protocol

Representations of experimental protocols: multiple Task s grouped together with Graduation objects.

Classes:

`Task_Params`	Metaclass for storing task parameters
`Trial_Data`	Base class for declaring trial data.
`Step_Group`	An hdf5 group for an individual step within a protocol.
`Protocol_Group`	The group and subgroups for a given protocol.
`Step_Data`	Schema for storing data for a single step of a protocol
`Protocol_Data`

pydantic model Task_Params[source]

Bases: Autopilot_Type

Metaclass for storing task parameters

Todo

Not yet used in GUI, terminal, and subject classes. Will replace the dictionary structure ASAP

Show JSON schema

{
   "title": "Task_Params",
   "description": "Metaclass for storing task parameters\n\n.. todo::\n\n    Not yet used in GUI, terminal, and subject classes. Will replace the dictionary structure ASAP",
   "type": "object",
   "properties": {}
}

pydantic model Trial_Data[source]

Bases: Table

Base class for declaring trial data.

Tasks should subclass this and add any additional parameters that are needed. The subject class will then use this to create a table in the hdf5 file.

See Nafc.TrialData for an example

Show JSON schema

{
   "title": "Trial_Data",
   "description": "Base class for declaring trial data.\n\nTasks should subclass this and add any additional parameters that are needed.\nThe subject class will then use this to create a table in the hdf5 file.\n\nSee :attr:`.Nafc.TrialData` for an example",
   "type": "object",
   "properties": {
      "group": {
         "title": "Group",
         "description": "Path of the parent step group",
         "type": "array",
         "items": {
            "type": "string"
         }
      },
      "session": {
         "title": "Session",
         "description": "Current training session, increments every time the task is started",
         "type": "array",
         "items": {
            "type": "integer"
         }
      },
      "session_uuid": {
         "title": "Session Uuid",
         "description": "Each session gets a unique uuid, regardless of the session integer, to enable independent addressing of sessions when session numbers might overlap (eg. reassignment)",
         "type": "array",
         "items": {
            "type": "string"
         }
      },
      "trial_num": {
         "title": "Trial Num",
         "description": "Trial data is grouped within, well, trials, which increase (rather than resetting) across sessions within a task",
         "datajoint": {
            "key": true
         },
         "type": "array",
         "items": {
            "type": "integer"
         }
      }
   },
   "required": [
      "session",
      "trial_num"
   ]
}

Fields:

group (List[str] | None)
session (List[int] | None)
session_uuid (List[str] | None)
trial_num (List[int] | None)

field group: List[str] | None = None: Path of the parent step group

field session: List[int] | None [Required]: Current training session, increments every time the task is started

field session_uuid: List[str] | None = None: Each session gets a unique uuid, regardless of the session integer, to enable independent addressing of sessions when session numbers might overlap (eg. reassignment)

field trial_num: List[int] | None [Required]: Trial data is grouped within, well, trials, which increase (rather than resetting) across sessions within a task

pydantic model Step_Group[source]

Bases: H5F_Group

An hdf5 group for an individual step within a protocol.

Typically this is populated by passing a step number and a dictionary of step parameters.

Parameters:

step (int) – Step number within a protocol
group_path (str) – Path to the group within an HDF5 file
step_dict (dict) – Dictionary of step parameters. Either this or step_name must be passed
step_name (str) – Step name – if step_dict is not present, use this to generate a name for the created hdf5 group
trial_data (Trial_Data) – Explicitly passed Trial_Data object. If not passed, get from the task_type parameter in the step_dict
**data – passed to superclass __init__ method

Show JSON schema

{
   "title": "Step_Group",
   "description": "An hdf5 group for an individual step within a protocol.\n\nTypically this is populated by passing a step number and a dictionary of step parameters.",
   "type": "object",
   "properties": {
      "path": {
         "title": "Path",
         "type": "string"
      },
      "title": {
         "title": "Title",
         "default": "",
         "type": "string"
      },
      "filters": {
         "title": "Filters"
      },
      "attrs": {
         "title": "Attrs",
         "type": "object"
      },
      "children": {
         "title": "Children"
      },
      "step_name": {
         "title": "Step Name",
         "type": "string"
      },
      "step": {
         "title": "Step",
         "type": "integer"
      },
      "trial_data": {
         "title": "Trial Data"
      },
      "continuous_group": {
         "title": "Continuous Group"
      }
   },
   "required": [
      "path",
      "step_name",
      "step"
   ]
}

Config:

arbitrary_types_allowed: bool = True

Fields:

continuous_group (autopilot.data.interfaces.tables.H5F_Group | None)
path (str)
step (int)
step_name (str)
trial_data (Type[autopilot.data.models.protocol.Trial_Data] | None)

field step_name: str [Required]

field step: int [Required]

field path: str [Required]

field trial_data: Type[Trial_Data] | None = <class 'autopilot.data.models.protocol.Trial_Data'>

field continuous_group: H5F_Group | None = None

pydantic model Protocol_Group[source]

Bases: H5F_Group

The group and subgroups for a given protocol.

For each protocol, a main group is created that has the name of the protocol, and then subgroups are created for each of its steps.

Within each step group, a table is made for TrialData, and tables are created as-needed for continuous data.

For Example:

/ data
|--- protocol_name
    |--- S##_step_name
    |   |--- trial_data
    |   |--- continuous_data
    |--- ... additional steps

Todo

Also make a Step group… what’s the matter with ya.

Override default __init__ method to populate a task’s groups.

Todo

When finished, replace the implicit structure of the protocol dictionary with Task_Params

Parameters:

protocol_name (str) – Name of a protocol (filename minus .json)
protocol (List[dict]) – A list of dictionaries, one with the parameters for each task level.
**data – passed to superclass init

Show JSON schema

{
   "title": "Protocol_Group",
   "description": "The group and subgroups for a given protocol.\n\nFor each protocol, a main group is created that has the name of the protocol,\nand then subgroups are created for each of its steps.\n\nWithin each step group, a table is made for TrialData, and tables are created\nas-needed for continuous data.\n\nFor Example::\n\n    / data\n    |--- protocol_name\n        |--- S##_step_name\n        |   |--- trial_data\n        |   |--- continuous_data\n        |--- ... additional steps\n\n.. todo::\n\n    Also make a Step group... what's the matter with ya.",
   "type": "object",
   "properties": {
      "path": {
         "title": "Path",
         "type": "string"
      },
      "title": {
         "title": "Title",
         "default": "",
         "type": "string"
      },
      "filters": {
         "title": "Filters"
      },
      "attrs": {
         "title": "Attrs",
         "type": "object"
      },
      "children": {
         "title": "Children"
      },
      "protocol_name": {
         "title": "Protocol Name",
         "type": "string"
      },
      "protocol": {
         "title": "Protocol",
         "type": "array",
         "items": {
            "type": "object"
         }
      },
      "tabs": {
         "title": "Tabs"
      },
      "steps": {
         "title": "Steps"
      }
   },
   "required": [
      "path",
      "protocol_name",
      "protocol"
   ]
}

Config:

arbitrary_types_allowed: bool = True

Fields:

protocol (List[dict])
protocol_name (str)
steps (List[autopilot.data.models.protocol.Step_Group])
tabs (List[autopilot.data.interfaces.tables.H5F_Table])

field protocol_name: str [Required]

field protocol: List[dict] [Required]

field tabs: List[H5F_Table] [Required]

field steps: List[Step_Group] [Required]

pydantic model Step_Data[source]

Bases: Schema

Schema for storing data for a single step of a protocol

Show JSON schema

{
   "title": "Step_Data",
   "description": "Schema for storing data for a single step of a protocol",
   "type": "object",
   "properties": {
      "task": {
         "$ref": "#/definitions/Task_Params"
      },
      "trial_data_table": {
         "$ref": "#/definitions/Table"
      },
      "trial_data": {
         "$ref": "#/definitions/Trial_Data"
      },
      "continuous_data": {
         "title": "Continuous Data",
         "type": "object",
         "additionalProperties": {
            "type": "array",
            "items": {}
         }
      }
   },
   "required": [
      "task",
      "trial_data_table",
      "trial_data",
      "continuous_data"
   ],
   "definitions": {
      "Task_Params": {
         "title": "Task_Params",
         "description": "Metaclass for storing task parameters\n\n.. todo::\n\n    Not yet used in GUI, terminal, and subject classes. Will replace the dictionary structure ASAP",
         "type": "object",
         "properties": {}
      },
      "Table": {
         "title": "Table",
         "description": "Tabular data: each field will have multiple values -- in particular an equal number across fields.\n\nUsed for trialwise data, and can be used to create pytables descriptions.\n\n.. todo::\n\n    To make this usable as a live container of data, the fields need to be declared as Lists (eg. instead of just\n    declaring something an ``int``, it must be specified as a ``List[int]`` to pass validation. We should expand this\n    model to relax that constraint and effectively treat every field as containing a list of values.",
         "type": "object",
         "properties": {}
      },
      "Trial_Data": {
         "title": "Trial_Data",
         "description": "Base class for declaring trial data.\n\nTasks should subclass this and add any additional parameters that are needed.\nThe subject class will then use this to create a table in the hdf5 file.\n\nSee :attr:`.Nafc.TrialData` for an example",
         "type": "object",
         "properties": {
            "group": {
               "title": "Group",
               "description": "Path of the parent step group",
               "type": "array",
               "items": {
                  "type": "string"
               }
            },
            "session": {
               "title": "Session",
               "description": "Current training session, increments every time the task is started",
               "type": "array",
               "items": {
                  "type": "integer"
               }
            },
            "session_uuid": {
               "title": "Session Uuid",
               "description": "Each session gets a unique uuid, regardless of the session integer, to enable independent addressing of sessions when session numbers might overlap (eg. reassignment)",
               "type": "array",
               "items": {
                  "type": "string"
               }
            },
            "trial_num": {
               "title": "Trial Num",
               "description": "Trial data is grouped within, well, trials, which increase (rather than resetting) across sessions within a task",
               "datajoint": {
                  "key": true
               },
               "type": "array",
               "items": {
                  "type": "integer"
               }
            }
         },
         "required": [
            "session",
            "trial_num"
         ]
      }
   }
}

Fields:

continuous_data (Dict[str, list])
task (autopilot.data.models.protocol.Task_Params)
trial_data (autopilot.data.models.protocol.Trial_Data)
trial_data_table (autopilot.data.modeling.base.Table)

field task: Task_Params [Required]

field trial_data_table: Table [Required]

field trial_data: Trial_Data [Required]

field continuous_data: Dict[str, list] [Required]

pydantic model Protocol_Data[source]

Bases: Schema

Show JSON schema

{
   "title": "Protocol_Data",
   "description": "A special type of type intended to be a representation of an\nabstract structure/schema of data, rather than a live container of\ndata objects themselves. This class is used for constructing data containers,\ntranslating between formats, etc. rather than momentary data handling",
   "type": "object",
   "properties": {
      "steps": {
         "title": "Steps",
         "type": "array",
         "items": {
            "$ref": "#/definitions/Step_Data"
         }
      }
   },
   "required": [
      "steps"
   ],
   "definitions": {
      "Task_Params": {
         "title": "Task_Params",
         "description": "Metaclass for storing task parameters\n\n.. todo::\n\n    Not yet used in GUI, terminal, and subject classes. Will replace the dictionary structure ASAP",
         "type": "object",
         "properties": {}
      },
      "Table": {
         "title": "Table",
         "description": "Tabular data: each field will have multiple values -- in particular an equal number across fields.\n\nUsed for trialwise data, and can be used to create pytables descriptions.\n\n.. todo::\n\n    To make this usable as a live container of data, the fields need to be declared as Lists (eg. instead of just\n    declaring something an ``int``, it must be specified as a ``List[int]`` to pass validation. We should expand this\n    model to relax that constraint and effectively treat every field as containing a list of values.",
         "type": "object",
         "properties": {}
      },
      "Trial_Data": {
         "title": "Trial_Data",
         "description": "Base class for declaring trial data.\n\nTasks should subclass this and add any additional parameters that are needed.\nThe subject class will then use this to create a table in the hdf5 file.\n\nSee :attr:`.Nafc.TrialData` for an example",
         "type": "object",
         "properties": {
            "group": {
               "title": "Group",
               "description": "Path of the parent step group",
               "type": "array",
               "items": {
                  "type": "string"
               }
            },
            "session": {
               "title": "Session",
               "description": "Current training session, increments every time the task is started",
               "type": "array",
               "items": {
                  "type": "integer"
               }
            },
            "session_uuid": {
               "title": "Session Uuid",
               "description": "Each session gets a unique uuid, regardless of the session integer, to enable independent addressing of sessions when session numbers might overlap (eg. reassignment)",
               "type": "array",
               "items": {
                  "type": "string"
               }
            },
            "trial_num": {
               "title": "Trial Num",
               "description": "Trial data is grouped within, well, trials, which increase (rather than resetting) across sessions within a task",
               "datajoint": {
                  "key": true
               },
               "type": "array",
               "items": {
                  "type": "integer"
               }
            }
         },
         "required": [
            "session",
            "trial_num"
         ]
      },
      "Step_Data": {
         "title": "Step_Data",
         "description": "Schema for storing data for a single step of a protocol",
         "type": "object",
         "properties": {
            "task": {
               "$ref": "#/definitions/Task_Params"
            },
            "trial_data_table": {
               "$ref": "#/definitions/Table"
            },
            "trial_data": {
               "$ref": "#/definitions/Trial_Data"
            },
            "continuous_data": {
               "title": "Continuous Data",
               "type": "object",
               "additionalProperties": {
                  "type": "array",
                  "items": {}
               }
            }
         },
         "required": [
            "task",
            "trial_data_table",
            "trial_data",
            "continuous_data"
         ]
      }
   }
}

Fields:

steps (List[autopilot.data.models.protocol.Step_Data])

field steps: List[Step_Data] [Required]