TutorialΒΆ
import SBMLKinetics
initial_model_indx = 5
final_model_indx = 6
model_indices = range(initial_model_indx, final_model_indx+1)
analyzer = KineticAnalyzer(path = 'D:/path/to/folder',
dataSet = "biomodels.zip", model_indices=model_indices)
#Query Distributions
analyzer.getKTypeDistribution()
analyzer.getKTypeDistributionPerRType(R_type = SBMLKinetics.types.R_type(1,1))
analyzer.getRTypeDistribution()
analyzer.getRTypeDistributionPerModel()
#Query Elements
analyzer.getTopKType()[0].K_type_str
analyzer.getKTypeProb(K_type = SBMLKinetics.types.K_type("NA")
analyzer.getTopKTypePerRType(R_type = SBMLKinetics.types.R_type(1,1))[0].K_type_str
analyzer.getKTypeProbPerRType(R_type = SBMLKinetics.types.R_type(1,1), K_type=SBMLKinetics.types.K_type("NA"))
analyzer.getTopRType()[0].rct_num
analyzer.getRTypeProb(R_type = SBMLKinetics.types.R_type(1,1))
analyzer.getNumSBMLModelsAnalyzed()
analyzer.getNumRxnsAnalyzed()
#Plots
analyzer.plotKTypeDistribution(path = 'D:/path/to/folder/')
analyzer.plotKTypeDistributionPerRType(R_type = SBMLKinetics.types.R_type(1,1))
analyzer.plotKTypeDistributionVsRType()
analyzer.plotRTypeDistribution()
analyzer.plotRTypeDistributionPerModel()
For example, the output of analyzer.getKTypeDistribution() is a dataframe as below.
Classifications |
Percentage |
Percentage standard error |
Percentage per model |
Percentage per model standard error |
|---|---|---|---|---|
ZERO |
0.33333 |
0 |
0.33333 |
0 |
UNDR |
0.33333 |
0 |
0.33333 |
0 |
UNMO |
0 |
0 |
0 |
0 |
BIDR |
0 |
0 |
0 |
0 |
BIMO |
0 |
0 |
0 |
0 |
MM |
0 |
0 |
0 |
0 |
MMCAT |
0 |
0 |
0 |
0 |
HILL |
0 |
0 |
0 |
0 |
FR |
0 |
0 |
0 |
0 |
NA |
0.33333 |
0 |
0.33333 |
0 |