allobjects · allobjectvars · hoc_pointer_ · name_declared · nrn_digest · object_id · object_pop · object_push · symbols · use_exp_pow_precision

Debugging and Internals Access

See also

neuron.nrn_dll()

Namespace Related

name_declared()

Python

Syntax:

type = n.name_declared("name")

type = n.name_declared("name", 1)

type = n.name_declared("name", 2)

Description:

Return 0 if the name is not in the NEURON/HOC symbol table. The first form looks for names in the top level symbol table. The second form looks in the current object context. The last form also looks in the top level symbol table but is useful in Python to distinguish subtypes of variables which appear as doubles in HOC but internally are really not doubles and so cannot be pointed to by double*, e.g., n.secondorder which is <type 'int'> or n._ref_nseg which raises either TypeError: Section access unspecified or TypeError: Cannot be a reference

If the name exists return:

Return Value	Description
2	If an objref
3	If a Section
4	If a strdef
5	If a scalar or double variable (if second arg is not 2)

If the second argument is 2:

Return Value	Description
5	If a scalar double
6	If a double array
7	If an integer
8	If a Section property

If none of the above apply, return 1.

Note

This function checks the NEURON/HOC symbol table; Python objects are handled separately.

To test if a simple name is a local variable in Python, use:

if 'soma' in locals():
    # do something

Checking against globals() and dir() are also often useful.

If the name is known in advance, use a try/except block and catch NameError and AttributeError:

try:
    n.soma.squiggle
except (NameError, AttributeError):
    print('Name does not exist')

Combining this with an eval can allow testing arbitrary names, but is potentially unsafe as it allows execution of arbitrary code.

HOC

Syntax:

type = name_declared("name")

type = name_declared("name", 1)

type = name_declared("name", 2)

Description:

Return 0 if the name is not in the symbol table. The first form looks for names in the top level symbol table. The second form looks in the current object context. The last form also looks in the top level symbol table but is useful in Python to distinguish subtypes of variables which appear as doubles in HOC but internally are really not doubles and so cannot be pointed to by double*, eg. n.secondorder which is <type ‘int’> or n.nseg which returns either TypeError: Section access unspecified or nseg  not a USERPROPERTY that can be pointed to

If the name exists return:

Return Value	Description
2	If an objref
3	If a Section
4	If a strdef
5	If a scalar or double variable (if second arg is not 2)

If the second argument is 2:

Return Value	Description
5	If a scalar double
6	If a double array
7	If an integer
8	If a Section property

If none of the above apply, return 1.

Note that names can be (re)declared only if they do not already exist or are already of the same type. This is too useful to require the user to waste an objref in creating a StringFunctions class to use is_name().

name_declared("nrnmainmenu_")
{object_push(nrnmainmenu_) print name_declared("ldfile", 0) object_pop()}
{object_push(nrnmainmenu_) print name_declared("ldfile", 1) object_pop()}

---

symbols()

Python

Name:

symbols — type the names of HOC functions and variables

Syntax:

n.symbols()

Description:

Types a list of functions and variable names defined in HOC. Dimensions of arrays are also indicated.

Warning

No longer works. The nearest replacement is dir(h) or SymChooser() .

HOC

Name:

symbols — type the names of HOC functions and variables

Syntax:

symbols()

Description:

Types a list of functions and variable names defined in HOC. Dimensions of arrays are also indicated.

Warning

No longer works. The nearest replacement is SymChooser() .

Object Related

object_id()

Python

Syntax:

n.object_id(objref)

n.object_id(objref, 1)

Description:

Returns 0 if the object reference does not point to an object instance. (Otherwise returns the pointer cast to a double, not a very useful number, except that this is equal to the value returned by Python’s hash function.)

If the second argument is 1, it returns the index of the object name. Returns -1 if the object is the NULLObject.

Example:

from neuron import n

a, b, c = n.List(), n.List(), n.Vector()

print(n.object_id(a))       # displays a double; equal to hash(a)
print(n.object_id(a, 1))    # 0 since a == n.List[0]
print(n.object_id(b, 1))    # 1 since b == n.List[1]
print(n.object_id(c, 1))    # 0 since c == n.Vector[0]

HOC

Syntax:

object_id(objref)

object_id(objref, 1)

Description:

Returns 0 if the object reference does not point to an object instance. (Otherwise returns the pointer cast to a double, not a very useful number, except that this is equal to the value returned by Python’s hash function.)

If the second argument is 1, it returns the index of the object name. Returns -1 if the object is the NULLObject.

Example:

objref a, b, c
a = new List()
b = new List()
c = new Vector()

print object_id(a)       // displays a double; equal to hash(a)
print object_id(a, 1)    // 0 since a == List[0]
print object_id(b, 1)    // 1 since b == List[1]
print object_id(c, 1)    // 0 since c == Vector[0]

---

allobjectvars()

Python

Syntax:

n.allobjectvars()

Description:

Prints all the HOC object references (objref variables) that have been declared along with the class type of the object they reference and the number of references. Objects created via Python and not assigned to a HOC objref will not appear.

Example:

>>> n('objref foo')
1
>>> n.foo = n.Vector()
>>> n.allobjectvars()
obp hoc_obj_[0] -> NULL
obp hoc_obj_[1] -> NULL
obp foo[0] -> Vector[0] with 1 refs.
0.0
>>> banana = n.foo
>>> n.allobjectvars()
obp hoc_obj_[0] -> NULL
obp hoc_obj_[1] -> NULL
obp foo[0] -> Vector[0] with 2 refs.
0.0

HOC

Syntax:

allobjectvars()

Description:

Prints all the object references (objref variables) that have been declared along with the class type of the object they reference and the number of references.

Warning

Instead of printing the address of the object in hex format, it ought also to print the object_id and/or the internal instance name.

---

allobjects()

Python

Syntax:

n.allobjects()

n.allobjects("templatename")

nref = n.allobjects(objectref)

Description:

Prints the internal names of all class instances (objects) available from the interpreter along with the number of references to them.

With a templatename the list is restricted to objects of that class.

With an object variable, nothing is printed but the reference count is returned. The count is too large by one if the argument was of the form templatename[index] since a temporary reference is created while the object is on the stack during the call.

Example:

>>> v = n.Vector()
>>> foo = n.List()
>>> n.allobjects()
List[0] with 1 refs
Vector[0] with 1 refs
0.0
>>> n.allobjects('Vector')
Vector[0] with 1 refs
0.0
>>> n.allobjects(foo)
2.0

See also

Use a List to programmatically loop over all instances of a template.

HOC

Syntax:

allobjects()

allobjects("templatename")

nref = allobjects(objectref)

Description:

Prints the internal names of all class instances (objects) available from the interpreter along with the number of references to them.

With a templatename the list is restricted to objects of that class.

With an object variable, nothing is printed but the reference count is returned. The count is too large by one if the argument was of the form templatename[index] since a temporary reference is created while the object is on the stack during the call.

---

object_push()

Python

Syntax:

n.object_push(objref)

Description:

Enter the context of the object referenced by objref. In this context you can directly access any variables or call any functions, even those not declared as public. Do not attempt to create any new symbol names! This function is generally used by the object itself to save its state in a session.

HOC

Syntax:

object_push(objref)

Description:

Enter the context of the object referenced by objref. In this context you can directly access any variables or call any functions, even those not declared as public. Do not attempt to create any new symbol names! This function is generally used by the object itself to save its state in a session.

---

object_pop()

Python

Syntax:

n.object_pop()

Description:

Pop the last object from an object_push() .

HOC

Syntax:

object_pop()

Description:

Pop the last object from an object_push() .

---

Miscellaneous

hoc_pointer_()

Python

Syntax:

n.hoc_pointer_(variable_ref)

Description:

A function used by C and C++ implementations to request a pointer to the variable from its interpreter name. Not needed by or useful for the user; returns 1.0 on success.

HOC

Syntax:

hoc_pointer_(&variable)

Description:

A function used by C and C++ implementations to request a pointer to the variable from its interpreter name. Not needed by or useful for the user; returns 1.0 on success.

---

Debugging

nrn_digest()

Python

Syntax:

n.nrn_digest()

n.nrn_digest(tid, i)

n.nrn_digest(tid, i, "abort")

n.nrn_digest(filename)

Description:

Available when configured with the cmake option -DNRN_ENABLE_DIGEST=ON

If the same simulation gives different results on different machines, this function can help isolate the statement that generates the first difference during the simulation. I think ParallelContext.prcellstate() is generally better, but in rare situations, nrn_digest can be very helpful.

The first three forms begin digest gathering. The last form prints the gathered digest information to the filename. With just the two tid, i arguments, the i gathered item of the tid thread is printed (for single thread simulations, use tid = 0), to the terminal as well as the individual values of the array for that digest item. With the third "abort" argument, the ith gathered item is printed and abort() is called (dropping into gdb if that is being used so that one can observe the backtrace).

Lines are inserted into the digest by calling the C function declared in src/oc/nrndigest.h.

void nrn_digest_dbl_array(const char* msg, int tid, double t, double* array, size_t sz);

at the moment, such lines are present in src/nrncvode/occvode.cpp to instrument the cvode callbacks that compute y' = f(y, t) and the approximate jacobian matrix solver M*x = b. I.e in part

#include "nrndigest.h"
...
void Cvode::fun_thread(neuron::model_sorted_token const& sorted_token,
        double tt,
        double* y,
        double* ydot,
        NrnThread* nt) {
    CvodeThreadData& z = CTD(nt->id);
#if NRN_DIGEST
    if (nrn_digest_) {
        nrn_digest_dbl_array("y", nt->id, tt, y, z.nvsize_);
    }
#endif
...
#if NRN_DIGEST
    if (nrn_digest_ && ydot) {
        nrn_digest_dbl_array("ydot", nt->id, tt, ydot, z.nvsize_);
    }
#endif

Note: when manually adding such lines, the conditional compilation and nrn_digest_ test are not needed. The arguments to nrn_digest_dbl_array determine the line added to the digest. The 5th arg is the size of the 4th arg double array. The double array is processed by SHA1 and the first 16 hex digits are appended to the line. An example of the first few lines of output in a digest file is .. code-block:

tid=0 size=1344
y 0 0 0 e1f6a372856b45e6
y 0 1 0 e1f6a372856b45e6
ydot 0 2 0 523c9694c335e458
y 0 3 4.7121609153871379e-09 fabb4bc469447404
ydot 0 4 4.7121609153871379e-09 60bcff174645fc29

The first line is thread id and number of lines for that thread. Other thread groups, if any, follow the end of each thread group. The digest lines consist of thread id, line identifier (start from 0 for each group), double value of the 3rd arg, hash of the array.

---

use_exp_pow_precision()

Python

Syntax:

n.use_exp_pow_precision(istyle)

Description:

Works when configured with the cmake option -DNRN_ENABLE_ARCH_INDEP_EXP_POW=ON and otherwise does nothing.

• istyle = 1

  All calls to exp() and pow() as well as their use internally, in mod files, and by cvode, are computed on mac, linux, windows so that double precision floating point results are cross platform consistent. (Makes use of a multiple precision floating-point computation library.)

• istyle = 2

  exp and pow are rounded to 32 bits of mantissa

• istyle = 0

  Default. exp and pow calcualted natively (cross platform values can have round off error differences.)

  When using clang (eg. on a mac) cross platform floating point identity is often attainable with C and C++ flag option "-ffp-contract=off".