[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

pyfixest/estimation/estimation.py

@@ -1,5 +1,5 @@
 from collections.abc import Mapping
-from typing import Any, Optional, Union, Sequence
+from typing import Any, Optional, Union
 
 import pandas as pd
 
@@ -503,7 +503,7 @@ def fepois(
     fml: str,
     data: DataFrameType,  # type: ignore
     vcov: Optional[Union[VcovTypeOptions, dict[str, str]]] = None,
-    offset:  Union[None, str] = None,
+    offset: Union[None, str] = None,
     ssc: Optional[dict[str, Union[str, bool]]] = None,
     fixef_rm: FixedRmOptions = "none",
     fixef_tol: float = 1e-08,

pyfixest/estimation/feols_.py

@@ -379,7 +379,6 @@ def prepare_model_matrix(self):
         self._offset = self._set_offset()
         self._N, self._N_rows = self._set_nobs()
 
-
     def _set_nobs(self) -> tuple[int, int]:
         """
         Fetch the number of observations used in fitting the regression model.
@@ -417,7 +416,7 @@ def _set_weights(self) -> np.ndarray:
             _weights = np.ones(N)
 
         return _weights.reshape((N, 1))
-    
+
     def _set_offset(self) -> np.ndarray:
         """
         Return the offset used in the regression model.
@@ -429,7 +428,6 @@ def _set_offset(self) -> np.ndarray:
             If no offset is used, returns an array of zeros
             with the same length as the dependent variable array.
         """
-
         N = len(self._Y)
 
         if self._offset_df is not None:

pyfixest/estimation/fepois_.py

@@ -149,7 +149,7 @@ def prepare_model_matrix(self):
             raise ValueError(
                 "The dependent variable must be a weakly positive integer."
             )
-        
+
         # check for separation
         na_separation: list[int] = []
         if (
@@ -170,7 +170,9 @@ def prepare_model_matrix(self):
             self._Y.drop(na_separation, axis=0, inplace=True)
             self._X.drop(na_separation, axis=0, inplace=True)
             self._fe.drop(na_separation, axis=0, inplace=True)
-            self._offset = np.delete(self._offset,na_separation,axis=0) # _offset is a numpy array so we use delete instead of drop
+            self._offset = np.delete(
+                self._offset, na_separation, axis=0
+            )  # _offset is a numpy array so we use delete instead of drop
             self._data.drop(na_separation, axis=0, inplace=True)
             self._N = self._Y.shape[0]
 
@@ -699,4 +701,3 @@ def _fepois_input_checks(drop_singletons: bool, tol: float, maxiter: int):
         raise TypeError("maxiter must be integer.")
     if maxiter <= 0:
         raise AssertionError("maxiter must be greater than 0.")
-        

pyfixest/estimation/model_matrix_fixest_.py

@@ -147,7 +147,7 @@ def model_matrix_fixest(
     if offset is not None:
         offset_df = mm["offset"]
 
-    for df in [Y, X, Z, endogvar, weights_df,offset_df]:
+    for df in [Y, X, Z, endogvar, weights_df, offset_df]:
         if df is not None:
             cols_to_convert = df.select_dtypes(exclude=["int64", "float64"]).columns
             if cols_to_convert.size > 0: