Pycotools
0.0
Quick Start
Create Michaelis-Menten Model
Simulate Michaelis-Menten model
Plot results
Inspect the model
Prepare Time Course Results for Parameter Estimation
Do parameter estimations
Visualize data
Profile Likelihoods
Best Parameters
Installation, dependencies, versions, environment variables
COPASI
COPASI Environment Variables
On Linux or macOS
On Windows
Python
Python3 Users
IDE
Pip
Pycotools
The Model
The Zi2012 Model
Parse a Model into Pycotools
Open and Save
Get Model Information
Model attributes
Access Model Attributes
Get, Set, Add and Remove
How to get model objects
Get the Smad3c metabolite
Get any global quantity with a fixed simulation_type attribute
Get a function by its expression
Get all local parameters in the R17_LRC_formation reaction
How to change existing model attributes
Change the name of a metabolite
Change initial_value of a global_quantity
How to add a model component
Add a metabolite
Add a global quantity to the model
Add a reaction
Remove model components
Build a new model: The Build Context Manager
Build With Antimony
Build Models With Antimony
A Negative Feedback Motif
Simulate from Negative Feedback Model
Positive Plus Negative Feedbck Loop
Simulate
TimeCourse
Imports and Getting the Test Model
Get Model Object
Deterministic Time Course
Run a deterministic time course
Save time course configured model
Being selective about which output variables to select
Visualization
Plot the results
Plot on the same axis
Choose Y variables
Plot in Phase Space
Save to file
Alternative Solvers
Stochastic MM
Run a Time Course Using Direct Method
Plot stochastic time course
Parameter Scan
Get Model String
Parse Model
Parameter Scan
Two Way Parameter Scan
Repeat Scan Items
Parameter Estimation Tutorial
Build a Model
Experimental Data Files
Simulate Experimental Data
Format the Simulated Data
Setup and run single parameter estimation
Use Particle Swarm
Use Genetic Algorithm
Write Parameter Estimation Configuration File
Configure Parameter Estimation
Set up the Parameter Estimation
Run Parameter Estimation
Check Parameter Estimation Report Exists
Visualize Parameter Estimaton Data
Save to File
Choose Results Directory
Specify Which Variables to Plot
Multiple Data Files
Generate Multiple Synthetic Data Files
Setup and Run Parameter Estimation
Plot the Results
Steady State Experiments
Setup and Run Parameter Estimation
Parameter Estimation Workflow
Build Example Model
Simulate Time Course
Generate Synthetic Data
Format synthetic data
Run parameter estimations
Exploratory data analysis on parameter estimation data
Evaluate the performance of the optimization algorithm
Likelihood-Ranks Plot
Distributions of parameters
Boxplots
Histograms
Correlations
Pearsons Correlations
Scatters
Time course Ensemble
Profile Likelihoods
Run Local Chaser Estimation
Run Profile Likelihoods
Plot Profile Likelihoods
Interpretation
Summary
Optimization performance
Trajectories
Distributions
Correlations
Profile Likelihoods
Modifications for Fit2
Best parameters Versus True Parameters
Insert Parameters
Build Example Model
Insert Parameters from Python Dictionary
Insert Parameters from Pandas DataFrame
Insert Parameters from Parameter Estimation Output
Insert Parameters using the
model.Model().insert_parameters
method
Change parameters using
model.Model().set
Model Selection Workflow
Simulate the Models
Simulate Synthetic Data
Perform Model Selection
Calculate and Plot Model Selection Criteria
Best Parameters
Interpretation
Subsequent Analysis
Ensemble Time Courses
Likelihood ranks
Boxplots
Correlations
Scatter Graphs
Profile Likelihoods
Calculation
Visualization
Examples
The Lorenz attractor system
Visualization
Time on x axis
Phase Space Plots
The Lotka Volterra System
Visualization
Repressilator
Define the Model
Simulate
API Documentation
model
tasks
Viz
kwargs
Kwargs for plotting
savefig kwargs
truncate-kwargs
Caveats
Non-Ascii Characters
Parameter Estimation
Duplicate Names
Known Bugs
Pycotools
Docs
»
Python Module Index
Python Module Index
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