The following sections describe the different parameter types and internal AlliGator variables that can be passed.

AlliGator Python Plugins API v 1

AlliGator versions: 0.63-current

Parameter Types

The following input parameter types are supported:

Type	Example	Description
U8	1	unsigned byte
U16	1	unsigned short integer
U32	1	unsigned long integer
I8	-1	signed byte
I16	-1	signed short integer
I32	-1	signed long integer
float32	1.0	single-precision floating point number
float64	1.0	double-precision floating point number
string	a string	string
path	C:\Desktop\test.txt	file or folder path
boolean	True	boolean: True or False
AlliGator	Phasor Frequency	any exposed AlliGator parameter [*]

[*]

Requested AlliGator parameters are provided automatically to the plugin function. To obtain a list of current exposed internal AlliGator parameters, use the Send button in the Settings:Plugins panel. This will send a copy of that list to the Clipboard, together with the current parameter values.

A list of exposed parameters with their default values can be found here.

Check the Parameter Names only checkbox in the Settings:Plugins panel to get a list of exposed internal AlliGator parameters without their current value.

AlliGator Python Plugin Data Types

The different data types are declared in the alligator.py script found in the Python Plugins folder, reproduced below:

# AlliGator Python Plugin Definitions
# Author: X. Michalet
# Last modified: 2026-02-18

### AlliGator Python Plugin API Version = 1 ###

# makes sure the path to AlliGator Plugins is known to Python

import os
import sys

def define_plugin_path():

    if not (os.getenv('LOCALAPPDATA')+'/AlliGator/Python Plugins' in os.environ):
        sys.path.append(os.getenv('LOCALAPPDATA')+'/AlliGator/Python Plugins')

    return()


import collections
from collections import namedtuple

graph_plugin_data = namedtuple('graph_plugin_data',\
    'Graph_Name, Plots, Reference_Decay')

# where 'Plots' is a list of, and 'Reference_Decay' is a, plot_plugin_data:

plot_plugin_data = namedtuple('plot_plugin_data',\
    'Plot_Name, X_Array, Y_Array')

# where 'X_Array' and 'Y_Array' are 1D lists of double-precision
# floating point numbers

empty_plot = plot_plugin_data(Plot_Name = '', X_Array = [], Y_Array = [])

fli_dataset_plugin_data = namedtuple('fli_dataset_plugin_data',\
    'FLI_Dataset_Name, Gate_Duration, \
    Gate_Separation, Gate_Number, X_Size, Y_Size, Image_Data_List,\
    Reference_Decay, Mask_Image, Parameter_Map')

# where 'Image_Data_List' is a list of image_plugin_data:

image_plugin_data = namedtuple('image_plugin_data',\
    'Image_Name, Image')

# where 'Image' is a 2D list of single-precision floating point numbers

# and 'Parameter_Map' is a named tuple:

parameter_map_plugin_data = namedtuple('parameter_map_plugin_data',\
    'Parameter_Names, Parameter_Flattened_Map, Locations,\
    IRF_X,IRF_Y_Flattened_List')

# where 'Parameter_Names' is a list of provided parameters,
# 'Parameter_Flattened_Map' is a list of parameter lists, one parameter list
# per valid location
# 'Locations' is a list of namedtuple, coordinatess of the fitted decays
# 'IRF_X' is the common time axis of al IRFs
# 'IRF_Y_Flattened_List' is a list of IRF Intensities at the different locations
# Note that in principle, the number of locations can be different from the
# number of parameter lists

empty_map = parameter_map_plugin_data(
    Parameter_Names = [],
    Parameter_Flattened_Map = [],
    Locations = [],
    IRF_X = [],
    IRF_Y_Flattened_List = [])

location = namedtuple('location', 'X, Y')