Functions for correlation matrix, copula indicator and plotting #103
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
TolisChal
approved these changes
Aug 12, 2024
TolisChal
reviewed
Aug 12, 2024
dingo/utils.py
Outdated
Comment on lines
317
to
319
| print(positive, "out of", i+1, "copulas were positive correlated based on copula indicator") | ||
| print(negative, "out of", i+1, "copulas were negative correlated based on copula indicator") | ||
|
|
There was a problem hiding this comment.
The prints should be requested by the user I think. These numbers could be part of the output as with a label for each copula: "positive" or "negative"
There was a problem hiding this comment.
I created a dictionary of this format that is returned
{'ACONTb_ACONTa': {'pearson': 0.9999999999999996, 'indicator': 700000000.9999999, 'classification': 'positive'},
'ACt2r_ACKr': {'pearson': 1.0, 'indicator': 700000000.9999999, 'classification': 'positive'}}
TolisChal
reviewed
Aug 14, 2024
dingo/utils.py
Outdated
| 'indicator': indicator, | ||
| 'classification': "no correlation"} | ||
|
|
||
| print("Completed process of",i+1,"from",corr_indices.shape[0],"copulas") |
There was a problem hiding this comment.
All the prints should ideally requested by the user and be off by default.
I'd use a flag verbose: bool as an input variable with False as default value. Then, print any message only if verbose is true.
TolisChal
reviewed
Aug 14, 2024
dingo/preprocess.py
Outdated
| self._model.reactions.get_by_id(reaction).bounds = self._reaction_bounds_dict[reaction] | ||
|
|
||
|
|
||
| print(len(self._removed_reactions), "of the", len(self._initial_reactions), \ |
There was a problem hiding this comment.
Plz, see my comment below for the printed messages.
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.
Aim of this PR is:
PreProcessclass.The
correlated_reactionsfunction that calculates a pearson correlation matrix from reactions steady states is appended to the scriptdingo/utils.pyCorrelations that do not make the pearson cutoff are replaced with 0. For pairwise reactions with a greater pearson coefficient than the cutoff, a copula indicator is computed to filter false-positive correlations. Parameters of this function can adjust the width of the copula's diagonal for the calculation of the indicator and return only the lower triangle of the symmetric matrix. Cutoffs for pearson and indicator filtering can be adjusted from the user too.The
plot_corr_matrixfunction that creates a heatmap plot of a correlation matrix is appended to the scriptdingo/illustrations.pyParameters of this function can specify the format of the saved image plot and place as labels only the remained reactions for reduced models.The
reducefunction of thePreProcessclass for theextendparameter set toTruehas also changed to identify additional reactions for removal in bigger models. It uses the newcorrelated_reactionsfunction to calculate a correlation matrix and order reactions based on their sum of absolute correlations with other reactions. Reactions with smaller values of overall correlation are removed first. The removal stops in the first reaction that alters the value of the objective function.A
correlation.pyunittest is also created in thetestsdirectory and thepreprocess.pyunittest is updated too.