Merge pull request #620 from bashtage/update-scipy

MAINT: Updates for scipy changes

Author: bashtage

azure-pipelines.yml

@@ -9,6 +9,7 @@ variables:
   OMP_NUM_THREADS: 1
   VML_NUM_THREADS: 1
   OPENBLAS_NUM_THREADS: 1
+  JUPYTER_PLATFORM_DIRS: 1
   PYTHONHASHSEED: 12345678 # Ensure tests are correctly gathered by xdist
   TEST_INSTALL: false
   MPLBACKEND: agg

doc/source/changes/5.0.rst

@@ -38,4 +38,4 @@ Version 5.0
 
 * Switched variable ordering by default.  Importing ``linearmodels.__future__.ordering``
   is a no-op, and has no effect.
-* Removed dependence on property-cached in favor of :meth:`functools.cached_property`.
+* Removed dependence on property-cached in favor of :class:`functools.cached_property`.

doc/source/conf.py

@@ -276,15 +276,13 @@
 
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
-    "statsmodels": ("https://www.statsmodels.org/dev/", None),
-    "matplotlib": ("https://matplotlib.org/stable/", None),
-    "scipy": ("https://docs.scipy.org/doc/scipy/", None),
-    "python": ("https://docs.python.org/3/", None),
-    "numpy": ("https://numpy.org/doc/stable/", None),
-    "np": ("https://numpy.org/doc/stable/", None),
-    "pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
-    "pd": ("https://pandas.pydata.org/pandas-docs/stable/", None),
-    "xarray": ("https://docs.xarray.dev/en/stable/", None),
+    "statsmodels": ("https://www.statsmodels.org/dev", None),
+    "matplotlib": ("https://matplotlib.org/stable", None),
+    "scipy": ("https://docs.scipy.org/doc/scipy", None),
+    "python": ("https://docs.python.org/3", None),
+    "numpy": ("https://numpy.org/doc/stable", None),
+    "pandas": ("https://pandas.pydata.org/pandas-docs/stable", None),
+    "xarray": ("https://docs.xarray.dev/en/stable", None),
 }
 
 extlinks = {"issue": ("https://github.com/bashtage/linearmodels/issues/%s", "GH%s")}

linearmodels/asset_pricing/model.py

@@ -286,7 +286,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debias the covariance estimator using
             a degree of freedom adjustment
-        **cov_config : dict
+        cov_config : dict
             Additional covariance-specific options.  See Notes.
 
         Returns
@@ -611,7 +611,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debias the covariance estimator using
             a degree of freedom adjustment
-        **cov_config
+        cov_config
             Additional covariance-specific options.  See Notes.
 
         Returns
@@ -942,7 +942,7 @@ def fit(
             optimizing the objective function. If not provided, defers to
             scipy to choose an appropriate optimizer. All minimize inputs
             except ``fun``, ``x0``, and ``args`` can be overridden.
-        **cov_config
+        cov_config
             Additional covariance-specific options.  See Notes.
 
         Returns

linearmodels/iv/absorbing.py

@@ -147,7 +147,7 @@ def lsmr_annihilate(
             resid = _VARIABLE_CACHE[regressor_hash][variable_digest]
         else:
             beta = lsmr(x, _y, **default_opts)[0]
-            resid = y[:, i : i + 1] - (x.dot(sp.csc_matrix(beta[:, None]))).toarray()
+            resid = y[:, i : i + 1] - x.dot(sp.csc_matrix(beta[:, None])).toarray()
             _VARIABLE_CACHE[regressor_hash][variable_digest] = resid
         resids.append(resid)
     return column_stack(resids)
@@ -1025,7 +1025,7 @@ def fit(
 
                Use absorb_options to pass options
 
-        **cov_config
+        cov_config
             Additional parameters to pass to covariance estimator. The list
             of optional parameters differ according to ``cov_type``. See
             the documentation of the alternative covariance estimators for

linearmodels/iv/model.py

@@ -638,7 +638,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debiased the covariance estimator using
             a degree of freedom adjustment.
-        **cov_config
+        cov_config
             Additional parameters to pass to covariance estimator. The list
             of optional parameters differ according to ``cov_type``. See
             the documentation of the alternative covariance estimators for
@@ -1250,7 +1250,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debiased the covariance estimator using
             a degree of freedom adjustment.
-        **cov_config
+        cov_config
             Additional parameters to pass to covariance estimator. Supported
             parameters depend on specific covariance structure assumed. See
             :class:`linearmodels.iv.gmm.IVGMMCovariance` for details
@@ -1588,7 +1588,7 @@ def fit(
             optimizing the objective function. If not provided, defers to
             scipy to choose an appropriate optimizer. All minimize inputs
             except ``fun``, ``x0``, and ``args`` can be overridden.
-        **cov_config
+        cov_config
             Additional parameters to pass to covariance estimator. Supported
             parameters depend on specific covariance structure assumed. See
             :class:`linearmodels.iv.gmm.IVGMMCovariance` for details

linearmodels/panel/model.py

@@ -1000,7 +1000,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debiased the covariance estimator using
             a degree of freedom adjustment.
-        **cov_config
+        cov_config
             Additional covariance-specific options.  See Notes.
 
         Returns
@@ -1865,7 +1865,7 @@ def fit(
             Flag indicating that the covariance estimator should be adjusted
             to account for the estimation of effects in the model. Only used
             if ``auto_df=False``.
-        **cov_config
+        cov_config
             Additional covariance-specific options.  See Notes.
 
         Returns
@@ -2225,7 +2225,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debiased the covariance estimator using
             a degree of freedom adjustment.
-        **cov_config
+        cov_config
             Additional covariance-specific options.  See Notes.
 
         Returns
@@ -2527,7 +2527,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debiased the covariance estimator using
             a degree of freedom adjustment.
-        **cov_config
+        cov_config
             Additional covariance-specific options.  See Notes.
 
         Returns
@@ -2842,7 +2842,7 @@ def fit(
         debiased : bool
             Flag indicating whether to debiased the covariance estimator using
             a degree of freedom adjustment.
-        **cov_config
+        cov_config
             Additional covariance-specific options.  See Notes.
 
         Returns

linearmodels/system/model.py

@@ -1291,7 +1291,7 @@ def fit(
             * "clustered" - Allows for 1 and 2-way clustering of errors
               (Rogers).
 
-        **cov_config
+        cov_config
             Additional parameters to pass to covariance estimator. All
             estimators support debiased which employs a small-sample adjustment
 
@@ -1955,7 +1955,7 @@ def fit(
             * "robust", "heteroskedastic" - Heteroskedasticity robust
               covariance estimator
 
-        **cov_config
+        cov_config
             Additional parameters to pass to covariance estimator. All
             estimators support debiased which employs a small-sample adjustment
 

requirements-dev.txt

@@ -5,6 +5,8 @@ pytest>=7.3.0,<8
 isort>=5.12
 ipython
 matplotlib
+ruff
+flake8
 jupyter
 nbconvert
 nbformat