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version: 3.20.2 + version: 3.21.0 build: pyhd8ed1ab_0 subdir: noarch noarch: python - url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.20.2-pyhd8ed1ab_0.conda - sha256: 1e84fcfa41e0afdd87ff41e6fbb719c96a0e098c1f79be342293ab0bd8dea322 - md5: 4daaed111c05672ae669f7036ee5bba3 + url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.21.0-pyhd8ed1ab_0.conda + sha256: 232a30e4b0045c9de5e168dda0328dc0e28df9439cdecdfb97dd79c1c82c4cec + md5: fee389bf8a4843bd7a2248ce11b7f188 depends: - python >=3.8 license: MIT license_family: MIT purls: - pkg:pypi/zipp?source=hash-mapping - size: 21409 - timestamp: 1726248679175 + size: 21702 + timestamp: 1731262194278 - kind: conda name: zlib version: 1.3.1 diff --git a/pyfixest/estimation/FixestMulti_.py b/pyfixest/estimation/FixestMulti_.py index 9737581a..a8d6c992 100644 --- a/pyfixest/estimation/FixestMulti_.py +++ b/pyfixest/estimation/FixestMulti_.py @@ -386,7 +386,7 @@ def _estimate_all_models( self.all_fitted_models[FIT._model_name] = FIT - def to_list(self): + def to_list(self) -> list[Union[Feols, Fepois, Feiv]]: """ Return a list of all fitted models. diff --git a/pyfixest/estimation/feols_.py b/pyfixest/estimation/feols_.py index 6f83faa5..a2f3f8bc 100644 --- a/pyfixest/estimation/feols_.py +++ b/pyfixest/estimation/feols_.py @@ -1696,10 +1696,12 @@ def get_performance(self) -> None: ssy = np.sum((_Y - np.mean(_Y)) ** 2) if _has_weights: + ssy = np.sum(_Y**2) - np.sum(_Y**2) / np.sum(_weights) self._rmse = np.nan self._r2 = np.nan self._adj_r2 = np.nan else: + ssy = np.sum((_Y - np.mean(_Y)) ** 2) self._rmse = np.sqrt(ssu / _N) self._r2 = 1 - (ssu / ssy) self._adj_r2 = 1 - (ssu / ssy) * _adj_factor diff --git a/pyfixest/estimation/multcomp.py b/pyfixest/estimation/multcomp.py index e3abad8f..f089ed8f 100644 --- a/pyfixest/estimation/multcomp.py +++ b/pyfixest/estimation/multcomp.py @@ -4,12 +4,16 @@ import numpy as np import pandas as pd +from pyfixest.estimation.feiv_ import Feiv from pyfixest.estimation.feols_ import Feols from pyfixest.estimation.fepois_ import Fepois +from pyfixest.estimation.FixestMulti_ import FixestMulti from pyfixest.report.summarize import _post_processing_input_checks +ModelInputType = Union[FixestMulti, list[Union[Feols, Fepois, Feiv]]] -def bonferroni(models: list[Union[Feols, Fepois]], param: str) -> pd.DataFrame: + +def bonferroni(models: ModelInputType, param: str) -> pd.DataFrame: """ Compute Bonferroni adjusted p-values for multiple hypothesis testing. @@ -18,9 +22,8 @@ def bonferroni(models: list[Union[Feols, Fepois]], param: str) -> pd.DataFrame: Parameters ---------- - models : list[Feols, Fepois], Feols or Fepois - A list of models for which the p-values should be adjusted, or a Feols or - Fepois object. + models : A supported model object (Feols, Fepois, Feiv, FixestMulti) or a list of + Feols, Fepois & Feiv models. param : str The parameter for which the p-values should be adjusted. @@ -65,7 +68,7 @@ def bonferroni(models: list[Union[Feols, Fepois]], param: str) -> pd.DataFrame: def rwolf( - models: list[Union[Feols, Fepois]], + models: Union[FixestMulti, list[Union[Feols, Fepois]]], param: str, reps: int, seed: int, diff --git a/pyfixest/report/summarize.py b/pyfixest/report/summarize.py index 933b3f87..188a4647 100644 --- a/pyfixest/report/summarize.py +++ b/pyfixest/report/summarize.py @@ -1,4 +1,5 @@ import re +from collections.abc import ValuesView from typing import Optional, Union import numpy as np @@ -13,9 +14,13 @@ from pyfixest.report.utils import _relabel_expvar from pyfixest.utils.dev_utils import _select_order_coefs +ModelInputType = Union[ + FixestMulti, Feols, Fepois, Feiv, list[Union[Feols, Fepois, Feiv]] +] + def etable( - models: Union[list[Union[Feols, Fepois, Feiv]], FixestMulti], + models: ModelInputType, type: str = "gt", signif_code: Optional[list] = None, coef_fmt: str = "b \n (se)", @@ -40,8 +45,8 @@ def etable( Parameters ---------- - models : list - A list of models of type Feols, Feiv, Fepois. + models : A supported model object (Feols, Fepois, Feiv, FixestMulti) or a list of + Feols, Fepois & Feiv models. type : str, optional Type of output. Either "df" for pandas DataFrame, "md" for markdown, "gt" for great_tables, or "tex" for LaTeX table. Default is "gt". @@ -132,11 +137,6 @@ def etable( signif_code[0] < signif_code[1] < signif_code[2] ), "signif_code must be in increasing order" - # Check if models is of type FixestMulti - # If so, convert it to a list of models - if isinstance(models, FixestMulti): - models = models.to_list() - models = _post_processing_input_checks(models) if custom_stats is None: @@ -464,9 +464,7 @@ def etable( return None -def summary( - models: Union[list[Union[Feols, Fepois, Feiv]], FixestMulti], digits: int = 3 -) -> None: +def summary(models: ModelInputType, digits: int = 3) -> None: """ Print a summary of estimation results for each estimated model. @@ -476,8 +474,8 @@ def summary( Parameters ---------- - models : list[Union[Feols, Fepois, Feiv]] or FixestMulti. - The models to be summarized. + models : A supported model object (Feols, Fepois, Feiv, FixestMulti) or a list of + Feols, Fepois & Feiv models. digits : int, optional The number of decimal places to round the summary statistics to. Default is 3. @@ -550,8 +548,8 @@ def summary( def _post_processing_input_checks( - models: Union[list[Union[Feols, Fepois, Feiv]], FixestMulti], -) -> list[Union[Feols, Fepois]]: + models: ModelInputType, +) -> list[Union[Feols, Fepois, Feiv]]: """ Perform input checks for post-processing models. @@ -572,34 +570,23 @@ def _post_processing_input_checks( TypeError: If the models argument is not of the expected type. """ - # check if models instance of Feols or Fepois - if isinstance(models, (Feols, Fepois)): - models = [models] - - else: - if isinstance(models, (list, type({}.values()))): - for model in models: - if not isinstance(model, (Feols, Fepois)): - raise TypeError( - f""" - Each element of the passed list needs to be of type Feols - or Fepois, but {type(model)} was passed. If you want to - summarize a FixestMulti object, please use FixestMulti.to_list() - to convert it to a list of Feols or Fepois instances. - """ - ) - + models_list: list[Union[Feols, Fepois, Feiv]] = [] + + if isinstance(models, (Feols, Fepois, Feiv)): + models_list = [models] + elif isinstance(models, FixestMulti): + models_list = models.to_list() + elif isinstance(models, (list, ValuesView)): + if all(isinstance(m, (Feols, Fepois, Feiv)) for m in models): + models_list = models else: raise TypeError( - """ - The models argument must be either a list of Feols or Fepois instances, or - simply a single Feols or Fepois instance. The models argument does not accept instances - of type FixestMulti - please use models.to_list() to convert the FixestMulti - instance to a list of Feols or Fepois instances. - """ + "All elements in the models list must be instances of Feols, Feiv, or Fepois." ) + else: + raise TypeError("Invalid type for models argument.") - return models + return models_list def _tabulate_etable_md(df, n_coef, n_fixef, n_models, n_model_stats): diff --git a/pyfixest/report/visualize.py b/pyfixest/report/visualize.py index 7fab927f..faf93fc1 100644 --- a/pyfixest/report/visualize.py +++ b/pyfixest/report/visualize.py @@ -23,10 +23,16 @@ from pyfixest.estimation.feiv_ import Feiv from pyfixest.estimation.feols_ import Feols from pyfixest.estimation.fepois_ import Fepois +from pyfixest.estimation.FixestMulti_ import FixestMulti from pyfixest.report.summarize import _post_processing_input_checks from pyfixest.report.utils import _relabel_expvar from pyfixest.utils.dev_utils import _select_order_coefs +ModelInputType = Union[ + FixestMulti, Feols, Fepois, Feiv, list[Union[Feols, Fepois, Feiv]] +] + + LetsPlot.setup_html() @@ -60,7 +66,7 @@ def set_figsize( def iplot( - models, + models: ModelInputType, alpha: float = 0.05, figsize: Optional[tuple[int, int]] = None, yintercept: Union[int, str, None] = None, @@ -83,9 +89,8 @@ def iplot( Parameters ---------- - models : list or object - A list of fitted models of type `Feols` or - `Fepois`, or just a single model. + models : A supported model object (Feols, Fepois, Feiv, FixestMulti) or a list of + Feols, Fepois & Feiv models. figsize : tuple or None, optional The size of the figure. If None, the default size is used. alpha : float @@ -157,8 +162,8 @@ def iplot( "The 'joint' parameter is only available for a single model, i.e. objects of type FixestMulti are not supported." ) - df_all = [] - all_icovars = [] + df_all: list[pd.DataFrame] = [] + all_icovars: list[str] = [] if keep is None: keep = [] @@ -205,7 +210,7 @@ def iplot( def coefplot( - models: list, + models: ModelInputType, alpha: float = 0.05, figsize: Optional[tuple[int, int]] = None, yintercept: float = 0, @@ -227,8 +232,8 @@ def coefplot( Parameters ---------- - models : list or object - A list of fitted models of type `Feols` or `Fepois`, or just a single model. + models : A supported model object (Feols, Fepois, Feiv, FixestMulti) or a list of + Feols, Fepois & Feiv models. figsize : tuple or None, optional The size of the figure. If None, the default size is used. alpha : float diff --git a/tests/test_api.py b/tests/test_api.py index af02fbe6..95793be2 100644 --- a/tests/test_api.py +++ b/tests/test_api.py @@ -13,11 +13,17 @@ def test_api(): fit2 = pf.estimation.fepois( "Y ~ X1 + X2 + f2 | f1", data=df2, vcov={"CRV1": "f1+f2"} ) + fit_multi = pf.feols("Y + Y2 ~ X1", data=df2) + pf.summary(fit1) pf.report.summary(fit2) pf.etable([fit1, fit2]) pf.coefplot([fit1, fit2]) + pf.summary(fit_multi) + pf.etable(fit_multi) + pf.coefplot(fit_multi) + def test_feols_args(): """ diff --git a/tests/test_multcomp.py b/tests/test_multcomp.py index 6a3e6daa..892588a2 100644 --- a/tests/test_multcomp.py +++ b/tests/test_multcomp.py @@ -5,6 +5,7 @@ from rpy2.robjects import pandas2ri from rpy2.robjects.packages import importr +import pyfixest as pf from pyfixest.estimation.estimation import feols from pyfixest.estimation.multcomp import _get_rwolf_pval, bonferroni, rwolf from pyfixest.utils.set_rpy2_path import update_r_paths @@ -195,3 +196,20 @@ def test_sampling_scheme(seed, reps): assert ( np.abs(percent_diff) < 1.0 ), f"Percentage difference is too large: {percent_diff}%" + + +@pytest.mark.extended +def test_multi_vs_list(seeds, reps): + "Test that lists of models and FixestMulti input produce identical results." + seed = 1232 + reps = 100 + data = pf.get_data(N=100) + + fit_all = pf.feols("Y + Y2 ~ X1 + X2", data=data) + fit1 = pf.feols("Y ~ X1 + X2", data=data) + fit2 = pf.feols("Y2 ~ X1 + X2", data=data) + + assert bonferroni(fit_all, "X1").equals(bonferroni([fit1, fit2], "X1")) + assert rwolf(fit_all, "X1", seed=seed, reps=reps).equals( + rwolf([fit1, fit2], "X1", seed=seed, reps=reps) + )