buffer

Models for a data stream from a miniscope device: header formats, containers, etc.

pydantic model miniscope_io.models.buffer.BufferHeader

Container for the data stream’s header, structured by MetadataHeaderFormat

Show JSON schema
{
   "title": "BufferHeader",
   "description": "Container for the data stream's header, structured by :class:`.MetadataHeaderFormat`",
   "type": "object",
   "properties": {
      "linked_list": {
         "title": "Linked List",
         "type": "integer"
      },
      "frame_num": {
         "title": "Frame Num",
         "type": "integer"
      },
      "buffer_count": {
         "title": "Buffer Count",
         "type": "integer"
      },
      "frame_buffer_count": {
         "title": "Frame Buffer Count",
         "type": "integer"
      },
      "timestamp": {
         "title": "Timestamp",
         "type": "integer"
      }
   },
   "required": [
      "linked_list",
      "frame_num",
      "buffer_count",
      "frame_buffer_count",
      "timestamp"
   ]
}

Fields:
field buffer_count: int [Required]
field frame_buffer_count: int [Required]
field frame_num: int [Required]
field linked_list: int [Required]
field timestamp: int [Required]
classmethod from_format(vals: Sequence, format: BufferHeaderFormat, construct: bool = False) → _T

Instantiate a buffer header from linearized values (eg. in an ndarray or list) and an associated format that tells us what index the model values are found in that data.

Parameters:

  • vals (list, numpy.ndarray) – Indexable values to cast to the header model

  • format (BufferHeaderFormat) – Format used to index values

  • construct (bool) – If True , use model_construct() to create the model instance (ie. without validation, but faster). Default: False

Returns:

BufferHeader

pydantic model miniscope_io.models.buffer.BufferHeaderFormat

Format model used to parse header at the beginning of every buffer.

Show JSON schema
{
   "title": "BufferHeaderFormat",
   "description": "Format model used to parse header at the beginning of every buffer.",
   "type": "object",
   "properties": {
      "linked_list": {
         "title": "Linked List",
         "type": "integer"
      },
      "frame_num": {
         "title": "Frame Num",
         "type": "integer"
      },
      "buffer_count": {
         "title": "Buffer Count",
         "type": "integer"
      },
      "frame_buffer_count": {
         "title": "Frame Buffer Count",
         "type": "integer"
      },
      "timestamp": {
         "title": "Timestamp",
         "type": "integer"
      }
   },
   "required": [
      "linked_list",
      "frame_num",
      "buffer_count",
      "frame_buffer_count",
      "timestamp"
   ]
}

Fields:
field buffer_count: int [Required]
field frame_buffer_count: int [Required]
field frame_num: int [Required]
field linked_list: int [Required]
field timestamp: int [Required]