collection

Classes

Collection(name, columns, types)

Manages a collection of data entries stored in a CSV file and a pandas DataFrame.
class Collection(name: str, columns: list[str], types: list[Type])[source]

Bases: EventBase

Manages a collection of data entries stored in a CSV file and a pandas DataFrame.

name

Name of the collection.

Type:

str

columns

List of column names.

Type:

list[str]

types

List of column data types.

Type:

list[Type]

dict

Dictionary mapping columns to types.

Type:

dict

path

Path to the CSV file.

Type:

Path

df

The pandas DataFrame holding the data.

Type:

pd.DataFrame

add_entry(entry: list) → None[source]

Adds a new entry to the collection.

Parameters:

entry (list) – The list of values for the new row.

static convert_with_default(value, target_type: Any) → Any[source]

Converts a value to a target type, using defaults for failures.

Parameters:

  • value – The value to convert.

  • target_type (Any) – The target type.

Returns:

The converted value or a default.

Return type:

Any

convert_df_to_types(df: pandas.DataFrame) → pandas.DataFrame[source]

Converts DataFrame columns to the specified types.

Parameters:

df (pd.DataFrame) – The DataFrame to convert.

Returns:

The converted DataFrame.

Return type:

pd.DataFrame

check_split_csv() → None[source]

Checks if the CSV file is too large and splits it if necessary.

get_last_entry(column: str, value: str) → pandas.Series | None[source]

Gets the last entry matching a specific value in a column.

Parameters:

  • column (str) – The column to search.

  • value (str) – The value to match.

Returns:

The last matching row, or None.

Return type:

Union[pd.Series, None]

get_last_entry_name(column: str, value: str) → str | None[source]

Gets the ‘name’ field of the last entry matching a condition.

Parameters:

  • column (str) – The column to search.

  • value (str) – The value to match.

Returns:

The name, or None.

Return type:

str | None

get_first_entry(column: str, value: str) → pandas.Series | None[source]

Gets the first entry matching a specific value in a column.

Parameters:

  • column (str) – The column to search.

  • value (str) – The value to match.

Returns:

The first matching row, or None.

Return type:

Union[pd.Series, None]

change_last_entry(column: str, value: Any) → None[source]

Updates a value in the last entry of the DataFrame and saves.

Parameters:

  • column (str) – The column to update.

  • value (Any) – The new value.

log(date: str, type: str, subject: str, description: str) → None[source]

Logs an event if the collection schema matches standard logging fields.

Parameters:

  • date (str) – Date string.

  • type (str) – Event type.

  • subject (str) – Subject name.

  • description (str) – Description.

log_temp(date: str, temperature: float, humidity: float) → None[source]

Logs temperature if the collection schema matches temperature fields.

Parameters:

  • date (str) – Date string.

  • temperature (float) – Temperature value.

  • humidity (float) – Humidity value.

get_last_water_df() → pandas.DataFrame[source]

Returns the latest water calibration entries for each port.

Returns:

Filtered DataFrame with max calibration numbers per port.

Return type:

pd.DataFrame

get_last_sound_df() → pandas.DataFrame[source]

Returns the latest sound calibration entries for each speaker/sound.

Returns:

Filtered DataFrame with max calibration numbers per sound.

Return type:

pd.DataFrame

get_valve_time(port: int, volume: float) → float[source]

Calculates valve open time for a given volume based on calibration.

Parameters:

  • port (int) – The port number.

  • volume (float) – The target volume in ul.

Returns:

The time in seconds.

Return type:

float

Raises:

ValueError – If calibration data is invalid or missing.

get_sound_gain(speaker: int, dB: float, sound_name: str) → float[source]

Calculates sound gain for a target dB based on calibration.

Parameters:

  • speaker (int) – The speaker ID.

  • dB (float) – The target decibels.

  • sound_name (str) – The name of the sound.

Returns:

The gain factor.

Return type:

float

Raises:

ValueError – If calibration data is invalid or missing.

save_from_df(training: TrainingProtocolBase = TrainingProtocolBase()) → None[source]

Saves values from the current DataFrame to the CSV file, processing formatting.

Parameters:

training (TrainingProtocolBase) – Protocol for formatting specific fields.

df_from_df(df: pandas.DataFrame, training: TrainingProtocolBase) → pandas.DataFrame[source]

Processes a DataFrame for saving (formatting dates, enums, etc).

Parameters:

  • df (pd.DataFrame) – The input DataFrame.

  • training (TrainingProtocolBase) – The training protocol for custom formatting.

Returns:

The processed DataFrame.

Return type:

pd.DataFrame