Hi,
You can use any of the scipy distributions (https://docs.scipy.org/doc/scipy/reference/stats.html) as a prior in pydream.
To use a uniform and a gaussian distribution you can do something like this:
from scipy.stats import norm, uniform
par1 = SampledParam(uniform, loc=lower_limits, scale=scale)
par2=SampledParam(norm, loc=mean, scale=std)
sampled_parameters = [par1, par2Hope this is helpful
Hi @pietromicheli, if your parameters change over time as a function of the concentration of one or multiples species in your model, you can create an Expression and pass it as rules' rates. For doing something like this, you can check this example:
https://github.com/pysb/pysb/blob/master/pysb/examples/expression_observables.py
If you just want to pass a list parameter values to be used at different time points, I am not aware that there is function like that in pysb. However, you could simulate the first time points with the parameters that you want and then used the simulated results as the initial conditions of the next simulation that has different parameter values. For an example like that, take a look at this function:
@alubbock might have some better ideas :)
Hi @ortega2247 and @lh64, thank you for the answers! :)
@lh64 you're definitely right, I apologize. I'm trying to model a post-synaptic neuron activity:
First, I simulate the gating of post-synaptic ion channels in a Pysb model. Then I use the trajectory of the open channels to calculate, for each time point, the quantity of Calcium ions that flow in the time unit. This post simulation calculation will create an array (of length equal to the time span array used for the first pysb simulation) that basically describes the time course of the post-synaptic calcium influx. What I'm trying to do now is to pass this array to a second Pysb model which contains some Calcium-dependent reactions. The goal here is to use the values of my array (one for each time step) to drive a synthesis-like reaction for a Calcium monomer that can be used by all the Calcium-dependent reactions. I really hope it's clear enough! :)
Thanks a lot @ortega2247 , your function seems super cool for creating a kind of discrete event during the simulation, but in this case I want that my parameter continuously change at each time step :)
I am a PyDream user. I wanted to confirm that there is no strict requirement for the number of chains in Dream(ZS), right? For 19 parameters, can I use 5 chains? For MCMC-DE, we had to use a minimum of D/2 chains where D is the dimension of parameter space. I read that Dream(ZS) does not have any such requirement. Just wanted to double-check.
Thanks
model.rules object by excluding the Rule(s) you don't want, using model.reset_equations to clear out the reactions, species, etc. created by BNG, and then regenerating the network. Here's a small example script I put together doing that:
initials or param_values arguments to the run method of the simulator. I'm attaching an example here. I defined two simple rules: X() >> None and A() + X() >> X(). In the code, I first run a simulation of the full system. Then, I run two sequential simulations, the first with only the X() >> None rule and the second with only the A() + X() >> X() rule, where the concentration of X() from the first simulation is fed into the simulator for the second simulation using the initials argument to ScipyOdeSimulator.run. To be clear, the second "simulation" is actually a series of simulations from output time point to output time point, with the final concentration of A() from the previous step and the corresponding value of X() passed into the simulator at each step. I have it loop over three different numbers of output points (10, 100, and 1000) to show how the output of the sequential simulation approaches the true result from the full simulation as the number of output points increases. I'm attaching those plots here as well. Hopefully this helps. If you have any further questions just let us know.
@lh64 Thank you for the answer!
Actually my first approach to this problem was to iteratively run one simulation for each time point just as you suggested, but I wasn't very happy with the computational cost of a such sequential simulation (expecially for a high number of time points). However looking at your code I noticed that (stupidly) I created at each iteration a new simulator object (via ScipyOdeSimulator() function). So it turned out that this unnecessary step tripled the cost of each iteration, compared to the cost that runinning the simulations (via .run() method) using always the same simulator object at each iteration would require. The overall cost is still quite high obviously, but for reasonably small number of time points it is tollerable.
Your answer and your code has been really helpfull, thanks a lot! :)
Was there any change made in the PyDream in the last one month? I installed the package again and the "start" argument is not working. It does not matter what chain initialization I give, the chains are starting at random positions. Any help here would be appreciated. Before I reinstalled PyDream yesterday, I did not have this issue.
pip show pydream in the terminal. The version should be 2.0.0
https://github.com/LoLab-VU/PyDREAM/pull/20/files/384866c232f9a16b8da4a7ececea62d665eaf644
Hi, I am having some ongoing trouble with the SBML exporter. Specifically the line 'sbml_output = export(model, 'sbml'). I never had problems before and had been using PySB to build and then export my models for some time, but after starting a new venv (under PyCharm) and I assume then using the latest package versions I started having issues. I solved these by just returning to the exact package versions for everything that I had, which fixed it. However now I am moving from a local instance to AWS, I am seeing the same issues and so far have not been able to solve them with package versions. The initial error is:
Traceback (most recent call last):
File "predict_KOs.py", line 605, in <module>
main()
File "predict_KOs.py", line 591, in main
mode_1_results = run_mode_1()
File "predict_KOs.py", line 375, in run_mode_1
model = build.build_model(networks[network])
File "/home/ubuntu/build.py", line 1177, in build_model
sbml_output = export(model, 'sbml')
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/init.py", line 176, in export
return e.export()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/sbml.py", line 315, in export
return libsbml.writeSBMLToString(self.convert(level=level))
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/sbml.py", line 125, in convert
pysb.bng.generate_equations(self.model)
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/bng.py", line 732, in generate_equations
verbose=verbose, **kwargs).split('\n'))
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/bng.py", line 672, in generate_network
bngfile.execute()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/bng.py", line 443, in execute
output += self.generator.get_content()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/generator/bng.py", line 26, in get_content
self.generate_content()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/generator/bng.py", line 31, in generate_content
self.generate_parameters()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/generator/bng.py", line 42, in generate_parameters
exprs = self.model.expressions_constant()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/core.py", line 1976, in expressions_constant
cset = ComponentSet(e for e in self.expressions
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/core.py", line 2255, in init
for value in iterable:
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/core.py", line 1977, in <genexpr>
if e.is_constant_expression())
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/core.py", line 1644, in is_constant_expression
for a in self.expr.atoms())
File "/home/ubuntu/.local/lib/python3.7/site-packages/sympy/core/basic.py", line 523, in atoms
result = {node for node in nodes if not node.args}
File "/home/ubuntu/.local/lib/python3.7/site-packages/sympy/core/basic.py", line 523, in <setcomp>
result = {node for node in nodes if not node.args}
AttributeError: 'str' object has no attribute 'args'
which is obtained using sympy==1.6.1. If I instead use sympy 1.5.1 (which is the version I had it working locally with), I get a an error about the BNG2.pl file, which I have confirmed is where it should be:
Traceback (most recent call last):
File "predict_KOs.py", line 605, in <module>
main()
File "predict_KOs.py", line 591, in main
mode_1_results = run_mode_1()
File "predict_KOs.py", line 375, in run_mode_1
model = build.build_model(networks[network])
File "/home/ubuntu/build.py", line 1177, in build_model
sbml_output = export(model, 'sbml')
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/init.py", line 176, in export
return e.export()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/sbml.py", line 315, in export
return libsbml.writeSBMLToString(self.convert(level=level))
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/sbml.
the end of the second error was missed off:
Traceback (most recent call last):
File "predict_KOs.py", line 605, in <module>
main()
File "predict_KOs.py", line 591, in main
mode_1_results = run_mode_1()
File "predict_KOs.py", line 375, in run_mode_1
model = build.build_model(networks[network])
File "/home/ubuntu/build.py", line 1177, in build_model
sbml_output = export(model, 'sbml')
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/init.py", line 176, in export
return e.export()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/sbml.py", line 315, in export
return libsbml.writeSBMLToString(self.convert(level=level))
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/export/sbml.py", line 125, in convert
pysb.bng.generate_equations(self.model)
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/bng.py", line 732, in generate_equations
verbose=verbose, **kwargs).split('\n'))
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/bng.py", line 672, in generate_network
bngfile.execute()
File "/home/ubuntu/.local/lib/python3.7/site-packages/pysb/bng.py", line 487, in execute
p_err.rstrip())
pysb.bng.BngInterfaceError:
Can't open perl script "BioNetGen-2.5.0/BNG2.pl": No such file or directory
conda install -c alubbock pysb, the dependency versions should be pinned correctly (please let me know if not).