Multirom #249
Open
Multirom #249
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
mtezzele
reviewed
Apr 16, 2024
Comment on lines
+184
to
+209
| # ddd | ||
|
|
||
|
|
||
| # if self.n_database == 1 and self.n_reduction == 1: | ||
| # self.train_full_database = self.database | ||
| # self.reduction.fit(self.database.snapshots_matrix.T) | ||
|
|
||
| # elif self.n_database == 1 and self.n_reduction > 1: | ||
| # self.train_full_database = self.database | ||
| # for reduction in self.reduction: | ||
| # reduction.fit(self.database.snapshots_matrix.T) | ||
|
|
||
| # elif self.n_database > 1 and self.n_reduction == 1: | ||
| # self.train_full_database = self.database | ||
| # self.reduction = [ | ||
| # (k, copy.deepcopy(self.reduction)) | ||
| # for k in self.train_full_database | ||
| # ] | ||
| # print(self.reduction) | ||
| # for reduction, database in zip(self.reduction, self.train_full_database): | ||
| # self.reduction[reduction].fit(self.train_full_database[database].snapshots_matrix.T) | ||
|
|
||
| # elif self.n_database > 1 and self.n_reduction > 1: | ||
| # raise NotImplementedError | ||
| # else: | ||
| # raise RuntimeError |
Comment on lines
+264
to
+271
| # print(self.predict_reduced_database) | ||
| # print(self.predict_reduced_database._pairs) | ||
| # print(self.predict_reduced_database._pairs[0]) | ||
| # print(self.predict_reduced_database._pairs[0][1].values) | ||
|
|
||
| print(self.predict_reduced_database.parameters_matrix) | ||
| print(self.approximation.predict( | ||
| self.predict_reduced_database.parameters_matrix)) |
Comment on lines
+279
to
+282
| # print(self.predict_reduced_database) | ||
| # print(self.predict_reduced_database._pairs) | ||
| # print(self.predict_reduced_database._pairs[0]) | ||
| # print(self.predict_reduced_database._pairs[0][1].values) |
Comment on lines
+289
to
+291
| # print(self.predict_reduced_database.snapshots_matrix) | ||
| # print(self.reduction.inverse_transform( | ||
| # self.predict_reduced_database.snapshots_matrix.T).T) |
Comment on lines
+628
to
+653
| # ddd | ||
|
|
||
|
|
||
| # if self.n_database == 1 and self.n_reduction == 1: | ||
| # self.train_full_database = self.database | ||
| # self.reduction.fit(self.database.snapshots_matrix.T) | ||
|
|
||
| # elif self.n_database == 1 and self.n_reduction > 1: | ||
| # self.train_full_database = self.database | ||
| # for reduction in self.reduction: | ||
| # reduction.fit(self.database.snapshots_matrix.T) | ||
|
|
||
| # elif self.n_database > 1 and self.n_reduction == 1: | ||
| # self.train_full_database = self.database | ||
| # self.reduction = [ | ||
| # (k, copy.deepcopy(self.reduction)) | ||
| # for k in self.train_full_database | ||
| # ] | ||
| # print(self.reduction) | ||
| # for reduction, database in zip(self.reduction, self.train_full_database): | ||
| # self.reduction[reduction].fit(self.train_full_database[database].snapshots_matrix.T) | ||
|
|
||
| # elif self.n_database > 1 and self.n_reduction > 1: | ||
| # raise NotImplementedError | ||
| # else: | ||
| # raise RuntimeError |
Comment on lines
+662
to
+704
| # print(self.database) | ||
| # print(self.reduction) | ||
| # print(self.approximation) | ||
|
|
||
| # from itertools import product | ||
| # element_keys = product( | ||
| # self.database.keys(), | ||
| # self.reduction.keys(), | ||
| # self.approximation.keys() | ||
| # ) | ||
| # self.roms = { | ||
|
|
||
| # tuple(key): { | ||
| # 'database': copy.deepcopy(self.database[key[0]]), | ||
| # 'reduction': copy.deepcopy(self.reduction[key[1]]), | ||
| # 'approximation': copy.deepcopy(self.approximation[key[2]]) | ||
| # } | ||
| # for key in element_keys | ||
| # } | ||
| # print(self.roms) | ||
| # self._full_database = copy.deepcopy(self.database) | ||
|
|
||
| # # FULL-ORDER PREPROCESSING here | ||
| # for plugin in self.plugins: | ||
| # plugin.fom_preprocessing(self) | ||
|
|
||
| # self.fit_reduction() | ||
| # # self.reduction.fit(self._full_database.snapshots_matrix.T) | ||
| # # print(self.reduction.singular_values) | ||
| # # print(self._full_database.snapshots_matrix) | ||
| # reduced_snapshots = self.reduction.transform( | ||
| # self._full_database.snapshots_matrix.T).T | ||
|
|
||
| # self._reduced_database = Database( | ||
| # self._full_database.parameters_matrix, reduced_snapshots) | ||
|
|
||
| # # REDUCED-ORDER PREPROCESSING here | ||
| # for plugin in self.plugins: | ||
| # plugin.rom_preprocessing(self) | ||
|
|
||
| # self.approximation.fit( | ||
| # self._reduced_database.parameters_matrix, | ||
| # self._reduced_database.snapshots_matrix) |
Comment on lines
+20
to
+22
| # def test_constructor_error(self): | ||
| # with self.assertRaises(TypeError): | ||
| # Database(np.eye(5)) |
| @@ -53,8 +53,9 @@ def test_predict_ref(): | |||
| ]) | |||
| rom.fit() | |||
| pred = rom.predict(db._pairs[0][0].values) | |||
| print(pred) | |||
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.