Closed atuldeshpande closed 4 years ago
The existing test cases are failing in this build
Comparing SINGE_Gene_Influence.txt
files are identical
Comparing SINGE_Ranked_Edge_List.txt
0 rows removed (0.0%)
0 rows added (0.0%)
1 rows changed (0.0%)
Comparing sparse adjacency matrices
Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_1.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_1.mat have different values
Maximum absolute difference: 6.4849853515625e-05
Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_2.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_2.mat have different values
Maximum absolute difference: 0.0001385211944580078
Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_1.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_1.mat have different values
Maximum absolute difference: 7.724761962890625e-05
Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_2.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_2.mat have different values
Maximum absolute difference: 0.011023879051208496
We expected the non-branching input data would give identical outputs, right?
No, there would be some difference within a threshold because we calculate one of the variables after the single precision conversion as opposed to before. On Aug 12, 2020, 11:51 AM -0400, Anthony Gitter notifications@github.com, wrote:
The existing test cases are failing in this build Comparing SINGE_Gene_Influence.txt files are identical Comparing SINGE_Ranked_Edge_List.txt 0 rows removed (0.0%) 0 rows added (0.0%) 1 rows changed (0.0%) Comparing sparse adjacency matrices Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_1.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_1.mat have different values Maximum absolute difference: 6.4849853515625e-05 Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_2.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_541_lambda_0p01_replicate_2.mat have different values Maximum absolute difference: 0.0001385211944580078 Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_1.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_1.mat have different values Maximum absolute difference: 7.724761962890625e-05 Spare matrices in standalone_output/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_2.mat and tests/reference/latest/AdjMatrix_data1_X_SCODE_datapmat_ID_542_lambda_0p01_replicate_2.mat have different values Maximum absolute difference: 0.011023879051208496 We expected the non-branching input data would give identical outputs, right? — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe.
Was that change in precision introduced in 1f6ac73eec6a285fb0c271a0b09cb7ef13706613? Moving the rind
selection line made sense, but I wasn't sure why the precision changed.
The new branching test case passes. We're still deciding how to adjust the failed tests for the original non-branching data.
Closes #49
Handles branching processes. Data file has an additional
branches
matrix with dimensions N_cells x N_branches, with its b-th column representing the b-th branch of the trajectory. If a cell is part of the b-th branch, the corresponding entry in the b-th column of branches = b, otherwise the corresponding entry = 0.This generates a GLG output for each branch separately, and the SINGE_Aggregate effectively provides a regulatory network describing the entire branching process.
MEX BUG workaround: This version also has a workaround to reduce the memory segmentation violations by clearing the mex file from MATLAB memory after each glmnet call. As a result, the memory occupied by the glmnetMex is released in each iteration.