Hello,

I'm trying to model a channel that is governed by 4 states, C1,C2,C3,O. The transitions from 1 state to another are bidirectional. I have initialised these states using the rxd.State and tried to model them using rxd.Rate, but am getting a compilation error "TypeError: unsupported operand type(s) for *: 'float' and 'Rate' ".

O = rxd.State(cyt_er_membrane, initial=0)

C1= rxd.State(cyt_er_membrane, initial=1)

C2 = rxd.State(cyt_er_membrane, initial=0)

C3 = rxd.State(cyt_er_membrane, initial=0)

C1 = rxd.Rate(C1, ((kim*C2)-(ki*ca[cyt]*C1))-((ko*ca[cyt]**2*C1)-(kom*O)))

C2 = rxd.Rate(C2, (((ki*ca[cyt]*O)-(kim*C2))-((kom*C2)-(ko*ca[cyt]**2*C3))))

O = rxd.Rate(O, ((ko*C1*ca[cyt]**2)-(kom*O))-((ki*ca[cyt]*O)-(kim*C2)))

C3 = rxd.Rate(C3, (((kom*C2)-(ko*C3*ca[cyt]**2))-((kim*C3)-(ki*ca[cyt]*C1))))

I had also tried using rxd.Reaction but the error is "'Reaction' object has no attribute '_sources'". I feel I'm making a fundamental mistake while modelling these equations in RxD.

(my apologies for the inelegant codes)

## Modelling a channel with multiple markov states

**Moderators:** hines, wwlytton, ramcdougal

### Re: Modelling a channel with multiple markov states

...Interesting, I didn't realise that was a feature of RxD, my Markov channel models are built with Channel Builder and then imported into my code (that includes RxD). I will interested to hear the answer to this enquiry also.

Regards

Regards

### Re: Modelling a channel with multiple markov states

This channel has a parameter that is gated by ca[er]. I have an NMODL equivalent of this channel but I don't know how to make that .mod file read the changes in ca[er]. That's why I thought of modelling it in RxD, where I can declare its 'Region' and 'Direction of action'.

How did you overcome this problem? That might also help me in my end-objective.

How did you overcome this problem? That might also help me in my end-objective.

### Re: Modelling a channel with multiple markov states

Sorry, my RXD models use pointers to gate channelbuilder channels with temperature not Ca[er]. So that approach may work with your problem, using Ca[er] instead of temperature... but look I am just a regular NEURON user, not an expert, so lets see what the experts say :-)

If "your" method works it seems much more direct!!!

If "your" method works it seems much more direct!!!

### Re: Modelling a channel with multiple markov states

I think the problem is with the Python namespace. When you create your first rate "C1 = rxd.Rate(C1, ... " it overwrites the C1 state you defined earlier, so when you come to use it in "O = rxd.Rate(O, ((ko*C1 ...", the C1 here now refers to a Rate not a State.

The solution is to use a different variable names for all your rates e.g.

C1transition = rxd.Rate(C1, ((kim*C2)-(ki*ca[cyt]*C1))-((ko*ca[cyt]**2*C1)-(kom*O)))

The solution is to use a different variable names for all your rates e.g.

C1transition = rxd.Rate(C1, ((kim*C2)-(ki*ca[cyt]*C1))-((ko*ca[cyt]**2*C1)-(kom*O)))

### Re: Modelling a channel with multiple markov states

Hello,

I have been working on this for a while and I'm quite lost.

As explained in the first post, I am trying to create a multiple state Markov model. It is of the form:

r1 = rxd.Rate(C1, ((kim*C2)-(ki*ca[cyt]*C1))-((ko*ca[cyt]**2*C1)-(kom*O)))

r2 = rxd.Rate(C2, (((ki*ca[cyt]*O)-(kim*C2))-((kom*C2)-(ko*ca[cyt]**2*C3))))

r3 = rxd.Rate(O, ((ko*C1*ca[cyt]**2)-(kom*O))-((ki*ca[cyt]*O)-(kim*C2)))

r4= rxd.Rate(C3, (((kom*C2)-(ko*C3*ca[cyt]**2))-((kim*C3)-(ki*ca[cyt]*C1))))

Kr = A*O #where A is a constant (float)

a1 = rxd.MultiCompartmentReaction(ca[er]>ca[cyt],Kr, membrane=cyt_er_membrane)

1. Now, I am unable to plot Kr with respect to time and the error displayed is:

ValueError: x and y must have same first dimension, but have shapes (1049,) and (1,)

2. The type(Kr) is "neuron.rxd.rxdmath._Arithmeticed", whereas it should be an array, same as type(time)

I tried converting Kr to an array but the above type does not have ".as_numpy() attribute"

3. I converted ca[cyt] to a numpy array and tried to resimulate r1, r2, r3, r4, but I get the following error:

TypeError: unhashable type: 'numpy.ndarray'

I'm not able to understand how to resolve this.

I have been working on this for a while and I'm quite lost.

As explained in the first post, I am trying to create a multiple state Markov model. It is of the form:

r1 = rxd.Rate(C1, ((kim*C2)-(ki*ca[cyt]*C1))-((ko*ca[cyt]**2*C1)-(kom*O)))

r2 = rxd.Rate(C2, (((ki*ca[cyt]*O)-(kim*C2))-((kom*C2)-(ko*ca[cyt]**2*C3))))

r3 = rxd.Rate(O, ((ko*C1*ca[cyt]**2)-(kom*O))-((ki*ca[cyt]*O)-(kim*C2)))

r4= rxd.Rate(C3, (((kom*C2)-(ko*C3*ca[cyt]**2))-((kim*C3)-(ki*ca[cyt]*C1))))

Kr = A*O #where A is a constant (float)

a1 = rxd.MultiCompartmentReaction(ca[er]>ca[cyt],Kr, membrane=cyt_er_membrane)

1. Now, I am unable to plot Kr with respect to time and the error displayed is:

ValueError: x and y must have same first dimension, but have shapes (1049,) and (1,)

2. The type(Kr) is "neuron.rxd.rxdmath._Arithmeticed", whereas it should be an array, same as type(time)

I tried converting Kr to an array but the above type does not have ".as_numpy() attribute"

3. I converted ca[cyt] to a numpy array and tried to resimulate r1, r2, r3, r4, but I get the following error:

TypeError: unhashable type: 'numpy.ndarray'

I'm not able to understand how to resolve this.

### Re: Modelling a channel with multiple markov states

I think the problem is O is a rxd.State. To access the values of a state (or species) you can use the nodes.

E.g. If you have defined nodes on a section called ‘dend’ then;
Will give you the value of O at the current time in the simulation, in the middle of ‘dend’.

To record the value during a simulation use;
To plot Kr just multiple the vector the float e.g.
Similarly for ca, you can access the nodes by specifying both the region and the segment, e.g.

E.g. If you have defined nodes on a section called ‘dend’ then;

Code: Select all

`O.nodes(dend(0.5)).value`

To record the value during a simulation use;

Code: Select all

`O_vec = h.Vector().record(O.nodes(dend(0.5))._ref_value)`

Code: Select all

`Kr_vec = A*O_vec`

Code: Select all

`ca_er_vec = h.Vector().record(ca.nodes(er)(dend(0.5))._ref_concentration)`

### Re: Modelling a channel with multiple markov states

Thank you sir. I will try this out