List: accept_action · append · browser · count · index · insrt · o · object · prepend · remove · remove_all · scroll_pos · select · select_action · selected

List

class List

List of objects

Syntax:

n.List()

n.List("templatename")

Description:

The List class provides useful tools for creating and manipulating lists of objects. In many cases, e.g., if you have a network of cells connected at synapses and each synapse is a separate object, you might want to store such information (pre-syns, post-syns, cells) using regular Python lists.

Besides interacting with legacy code, the NEURON List class provides two key features not available in Python lists:

The ability to create a dynamic List of all the object instances of a template (e.g., all instances of an "IClamp" or of a cell class.)
The ability to create a GUI browser for the list, which can be used to select and interact with the objects in the list.

There are two ways of invoking the constructor:

n.List(): Create an empty list. Objects added to the list are referenced. Objects removed from the list are unreferenced.
n.List("templatename"): Create a list of all the object instances of the template. These object instances are NOT referenced and therefore the list dynamically changes as objects of template instances are created and destroyed. Adding and removing objects from this kind of list is not allowed.

Example:

from neuron import n

clamps = n.IClamp(), n.IClamp(), n.IClamp()

all_iclamps = n.List('IClamp')
print(f'There are initially {len(all_iclamps)} IClamp objects.') # 3

another = n.IClamp()

print(f'There are now {len(all_iclamps)} IClamp objects.')       # 4

List.append()

Syntax:: l.append(object)
Description:: Append an object to a list, and return the number of items in list.

List.prepend()

Syntax:: l.prepend(object)
Description:: Add an object to the beginning of a list, and return the number of objects in the list. The inserted object has index=0. Following objects have an incremented index.

List.insrt()

Syntax:

l.insrt(i, object)

Description:

Insert an object before item i, and return the number of items in the list. The inserted object has index i, following items have an incremented index.

Not called insert because that name is a HOC keyword.

List.remove()

Syntax:: l.remove(i)
Description:: Remove the object at index i. Following items have a decremented index. ie it’s often most convenient to remove items from back to front. Return the number of objects remaining in the list.

List.remove_all()

Syntax:: l.remove_all()
Description:: Remove all the objects from the list. Return 0.

List.index()

Syntax:

l.index(object)

Description:

Return the index of the object in the List. Return a -1 if the object is not in the List.

This is approximately analogous to the Python list method .index(), except that the method for Python lists raises a ValueError if the object is not in the list.

List.count()

Syntax:

l.count()

Description:

Return the number of objects in the list.

This is mostly useful for legacy code. A more Python solution is to just use len(my_list).

List.browser()

Syntax:

l.browser()

l.browser("title", "strname")

l.browser("title", py_callable)

Description:

l.browser(["title"], ["strname"])
Make the list visible on the screen. The items are normally the object names but if the second arg is present and is the name of a string symbol that is defined in the object’s template, then that string is displayed in the list.

l.browser("title", py_callable)
Browser labels are computed. For each item, py_callable is executed with n.hoc_ac_ set to the index of the item. Some objects notify the List when they change, ie point processes when they change their location notify the list.

Example:

from neuron import n, gui

my_list = n.List()

for word in ['Python', 'HOC', 'NEURON', 'NMODL']:
    my_list.append(n.String(word))

my_list.browser('title', 's')   # n.String objects have an s attribute that returns the Python string

Example of computed labels:

from neuron import n, gui

my_list = n.List()
for word in ['NEURON', 'HOC', 'Python', 'NMODL']:
    my_list.append(n.String(word))

def label_with_lengths():
    item_id = n.hoc_ac_
    item = my_list[item_id].s
    return f'{item} ({len(item)})'

my_list.browser('Words!', label_with_lengths)

If we now execute the following line to add an entry to the List, the new entry will appear in the browser immediately:

my_list.append(n.String('Neuroscience'))

List.selected()

Syntax:: l.selected()
Description:: Return the index of the highlighted object or -1 if no object is highlighted.

See also

List.browser()

List.select_action()

Syntax:

l.select_action(command)

l.select_action(command, False or True)

Description:

Execute a command (a Python funciton handle) when an item in the list List.browser() is selected by single clicking the mouse.

If the second arg exists and is True (or 1) then the action is only called on the mouse button release. If nothing is selected at that time then hoc_ac_ = -1

Example:

from neuron import n, gui

my_list = n.List()

def on_click():
    item_id = my_list.selected()
    if item_id >= 0: # check to make sure selection isn't dragged off
        print(f'Item {item_id} selected ({my_list[item_id].s})')


for word in ['Python', 'HOC', 'NEURON', 'NMODL']:
    my_list.append(n.String(word))

my_list.browser('title', 's')
my_list.select_action(on_click)

List.accept_action()

Syntax:

l.accept_action(command)

Description:

Execute a command (a Python function handle) when double clicking on an item displayed in the list List.browser() by the mouse.

Usage mirrors that of List.select_action().

List.object()

Syntax:

l.object(i)

l.o(i)

Description:

Return the object at index i.

This is mostly useful for legacy code. In Python, use, e.g. my_list[i] instead.

List.o()

Syntax:

l.object(i)

l.o(i)

Description:

Return the object at index i.

This is mostly useful for legacy code. In Python, use, e.g. my_list[i] instead.