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Add keep/drop to coefplot and refactor code to improve maintainability #341

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merged 8 commits into from
Mar 4, 2024
Merged

Add keep/drop to coefplot and refactor code to improve maintainability #341

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17e86c0
dev: add keep/drop/exact_match to coefplot/iplot
Wenzhi-Ding Mar 4, 2024
df6c2e2
dev: remove backward compatibility.
Wenzhi-Ding Mar 4, 2024
7f058fb
dev: remove backward compatibility.
Wenzhi-Ding Mar 4, 2024
6240db3
fix test bug.
Wenzhi-Ding Mar 4, 2024
6a21645
fix class referenced functions
Wenzhi-Ding Mar 4, 2024
cb9263f
lint
Wenzhi-Ding Mar 4, 2024
a50cd8c
dev: make functions and docstrings easier maintenance.
Wenzhi-Ding Mar 4, 2024
823ac89
fix: ignore ruff D205 linting rule
Wenzhi-Ding Mar 4, 2024
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135 changes: 17 additions & 118 deletions pyfixest/estimation/FixestMulti_.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,6 @@
import functools
import warnings
from importlib import import_module
from typing import Optional, Union

import numpy as np
Expand All @@ -11,7 +13,6 @@
from pyfixest.estimation.fepois_ import Fepois, _check_for_separation
from pyfixest.estimation.FormulaParser import FixestFormulaParser
from pyfixest.estimation.model_matrix_fixest_ import model_matrix_fixest
from pyfixest.report.visualize import coefplot, iplot
from pyfixest.utils.dev_utils import _polars_to_pandas


Expand Down Expand Up @@ -42,6 +43,21 @@ def __init__(self, data: pd.DataFrame) -> None:
self._data.reset_index(drop=True, inplace=True)
self.all_fitted_models = {}

# set functions inherited from other modules
_module = import_module("pyfixest.report")
_tmp = getattr(_module, "coefplot")
self.coefplot = functools.partial(_tmp, models=self.all_fitted_models.values())
self.coefplot.__doc__ = _tmp.__doc__
_tmp = getattr(_module, "iplot")
self.iplot = functools.partial(_tmp, models=self.all_fitted_models.values())
self.iplot.__doc__ = _tmp.__doc__
_tmp = getattr(_module, "summary")
self.summary = functools.partial(_tmp, models=self.all_fitted_models.values())
self.summary.__doc__ = _tmp.__doc__
_tmp = getattr(_module, "etable")
self.etable = functools.partial(_tmp, models=self.all_fitted_models.values())
self.etable.__doc__ = _tmp.__doc__

def _prepare_estimation(
self,
estimation: str,
Expand Down Expand Up @@ -479,14 +495,6 @@ def tidy(self) -> pd.DataFrame:

return res

def summary(self, digits: int = 3) -> None: # noqa: D102
for x in list(self.all_fitted_models.keys()):
fxst = self.all_fitted_models[x]
fxst.summary(digits=digits)

def etable(self, digits: int = 3) -> pd.DataFrame: # noqa: D102
return self.tidy().T.round(digits)

def coef(self) -> pd.Series:
"""
Obtain the coefficients of the fitted models.
Expand Down Expand Up @@ -549,115 +557,6 @@ def confint(self) -> pd.Series:
"""
return self.tidy()[["2.5%", "97.5%"]]

def iplot(
self,
alpha: float = 0.05,
figsize: tuple = (500, 300),
yintercept: Union[int, str, None] = None,
xintercept: Union[int, str, None] = None,
rotate_xticks: int = 0,
title: Optional[str] = None,
coord_flip: Optional[bool] = True,
):
"""
Plot model coefficients.

Plot model coefficients with confidence intervals for variable interactions
specified via the `i()` syntax.

Parameters
----------
alpha : float, optional
The significance level for the confidence intervals. Default is 0.05.
figsize : tuple, optional
The size of the figure. Default is (10, 10).
yintercept : Union[int, str, None], optional
The value at which to draw a horizontal line.
xintercept : Union[int, str, None], optional
The value at which to draw a vertical line.
rotate_xticks : int, optional
The rotation angle for x-axis tick labels. Default is 0.
title : str, optional
The title of the plot. Default is None.
coord_flip : bool, optional
Whether to flip the coordinates of the plot. Default is True.

Returns
-------
lets-plot figure
A lets-plot figure of coefficients (and respective CIs) interacted
via the `i()` syntax.
"""
models = self.all_fitted_models
# get a list, not a dict, as iplot only works with lists
models = [models[x] for x in list(self.all_fitted_models.keys())]

plot = iplot(
models=models,
alpha=alpha,
figsize=figsize,
yintercept=yintercept,
xintercept=xintercept,
rotate_xticks=rotate_xticks,
title=title,
coord_flip=coord_flip,
)

return plot

def coefplot(
self,
alpha: float = 0.05,
figsize: tuple = (500, 300),
yintercept: int = 0,
rotate_xticks: int = 0,
title: Optional[str] = None,
coord_flip: Optional[bool] = True,
):
"""
Plot estimation results.

The plot() method is only defined for single regressions.

Parameters
----------
alpha : float
The significance level for the confidence intervals. Default is 0.05.
figsize : tuple
The size of the figure. Default is (5, 2).
yintercept : float
The value of the y-intercept. Default is 0.
figtitle:str, optional
The title of the figure. Default is None.
figtext : str, optional
The text at the bottom of the figure. Default is None.
title : str, optional
The title of the plot. Default is None.
coord_flip : bool, optional
Whether to flip the coordinates of the plot. Default is True.

Returns
-------
lets-plot figure
A lets-plot figure of regression coefficients.
"""
# get a list, not a dict, as iplot only works with lists
models = self.all_fitted_models
models = [models[x] for x in list(self.all_fitted_models.keys())]

plot = coefplot(
models=models,
figsize=figsize,
alpha=alpha,
yintercept=yintercept,
xintercept=None,
rotate_xticks=rotate_xticks,
title=title,
coord_flip=coord_flip,
)

return plot

def wildboottest(
self,
B: int,
Expand Down
141 changes: 13 additions & 128 deletions pyfixest/estimation/feols_.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import functools
import re
import warnings
from importlib import import_module
Expand Down Expand Up @@ -262,6 +263,18 @@ def __init__(
self._adj_r2 = None
self._adj_r2_within = None

# set functions inherited from other modules
_module = import_module("pyfixest.report")
_tmp = getattr(_module, "coefplot")
self.coefplot = functools.partial(_tmp, models=[self])
self.coefplot.__doc__ = _tmp.__doc__
_tmp = getattr(_module, "iplot")
self.iplot = functools.partial(_tmp, models=[self])
self.iplot.__doc__ = _tmp.__doc__
_tmp = getattr(_module, "summary")
self.summary = functools.partial(_tmp, models=[self])
self.summary.__doc__ = _tmp.__doc__

def get_fit(self) -> None:
"""
Fit an OLS model.
Expand Down Expand Up @@ -728,115 +741,6 @@ def wald_test(self, R=None, q=None, distribution="F") -> None:

return res

def coefplot(
self,
alpha: float = 0.05,
figsize: tuple[int, int] = (500, 300),
yintercept: Optional[float] = 0,
xintercept: Optional[float] = None,
rotate_xticks: int = 0,
coefficients: Optional[list[str]] = None,
title: Optional[str] = None,
coord_flip: Optional[bool] = True,
):
"""
Create a coefficient plot to visualize model coefficients.

Parameters
----------
alpha : float, optional
Significance level for highlighting significant coefficients.
Defaults to None.
figsize : tuple[int, int], optional
Size of the plot (width, height) in inches. Defaults to None.
yintercept : float, optional
Value to set as the y-axis intercept (vertical line). Defaults to None.
xintercept : float, optional
Value to set as the x-axis intercept (horizontal line). Defaults to None.
rotate_xticks : int, optional
Rotation angle for x-axis tick labels. Defaults to None.
coefficients : list[str], optional
List of coefficients to include in the plot.
If None, all coefficients are included.
title : str, optional
Title of the plot. Defaults to None.
coord_flip : bool, optional
Whether to flip the coordinates of the plot. Defaults to None.

Returns
-------
lets-plot figure
A lets-plot figure with coefficient estimates and confidence intervals.
"""
# lazy loading to avoid circular import
visualize_module = import_module("pyfixest.report")
_coefplot = getattr(visualize_module, "coefplot")

plot = _coefplot(
models=[self],
alpha=alpha,
figsize=figsize,
yintercept=yintercept,
xintercept=xintercept,
rotate_xticks=rotate_xticks,
coefficients=coefficients,
title=title,
coord_flip=coord_flip,
)

return plot

def iplot(
self,
alpha: float = 0.05,
figsize: tuple[int, int] = (500, 300),
yintercept: Optional[float] = None,
xintercept: Optional[float] = None,
rotate_xticks: int = 0,
title: Optional[str] = None,
coord_flip: Optional[bool] = True,
):
"""
Create coefficient plots for variables interacted via `i()` syntax.

Parameters
----------
alpha : float, optional
Significance level for visualization options. Defaults to 0.05.
figsize : tuple[int, int], optional
Size of the plot (width, height) in inches. Defaults to (500, 300).
yintercept : float, optional
Value to set as the y-axis intercept (vertical line). Defaults to None.
xintercept : float, optional
Value to set as the x-axis intercept (horizontal line). Defaults to None.
rotate_xticks : int, optional
Rotation angle for x-axis tick labels. Defaults to 0.
title : str, optional
Title of the plot. Defaults to None.
coord_flip : bool, optional
Whether to flip the coordinates of the plot. Defaults to True.

Returns
-------
lets-plot figure
A lets-plot figure with coefficient estimates and confidence intervals.
"""
visualize_module = import_module("pyfixest.report")
_iplot = getattr(visualize_module, "iplot")

plot = _iplot(
models=[self],
alpha=alpha,
figsize=figsize,
yintercept=yintercept,
xintercept=xintercept,
rotate_xticks=rotate_xticks,
title=title,
coord_flip=coord_flip,
)

return plot

def wildboottest(
self,
B: int,
Expand Down Expand Up @@ -1662,25 +1566,6 @@ def resid(self) -> np.ndarray:
"""
return self._u_hat

def summary(self, digits=3) -> None:
"""
Summary of estimated model.

Parameters
----------
digits : int, optional
The number of digits to be displayed. Defaults to 3.

Returns
-------
None
"""
# lazy loading to avoid circular import
summarize_module = import_module("pyfixest.report")
_summary = getattr(summarize_module, "summary")

return _summary(models=self, digits=digits)


def _check_vcov_input(vcov, data):
"""
Expand Down
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