mth5.io.phoenix.readers.calibrations

Created on Thu Jun 15 15:21:35 2023

@author: jpeacock

Calibrations can come in json files. the JSON file includes filters for all lowpass filters, so you need to match the lowpass filter used in the setup with the lowpass filter. Then you need to add the dipole length and sensor calibrations.

Classes

PhoenixCalibration

Phoenix Geophysics calibration data reader and filter manager.

Module Contents

class mth5.io.phoenix.readers.calibrations.PhoenixCalibration(cal_fn: str | pathlib.Path | None = None, **kwargs: Any)[source]

Phoenix Geophysics calibration data reader and filter manager.

This class reads Phoenix calibration files in JSON format and provides access to frequency response filters for different channels and lowpass filter settings. It supports both receiver and sensor calibration files.

Parameters:

cal_fn (str or pathlib.Path, optional) – Path to the calibration file to read. If provided, the file will be loaded automatically during initialization.
**kwargs (Any) – Additional keyword arguments that will be set as instance attributes.

obj[source]

The parsed calibration object containing all calibration data.

Type:: Any or None

obj: Any = None[source]

property cal_fn: pathlib.Path[source]

Path to the calibration file.

Returns:: The path to the calibration file.
Return type:: pathlib.Path

property calibration_date: mt_metadata.common.mttime.MTime | None[source]

Get the calibration date from the loaded calibration data.

Returns:: The calibration date as an MTime object, or None if no data is loaded.
Return type:: MTime or None

get_max_freq(freq: numpy.typing.NDArray[numpy.floating] | list[float] | numpy.ndarray) → int[source]

Calculate the maximum frequency for filter naming.

Determines the power-of-10 frequency limit based on the maximum frequency in the input array. Used to name filters as {channel}_{max_freq}hz_lowpass.

Parameters:: freq (numpy.ndarray) – Array of frequency values in Hz.
Returns:: The power-of-10 frequency limit (e.g., 1000 for frequencies up to 9999 Hz).
Return type:: int

Examples

>>> cal = PhoenixCalibration()
>>> freq = np.array([1.0, 10.0, 100.0, 1500.0])
>>> cal.get_max_freq(freq)
1000

property base_filter_name: str | None[source]

Generate the base filter name from instrument information.

Creates a standardized filter name prefix based on the instrument type, model, and serial number from the calibration data.

Returns:: Base filter name in format “{instrument_type}_{instrument_model}_{serial}” converted to lowercase, or None if no data is loaded.
Return type:: str or None

Examples

>>> cal = PhoenixCalibration("calibration.json")
>>> cal.base_filter_name
'mtu-5c_rmt03-j_666'

get_filter_lp_name(channel: str, max_freq: int) → str[source]

Generate a lowpass filter name for a specific channel and frequency.

Creates a standardized filter name for receiver calibration filters in the format: {base_filter_name}_{channel}_{max_freq}hz_lowpass

Parameters:

channel (str) – Channel identifier (e.g., ‘e1’, ‘h2’).
max_freq (int) – Maximum frequency in Hz for the lowpass filter.

Returns:

Complete lowpass filter name in lowercase.

Return type:

str

Examples

>>> cal = PhoenixCalibration("calibration.json")
>>> cal.get_filter_lp_name("e1", 1000)
'mtu-5c_rmt03-j_666_e1_1000hz_lowpass'

get_filter_sensor_name(sensor: str) → str[source]

Generate a sensor filter name for a specific sensor.

Creates a standardized filter name for sensor calibration filters in the format: {base_filter_name}_{sensor}

Parameters:: sensor (str) – Sensor identifier or serial number.
Returns:: Complete sensor filter name in lowercase.
Return type:: str

Examples

>>> cal = PhoenixCalibration("calibration.json")
>>> cal.get_filter_sensor_name("sensor123")
'mtu-5c_rmt03-j_666_sensor123'

read(cal_fn: str | pathlib.Path | None = None) → None[source]

Read and parse a Phoenix calibration file.

Loads calibration data from a JSON file and creates frequency response filters for each channel and frequency band. The method creates channel attributes (e.g., self.e1, self.h2) containing either: - Dictionary of filters by frequency (receiver calibration) - Single filter object (sensor calibration)

Parameters:: cal_fn (str, pathlib.Path, or None, optional) – Path to the calibration file to read. If None, uses the previously set calibration file path.
Raises:: IOError – If the calibration file cannot be found or read.

Notes

The method automatically determines calibration type based on file_type: - “receiver calibration”: Creates multiple filters per channel by frequency - “sensor calibration”: Creates single filter per channel

get_filter(channel: str, filter_name: str | int) → mt_metadata.timeseries.filters.FrequencyResponseTableFilter[source]

Get the frequency response filter for a specific channel and filter.

Retrieves the lowpass filter for the given channel and filter specification. The method automatically handles both string and integer filter names.

Parameters:

channel (str) – Channel identifier (e.g., ‘e1’, ‘h2’, ‘h3’).
filter_name (str or int) – Filter specification, typically the lowpass frequency in Hz (e.g., 1000, ‘100’, 10000).

Returns:

The frequency response filter object containing the calibration data for the specified channel and filter.

Return type:

FrequencyResponseTableFilter

Raises:

AttributeError – If the specified channel is not found in the calibration data.
KeyError – If the specified filter is not found for the given channel.

Examples

>>> cal = PhoenixCalibration("calibration.json")
>>> filt = cal.get_filter("e1", 1000)
>>> print(f"Filter name: {filt.name}")
>>> print(f"Frequency points: {len(filt.frequencies)}")