mth5.io.phoenix.readers.contiguous package

Submodules

mth5.io.phoenix.readers.contiguous.decimated_continuous_reader module

Module to read and parse native Phoenix Geophysics data formats of the MTU-5C Family.

This module implements Streamed readers for decimated continuos time series formats of the MTU-5C family.

author:: Jorge Torres-Solis

Revised 2022 by J. Peacock

class mth5.io.phoenix.readers.contiguous.decimated_continuous_reader.DecimatedContinuousReader(path: str | Path, num_files: int = 1, report_hw_sat: bool = False, **kwargs)[source]

Bases: TSReaderBase

Class to create a streamer for continuous decimated time series.

This reader handles continuous decimated time series files such as ‘td_150’, ‘td_30’. These files have no sub header information.

Parameters:

path (str or Path) – Path to the time series file
num_files (int, optional) – Number of files in the sequence, by default 1
report_hw_sat (bool, optional) – Whether to report hardware saturation, by default False
**kwargs – Additional keyword arguments passed to parent TSReaderBase class

subheader[source]

Empty dictionary as these files have no sub header information

Type:: dict

data_size[source]

Size of the data sequence when read

Type:: int or None

read() → ndarray[source]

Read in the full data from the current file.

Returns:: Single channel data array with dtype float32
Return type:: np.ndarray

read_sequence(start: int = 0, end: int | None = None) → ndarray[source]

Read a sequence of files.

Parameters:

start (int, optional) – Starting index in the sequence, by default 0
end (int or None, optional) – Ending index in the sequence to read, by default None

Returns:

Data within the given sequence range as float32 array

Return type:

np.ndarray

property segment_end_time: MTime[source]

Estimate end time of the segment.

The first sequence starts 1 second later than the set start time due to initiation within the data logger.

Returns:: Estimated end time from number of samples
Return type:: MTime

property segment_start_time: MTime[source]

Estimate the segment start time based on sequence number.

The first sequence starts 1 second later than the set start time due to initiation within the data logger.

Returns:: Start time of the recording segment
Return type:: MTime

property sequence_end: MTime[source]

Get the sequence end time.

Returns:: End time of the sequence based on data size or max samples
Return type:: MTime

property sequence_start: MTime[source]

Get the sequence start time.

Returns:: Start time of the sequence
Return type:: MTime

to_channel_ts(rxcal_fn: str | Path | None = None, scal_fn: str | Path | None = None) → ChannelTS[source]

Convert to a ChannelTS object.

Parameters:

rxcal_fn (str, Path or None, optional) – Path to receiver calibration file, by default None
scal_fn (str, Path or None, optional) – Path to sensor calibration file, by default None

Returns:

Channel time series object with data, metadata, and calibration

Return type:

ChannelTS

Module contents

class mth5.io.phoenix.readers.contiguous.DecimatedContinuousReader(path: str | Path, num_files: int = 1, report_hw_sat: bool = False, **kwargs)[source]

Bases: TSReaderBase

Class to create a streamer for continuous decimated time series.

This reader handles continuous decimated time series files such as ‘td_150’, ‘td_30’. These files have no sub header information.

Parameters:

path (str or Path) – Path to the time series file
num_files (int, optional) – Number of files in the sequence, by default 1
report_hw_sat (bool, optional) – Whether to report hardware saturation, by default False
**kwargs – Additional keyword arguments passed to parent TSReaderBase class

subheader

Empty dictionary as these files have no sub header information

Type:: dict

data_size

Size of the data sequence when read

Type:: int or None

read() → ndarray[source]

Read in the full data from the current file.

Returns:: Single channel data array with dtype float32
Return type:: np.ndarray

read_sequence(start: int = 0, end: int | None = None) → ndarray[source]

Read a sequence of files.

Parameters:

start (int, optional) – Starting index in the sequence, by default 0
end (int or None, optional) – Ending index in the sequence to read, by default None

Returns:

Data within the given sequence range as float32 array

Return type:

np.ndarray

property segment_end_time: MTime

Estimate end time of the segment.

The first sequence starts 1 second later than the set start time due to initiation within the data logger.

Returns:: Estimated end time from number of samples
Return type:: MTime

property segment_start_time: MTime

Estimate the segment start time based on sequence number.

The first sequence starts 1 second later than the set start time due to initiation within the data logger.

Returns:: Start time of the recording segment
Return type:: MTime

property sequence_end: MTime

Get the sequence end time.

Returns:: End time of the sequence based on data size or max samples
Return type:: MTime

property sequence_start: MTime

Get the sequence start time.

Returns:: Start time of the sequence
Return type:: MTime

to_channel_ts(rxcal_fn: str | Path | None = None, scal_fn: str | Path | None = None) → ChannelTS[source]

Convert to a ChannelTS object.

Parameters:

rxcal_fn (str, Path or None, optional) – Path to receiver calibration file, by default None
scal_fn (str, Path or None, optional) – Path to sensor calibration file, by default None

Returns:

Channel time series object with data, metadata, and calibration

Return type:

ChannelTS