Merge pull request #69 from billtubbs/master

Change to SINDy init defaults for optimizer, feature_library, and differentiation_method
dynamicslab · Apr 26, 2020 · c8e7324 · c8e7324
2 parents 5c45a36 + f9ac15b
commit c8e7324
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Showing 2 changed files with 15 additions and 15 deletions.
diff --git a/pysindy/optimizers/stlsq.py b/pysindy/optimizers/stlsq.py
@@ -9,8 +9,7 @@
 
 
 class STLSQ(BaseOptimizer):
-    """
-    Sequentially thresholded least squares algorithm.
+    """Sequentially thresholded least squares algorithm.
 
     Attempts to minimize the objective function
     :math:`\\|y - Xw\\|^2_2 + alpha \\times \\|w\\|^2_2`
@@ -128,8 +127,7 @@ def _no_change(self):
         return all(bool(i) == bool(j) for i, j in zip(this_coef, last_coef))
 
     def _reduce(self, x, y):
-        """
-        Iterates the thresholding. Assumes an initial guess is saved in
+        """Iterates the thresholding. Assumes an initial guess is saved in
         self.coef_ and self.ind_
         """
         ind = self.ind_
@@ -140,10 +138,8 @@ def _reduce(self, x, y):
         for _ in range(self.max_iter):
             if np.count_nonzero(ind) == 0:
                 warnings.warn(
-                    """Sparsity parameter is too big ({}) and eliminated all
-                    coefficients""".format(
-                        self.threshold
-                    )
+                    "Sparsity parameter is too big ({}) and eliminated all "
+                    "coefficients".format(self.threshold)
                 )
                 coef = np.zeros((n_targets, n_features))
                 break
@@ -152,10 +148,8 @@ def _reduce(self, x, y):
             for i in range(n_targets):
                 if np.count_nonzero(ind[i]) == 0:
                     warnings.warn(
-                        """Sparsity parameter is too big ({}) and eliminated all
-                        coefficients""".format(
-                            self.threshold
-                        )
+                        "Sparsity parameter is too big ({}) and eliminated all "
+                        "coefficients".format(self.threshold)
                     )
                     continue
                 coef_i = self._regress(x[:, ind[i]], y[:, i])

diff --git a/pysindy/pysindy.py b/pysindy/pysindy.py
@@ -93,15 +93,21 @@ class SINDy(BaseEstimator):
 
     def __init__(
         self,
-        optimizer=STLSQ(),
-        feature_library=PolynomialFeatures(),
-        differentiation_method=FiniteDifference(),
+        optimizer=None,
+        feature_library=None,
+        differentiation_method=None,
         feature_names=None,
         discrete_time=False,
         n_jobs=1,
     ):
+        if optimizer is None:
+            optimizer = STLSQ()
         self.optimizer = optimizer
+        if feature_library is None:
+            feature_library = PolynomialFeatures()
         self.feature_library = feature_library
+        if differentiation_method is None:
+            differentiation_method = FiniteDifference()
         self.differentiation_method = differentiation_method
         self.feature_names = feature_names
         self.discrete_time = discrete_time