Data

Classes for using in-memory data from a miniscope

pydantic model miniscope_io.data.Frame

An individual frame from a miniscope recording

Typically returned from SDCard.read()

Show JSON schema

{
   "title": "Frame",
   "type": "object",
   "properties": {
      "data": {
         "default": null,
         "title": "Data"
      },
      "headers": {
         "items": {
            "$ref": "#/$defs/SDBufferHeader"
         },
         "title": "Headers",
         "type": "array"
      }
   },
   "$defs": {
      "SDBufferHeader": {
         "description": "Header data at the start of each frame",
         "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"
            },
            "pixel_count": {
               "title": "Pixel Count",
               "type": "integer"
            },
            "length": {
               "title": "Length",
               "type": "integer"
            },
            "write_buffer_count": {
               "title": "Write Buffer Count",
               "type": "integer"
            },
            "dropped_buffer_count": {
               "title": "Dropped Buffer Count",
               "type": "integer"
            },
            "data_length": {
               "title": "Data Length",
               "type": "integer"
            },
            "write_timestamp": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Write Timestamp"
            },
            "battery_voltage": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Battery Voltage"
            }
         },
         "required": [
            "linked_list",
            "frame_num",
            "buffer_count",
            "frame_buffer_count",
            "timestamp",
            "pixel_count",
            "length",
            "write_buffer_count",
            "dropped_buffer_count",
            "data_length"
         ],
         "title": "SDBufferHeader",
         "type": "object"
      }
   },
   "required": [
      "headers"
   ]
}

Config:

• arbitrary_types_allowed: bool = True

Fields:

• data (numpy.ndarray)

• headers (List[miniscope_io.models.sdcard.SDBufferHeader])

Validators:

• frame_nums_must_be_equal » headers

field data: ndarray [Required]

field headers: List[SDBufferHeader] [Required]

Validated by:

• frame_nums_must_be_equal

validator frame_nums_must_be_equal  »  headers

Each frame_number field in each header must be the same (they come from the same frame!)

property frame_num: int | None

Frame number for this set of headers, if headers are present

pydantic model miniscope_io.data.Frames

A collection of frames from a miniscope recording

Show JSON schema

{
   "title": "Frames",
   "type": "object",
   "properties": {
      "frames": {
         "default": null,
         "title": "Frames"
      }
   }
}

Fields:

• frames (List[miniscope_io.data.Frame])

field frames: List[Frame] [Required]

flatten_headers(as_dict: Literal[False]) → List[SDBufferHeader]

flatten_headers(as_dict: Literal[True]) → List[dict]

Return flat list of headers, not grouped by frame

Parameters:

as_dict (bool) – If True, return a list of dictionaries, if False (default), return a list of SDBufferHeader s.

to_df(what: Literal['headers'] = 'headers') → DataFrame

Convert frames to pandas dataframe

Parameters:

what ('headers') – What information from the frame to include in the df, currently only ‘headers’ is possible