the + intercept term. + method : str + The search method to employ, either "forward" to employ a forward search heuristic + through the space, or "l1" to use the L1-regularized search path. Returns: - dict: The model selection procedure search path, containing the - submodels along the search path, keyed by their model size + -------- + dict: The model selection procedure search path, containing the submodels along the + search path, keyed by their model size. """ # set default `max_terms` value @@ -136,13 +154,7 @@ def search( method=method, ) - # return the path dictionary if specified - if return_path: - return self.path - else: - return None - - def loo_compare( + def plot_compare( self, plot: Optional[bool] = False, legend: Optional[bool] = True, @@ -152,49 +164,69 @@ def loo_compare( ) -> Tuple[pd.DataFrame, matplotlib.axes.Axes]: """Compare the ELPD of the projected models along the search path. - Args: - plot : bool, default False - Plot the results of the comparison. - legend : bool, default True - Add legend to figure. - title : bool - Show a tittle with a description of how to interpret the plot. - Defaults to True. - figsize : (float, float), optional - If None, size is (10, num of submodels) inches - plot_kwargs : dict, optional - Optional arguments for plot elements. Currently accepts 'color_elpd', - 'marker_elpd', 'marker_fc_elpd', 'color_dse' 'marker_dse', - 'ls_reference' 'color_ls_reference'. + Parameters: + ----------- + plot : bool + Plot the results of the comparison. Defaults to False + legend : bool + Add legend to figure. Defaults to True. + title : bool + Show a tittle with a description of how to interpret the plot. Defaults to True. + figsize : tuple + If None, size is (10, num of submodels) inches + plot_kwargs : dict + Optional arguments for plot elements. Currently accepts 'color_elpd', 'marker_elpd', + 'marker_fc_elpd', 'color_dse' 'marker_dse', 'ls_reference' 'color_ls_reference'. Returns: - A DataFrame, ordered from largest to smaller model. The columns are: - rank: The rank-order of the models. 0 is the best. - elpd: ELPD estimated either using (PSIS-LOO-CV). - Higher ELPD indicates higher out-of-sample predictive fit - ("better" model). - pIC: Estimated effective number of parameters. - elpd_diff: The difference in ELPD between two models. - The difference is computed relative to the reference model - weight: Relative weight for each model. - This can be loosely interpreted as the probability of each model - (among the compared model) given the data. - SE: Standard error of the ELPD estimate. - dSE: Standard error of the difference in ELPD between each model and - the top-ranked model. It's always 0 for the reference model. - warning: A value of 1 indicates that the computation of the ELPD may - not be reliable. This could be indication of PSIS-LOO-CV starting - to fail see http://arxiv.org/abs/1507.04544 for details. - scale: Scale used for the ELPD. This is always the log scale - axes : matplotlib_axes or bokeh_figure + -------- + A DataFrame, ordered from largest to smaller model. The columns are: + rank: The rank-order of the models. 0 is the best. + elpd: ELPD estimated either using (PSIS-LOO-CV). + Higher ELPD indicates higher out-of-sample predictive fit + ("better" model). + pIC: Estimated effective number of parameters. + elpd_diff: The difference in ELPD between two models. + The difference is computed relative to the reference model + weight: Relative weight for each model. + This can be loosely interpreted as the probability of each model + (among the compared model) given the data. + SE: Standard error of the ELPD estimate. + dSE: Standard error of the difference in ELPD between each model and + the top-ranked model. It's always 0 for the reference model. + warning: A value of 1 indicates that the computation of the ELPD may + not be reliable. This could be indication of PSIS-LOO-CV starting + to fail see http://arxiv.org/abs/1507.04544 for details. + scale: Scale used for the ELPD. This is always the log scale + axes : matplotlib_axes or bokeh_figure """ - comparison, axes = self.searcher.loo_compare( - plot=plot, - legend=legend, - title=title, - figsize=figsize, - plot_kwargs=plot_kwargs, - ) + + # test that search has been previously run + if self.searcher.search_completed is False: + raise UserWarning("Please run search before comparing submodels.") + + # initiate plotting arguments if none provided + if plot_kwargs is None: + plot_kwargs = {} + + self.searcher.idatas = {} # pylint: disable=attribute-defined-outside-init + + # make dictionary of inferencedata objects for each projection + for k, submodel in self.searcher.path.k_submodel.items(): + self.searcher.idatas[k] = submodel.idata + self.searcher.idatas[ + k + 1 # pylint: disable=undefined-loop-variable + ] = self.searcher.projector.idata + + # compare the submodels using loo (other criteria may be added in the future) + comparison = az.compare(self.searcher.idatas) + comparison.sort_index(ascending=False, inplace=True) + + # plot the comparison if requested + axes = None + if plot: + axes = plot_compare(comparison, legend, title, figsize, **plot_kwargs) + return comparison, axes def plot_densities( @@ -208,7 +240,7 @@ def plot_densities( # set default variable names to the reference model terms if not var_names: var_names = list( - set(self.model.response_component.terms.keys()) - set(self.model.response_name) + set(self.model.response_component.terms.keys()) - set([self.model.response_name]) ) axes = az.plot_density( @@ -222,18 +254,22 @@ def plot_densities( return axes -def test_model_idata_compatability(model, idata): - """Test that the Bambi model and idata are compatible with vanilla procedure. +def check_model_idata_compatability(model, idata): + """Check that the Bambi model and idata are compatible with vanilla procedure. In the future, this will be extended to allow for different structures and - covariates, testing instead only that the observation data are the same. + covariates, checking instead only that the observation data are the same. - Args: - model (bmb.models.Model): The reference Bambi model object - idata (az.InferenceData): The reference model fitted inference data obejct + Parameters: + ---------- + model : Bambi model + The reference GLM model to project + idata : InferenceData + The ArviZ InferenceData object of the fitted reference model Returns: - bool: Indicator of whether the two objects are compatible + ------- + bool : Indicator of whether the two objects are compatible """ # test that the variate's name is the same in reference model and idata diff --git a/kulprit/search/forward.py b/kulprit/search/forward.py index 2979426..2825502 100644 --- a/kulprit/search/forward.py +++ b/kulprit/search/forward.py @@ -54,13 +54,15 @@ def add_submodel( def get_candidates(self, k: int) -> List[List]: """Method for extracting a list of all candidate submodels. - Args: - k (int): The number of terms in the previous submodel, from which we - wish to find all possible candidate submodels + Parameters: + ---------- + k : int + The number of terms in the previous submodel, from which we wish to find all + possible candidate submodels. Returns: - List[List]: A list of lists, each containing the terms of all candidate - submodels + ------- + List: A list of lists, each containing the terms of all candidate submodels """ prev_subset = self.k_term_names[k - 1] @@ -74,13 +76,14 @@ def search( ) -> dict: """Forward search through the parameter space. - Args: - max_terms (int): Number of terms to perform the forward search - up to. + Parameters: + ---------- + max_terms : int + Number of terms to perform the forward search up to. Returns: - dict: A dictionary of submodels, keyed by the number of terms in the - submodel. + ------- + dict: A dictionary of submodels, keyed by the number of terms in the submodel. """ # initial intercept-only subset diff --git a/kulprit/search/searcher.py b/kulprit/search/searcher.py index 7d91be5..153aa1b 100644 --- a/kulprit/search/searcher.py +++ b/kulprit/search/searcher.py @@ -1,20 +1,15 @@ """Core search module.""" -from typing import Optional from typing_extensions import Literal -import pandas as pd -import arviz as az - from kulprit.projection.projector import Projector -from kulprit.plots.plots import plot_compare from kulprit.search.forward import ForwardSearchPath from kulprit.search.l1 import L1SearchPath class Searcher: def __init__(self, projector: Projector) -> None: - """Initialise forward search class. + """Initialise forward or l1 search class. Parameters: ---------- @@ -79,58 +74,3 @@ def search(self, max_terms: int, method: Literal["forward", "l1"] = "forward") - # return the final search path return k_submodels - - def loo_compare( - self, - plot: Optional[bool] = False, - legend: Optional[bool] = True, - title: Optional[bool] = True, - figsize: Optional[tuple] = None, - plot_kwargs: Optional[dict] = None, - ) -> pd.DataFrame: - """ - Rank submodels by ELPD and plot the comparison. - - Parameters: - ---------- - plot : bool - Whether or not to plot the comparison. - legend : bool - Whether or not to include a legend in the plot. - title : bool - Whether or not to include a title in the plot. - figsize : tuple - Figure size for the plot. - plot_kwargs : dict - Keyword arguments for the plot. - - Returns: - ------- - pd.DataFrame: A dataframe of the comparison results. - axes: A tuple of matplotlib axes objects. - """ - # test that search has been previously run - if self.search_completed is False: - raise UserWarning("Please run search before comparing submodels.") - - # initiate plotting arguments if none provided - if plot_kwargs is None: - plot_kwargs = {} - - self.idatas = {} # pylint: disable=attribute-defined-outside-init - - # make dictionary of inferencedata objects for each projection - for k, submodel in self.path.k_submodel.items(): - self.idatas[k] = submodel.idata - self.idatas[k + 1] = self.projector.idata # pylint: disable=undefined-loop-variable - - # compare the submodels by some criterion - comparison = az.compare(self.idatas) - comparison.sort_index(ascending=False, inplace=True) - - # plot the comparison if requested - axes = None - if plot: - axes = plot_compare(comparison, legend, title, figsize, **plot_kwargs) - - return comparison, axes diff --git a/tests/conftest.py b/tests/conftest.py index 8ab497a..acc9571 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,9 +1,10 @@ """Module for storing fixtures used in kulprit tests.""" +# pylint: disable=redefined-outer-name +import pytest -import kulprit as kpt import bambi as bmb -import pytest +import kulprit as kpt # define model fitting options NUM_DRAWS, NUM_CHAINS = 500, 4 @@ -36,7 +37,7 @@ def ref_model(bambi_model, bambi_model_idata): # pragma: no cover """Initialise a Gaussian reference model for use in later tests.""" # build and return reference model object - return kpt.ReferenceModel(bambi_model, bambi_model_idata) + return kpt.ProjectionPredictive(bambi_model, bambi_model_idata) @pytest.fixture(scope="session") diff --git a/tests/test_project.py b/tests/test_project.py index df1d8f2..2789e89 100644 --- a/tests/test_project.py +++ b/tests/test_project.py @@ -7,7 +7,7 @@ import bambi as bmb import kulprit as kpt -from kulprit import ReferenceModel +from kulprit import ProjectionPredictive from tests import KulpritTest @@ -19,7 +19,7 @@ class TestProjector(KulpritTest): def test_idata_is_none(self, bambi_model): """Test that some inference data is automatically produced when None.""" - no_idata_ref_model = ReferenceModel(bambi_model) + no_idata_ref_model = ProjectionPredictive(bambi_model) assert no_idata_ref_model.idata is not None def test_no_intercept_error(self): @@ -33,7 +33,7 @@ def test_no_intercept_error(self): with pytest.raises(UserWarning): # build a bad reference model object - kpt.ReferenceModel(bad_model, bad_idata) + kpt.ProjectionPredictive(bad_model, bad_idata) def test_hierarchical_error(self): """Test that an error is raised when model is hierarchical.""" @@ -45,7 +45,7 @@ def test_hierarchical_error(self): with pytest.raises(NotImplementedError): # build a bad reference model object - kpt.ReferenceModel(bad_model) + kpt.ProjectionPredictive(bad_model) def test_unimplemented_family(self): """Test that an error is raised when an unimplemented family is used.""" @@ -62,7 +62,7 @@ def test_unimplemented_family(self): with pytest.raises(NotImplementedError): # build a bad reference model object - kpt.ReferenceModel(bad_model, bad_idata) + kpt.ProjectionPredictive(bad_model, bad_idata) def test_different_variate_name(self, bambi_model_idata): """Test that an error is raised when model and idata aren't compatible.""" @@ -82,7 +82,7 @@ def test_different_variate_name(self, bambi_model_idata): with pytest.raises(UserWarning): # build a bad reference model object - kpt.ReferenceModel(bad_model, bambi_model_idata) + kpt.ProjectionPredictive(bad_model, bambi_model_idata) def test_different_variate_dim(self, bambi_model_idata): """Test that an error is raised when model and idata aren't compatible.""" @@ -102,7 +102,7 @@ def test_different_variate_dim(self, bambi_model_idata): with pytest.raises(UserWarning): # build a bad reference model object - kpt.ReferenceModel(bad_model, bambi_model_idata) + kpt.ProjectionPredictive(bad_model, bambi_model_idata) def test_no_term_names_error(self, ref_model): """Test that an error is raised when no term names are provided.""" @@ -132,7 +132,7 @@ def test_project_categorical(self): target_accept=0.9, idata_kwargs={"log_likelihood": True}, ) - ref_model = kpt.ReferenceModel(model=model_cat, idata=fitted_cat) + ref_model = kpt.ProjectionPredictive(model=model_cat, idata=fitted_cat) sub_model = ref_model.project(terms=["gender"]) assert sub_model.size == 1 diff --git a/tests/test_search.py b/tests/test_search.py index 3a7c0ea..21c3784 100644 --- a/tests/test_search.py +++ b/tests/test_search.py @@ -48,7 +48,7 @@ def test_l1_categorical_error(self): ) with pytest.raises(NotImplementedError): - ref_model = kpt.ReferenceModel(model=model_cat, idata=fitted_cat) + ref_model = kpt.ProjectionPredictive(model=model_cat, idata=fitted_cat) ref_model.search(method="l1") def test_bad_search_method(self, ref_model): @@ -71,7 +71,7 @@ def test_loo(self, ref_model): ref_model_copy = copy.copy(ref_model) ref_model_copy.search() - cmp, _ = ref_model_copy.loo_compare() + cmp, _ = ref_model_copy.plot_compare() all(cmp.index == [0, 1, 2, 3]) def test_loo_with_no_search_path(self, ref_model): @@ -83,8 +83,8 @@ def test_loo_with_no_search_path(self, ref_model): # define and fit model with MCMC bambi_model = bmb.Model("z ~ x + y", data, family="gaussian") idata = bambi_model.fit(draws=self.NUM_DRAWS, chains=self.NUM_CHAINS) - ref_model = kpt.ReferenceModel(model=bambi_model, idata=idata) - ref_model.loo_compare() + ref_model = kpt.ProjectionPredictive(model=bambi_model, idata=idata) + ref_model.plot_compare() def test_forward_repr(self, ref_model): """Test the string representation of the forward search path.""" @@ -107,7 +107,7 @@ def test_plot_comparison(self, ref_model): ref_model_copy = copy.copy(ref_model) ref_model_copy.search() - ref_model_copy.loo_compare(plot=True, figsize=(10, 5)) + ref_model_copy.plot_compare(plot=True, figsize=(10, 5)) def test_plot_densities(self, ref_model): ref_model_copy = copy.copy(ref_model)