pyspex package

Subpackages

Submodules

pyspex.binning_tables module

Tools to read or write definitions of SPEXone binning-tables.

class pyspex.binning_tables.BinningTables(ckd_dir: str | None = None)[source]

Bases: object

Class to handle SPEXone binning-table definitions.

Parameters:

ckd_dir (Path) – Specify the name of directory with SPEXone binning-table files.

Raises:

FileNotFoundError – Directory with SPEXone binning-table files does not exist.

Notes

Syntax of the file name with SPEXone binning-tables:

SPX1_CKD_BIN_TBL_<yyyymmddTHHMMSS>_<NNN>.nc

where yyyymmddTHHMMSS defines the validity start (UTC) and NNN the release number of the file format.

The binning tables as defined on-ground are supposed to be available during the whole mission at the same on-board memory location. Because these original binning tables are necessary for re-processing and may facilitate instrument performance monitoring. Therefore, it is preferred that a new binning table is added to the current set, without changing the validity start string. However, new binning-table file should be released in case any of the binning tables are overwritten.

Examples

# create new file with binning-table definitions:

> bin_tbl = BinningTables()
> bin_tbl.create_if_needed(validity_start)
> bin_tbl.add_table(0, lineskip_arr, binning_table)
> bin_tbl.add_table(1, lineskip_arr, binning_table)

# add a new binning-table to an existing file:

> bin_tbl BinningTables()
> bin_tbl.create_if_needed(validity_start)
> bin_tbl.add_table(2, lineskip_arr, binning_table)

# use binning-table ‘130’ to unbin SPEXone detector data:

> bin_tbl BinningTables()
> bin_tbl.search(coverage_start)
> img = bin_tbl.unbin(130, img_binned)
add_table(table_id: int, lineskip_arr: ndarray, binning_table: ndarray) → None[source]

Add a binning table definition to existing file.

Parameters:

  • table_id (int) – Table identifier (integer between 1 and 255)

  • lineskip_arr (ndarray) – Lineskip array definition

  • binning_table (ndarray) – Binning table definition

create_if_needed(validity_start: str, release: int = 1) → None[source]

Initialize CKD file for binning tables if not exist.

Parameters:

  • validity_start (str) – Validity start of the CKD data, as yyyymmddTHHMMSS

  • release (int, default=1) – Release number, start at 1

search(coverage_start: str | None = None) → None[source]

Search CKD file with binning tables.

Parameters:

coverage_start (str, default=None) – time_coverage_start or start of the measurement (UTC)

Raises:

FileNotFoundError – No CKD with binning tables found

unbin(table_id: int, img_binned: ndarray) → ndarray[source]

Return unbinned detector data.

Parameters:

  • table_id (int) – Table identifier (integer between 1 and 255)

  • img_binned (np.ndarray) – Binned image data (1D array)

Returns:

unbinned image data (no interpolation).

Return type:

np.ndarray

pyspex.ccsds_io module

Contains the class CCSDSio to read SPEXone telemetry packets.

class pyspex.ccsds_io.CCSDSio(file_list: list)[source]

Bases: object

Read SPEXone telemetry packets.

Parameters:

file_list (iterator to strings) – list of file-names, where each file contains parts of a measurement

Notes

The formats of the PACE telemetry packets are following the standards: CCSDS-131.0-B-3, CCSDS-132.0-B-2 and CCSDS-133.0-B-1.

This module is currenty restriced to telementry packets with APID: 0x350 (Science), 0x320 (NomHK) and 0x322 (DemHK).

A telemtry packet consist of a PRIMARY HEADER, SECONDARY HEADER (consist of a timestamp) and USER DATA with the actual telemetry packet data.

Doc: TMTC handbook (SPX1-TN-005), issue 12, 15-May-2020

The files with science and telemetry data needs to be in chronological order. However, you may mix science and housekeeping data as long as science data are chronological and housekeeping data are chronological.

Examples

>>> packets = ()
>>> with CCSDSio(['file1', 'file2', 'file3']) as ccsds:
>>>     while True:
>>>         # read one telemetry packet at a time
>>>         packet = ccsds.read_packet()
>>>         if packet is None:
>>>             # now we have read all files
>>>             break
>>>
>>>         packets += (packet[0],)
>>>
>>>     # combine segmented Science packages
>>>     science_tm = ccsds.science_tm(packets)
>>>     # now you may want to collect the engineering packages
property ap_id: int | None

Returns SPEXone ApID.

close() → None[source]

Close resources.

static fix_dem_hk24(dem_hk: ndarray) → ndarray[source]

Correct 32-bit values in the DemHk.

Which originate from 24-bit values of the detector register parameters.

Parameters:

dem_hk (numpy.ndarray) – SPEXone DEM housekeeping packages

Returns:

SPEXone DEM housekeeping packages

Return type:

numpy.ndarray

static fix_sci_hk24(sci_hk: ndarray) → ndarray[source]

Correct 32-bit values in the Science HK.

Which originate from 24-bit values in the detector register parameters. In addition:

- copy the first 4 bytes of DET_CHENA to DET_ILVDS
- parameter 'REG_BINNING_TABLE_START' was writen in little-endian
Parameters:

sci_hk (numpy.ndarray) – SPEXone Science telemetry packages

Returns:

SPEXone Science telemetry packages

Return type:

numpy.ndarray

property grouping_flag: int | None

Returns grouping flag.

The meaning of the grouping flag values are:

00 continuation packet-data segment
01 first packet-data segment
10 last packet-data segment
11 packet-data unsegmented
open_next_file() → None[source]

Open next file from file_list.

property packet_length: int | None

Returns size of packet data in bytes.

Value equals secondary header + user data (always odd)

read_packet() → ndarray | None[source]

Read next telemetry packet.

Returns:

CCSDS packet data

Return type:

numpy.ndarray

science_tm(packets_in: tuple) → tuple[source]

Combine segmented Science telemetry packages.

Parameters:

packets_in (tuple) – Science or house-keeping telemetry packages

Returns:

unsegmented Science telemetry packages

Return type:

tuple

property secnd_hdr_flag: bool | None

Returns flag indicating presence of a secondary header.

static select_tm(packets_in: tuple, ap_id: int) → tuple[source]

Select telemetry packages on SPEXone ApID.

Parameters:

  • packets_in (tuple) – SPEXone telemetry packages

  • ap_id (int) – SPEXone ApID

Returns:

selected telemetry packages

Return type:

tuple

property sequence_count: int | None

Returns sequence counter, rollover to zero at 0x3FFF.

property type_indicator: int | None

Returns type of telemetry packet.

property version_no: int | None

Returns CCSDS version number.

pyspex.ccsds_io.hk_sec_of_day(ccsds_sec: ndarray, ccsds_subsec: ndarray, ref_day: datetime | None = None) → ndarray[source]

Convert CCSDS timestamp to seconds after midnight.

Parameters:

  • ccsds_sec (numpy array (dtype='u4')) – Seconds since 1970-01-01 (or 1958-01-01)

  • ccsds_subsec (numpy array (dtype='u2')) – Sub-seconds as (1 / 2**16) seconds

  • ref_day (datetime.datetime, optional) –

Return type:

numpy.ndarray with sec_of_day

pyspex.ccsds_io.img_sec_of_day(img_sec: ndarray, img_subsec: ndarray, img_hk: ndarray) → tuple[datetime, float | Any][source]

Convert Image CCSDS timestamp to seconds after midnight.

Parameters:

  • img_sec (numpy array (dtype='u4')) – Seconds since 1970-01-01 (or 1958-01-01)

  • img_subsec (numpy array (dtype='u2')) – Sub-seconds as (1 / 2**16) seconds

  • img_hk (numpy array) – DemHK telemetry packages

Returns:

reference day: datetime, sec_of_day: numpy.ndarray

Return type:

tuple

pyspex.ckd_io module

Contains the class CKDio to read SPEXone CKD.

References

class pyspex.ckd_io.CKDio(ckd_file: Path, verbose: bool = False)[source]

Bases: object

Defines a class to read SPEXone CKD parameters.

Parameters:

  • ckd_file (str) – Name of CKD file

  • verbose (bool, default=False) – Be verbose

Examples

Read several CKD parameters:

>>> with CKDio(Path('SPX1_CKD.nc')) as ckd:
>>>    dark = ckd.dark()
>>>    fov = ckd.fov()
close() → None[source]

Make sure that we close all resources.

dark() → Dataset | None[source]

Read Dark CKD.

Returns:

parameters of the SPEXone Dark CKD

Return type:

xarray.Dataset

date_created(compact: bool = False) → str[source]

Return creation date of the CKD product.

Parameters:

compact (bool) – return date in iso-format if not compact else return ‘YYYYmmddHHMMSS’

fov() → Dataset | None[source]

Read field-of-view CKD.

Returns:

parameters of the SPEXone field-of-view CKD

Return type:

xarray.Dataset

property git_commit: str

Return git hash of repository spexone_cal, used to generate the CKD.

nlin() → Dataset | None[source]

Read non-linearity CKD.

Returns:

parameters of the SPEXone non-linearity CKD

Return type:

xarray.Dataset

noise() → Dataset | None[source]

Read Noise CKD.

Returns:

parameters of the SPEXone Noise CKD

Return type:

xarray.Dataset

polarimetric() → Dataset | None[source]

Read Polarimetric CKD.

Returns:

parameters of the SPEXone Polarimetric CKD

Return type:

xarray.Dataset

prnu() → DataArray | None[source]

Read PRNU CKD.

Returns:

parameters of the SPEXone PRNU CKD

Return type:

xr.DataArray

property processor_version: str

Return the version of the spexone_cal program.

radiometric() → DataArray | None[source]

Read Radiometric CKD.

Returns:

parameters of the SPEXone Radiometric CKD

Return type:

xr.DataArray

wavelength() → Dataset | None[source]

Read Wavelength CKD.

Returns:

parameters of the SPEXone Wavelength CKD

Return type:

xarray.Dataset

pyspex.dem_io module

Contains the class DEMio to read SPEXone CMV4000 detector data.

class pyspex.dem_io.DEMio(flname: str)[source]

Bases: object

Read SPEXone DEM output.

Parameters:

flname (str) – filename with header or binary data of DEM measurement

Examples

Read data from a SPEXone DEM binary file:

> dem = DEMio(dem_file)
> img_hk = dem.get_sci_hk()
> img_data = dem.get_data()
property exp_control: tuple

(inte_sync, exp_dual, exp_ext).

Register address: 41

Type:

Exposure time control parameters

exp_time(t_mcp: float = 1e-07) → float[source]

Return pixel exposure time [s].

fot_time(t_mcp: float = 1e-07) → float[source]

Return frame overhead time [s].

frame_period(n_coad: int = 1) → float[source]

Return frame period [s].

get_data(numlines: int | None = None) → ndarray[source]

Return data of a detector frame (numpy uint16 array).

Parameters:

numlines (int, optional) – Provide number of detector rows when no headerfile is present

Returns:

data of a detector frame, dtype np.uint16

Return type:

numpy.ndarray

get_sci_hk() → ndarray[source]

Return Science telemetry.

A subset of MPS and housekeeping parameters.

Return type:

numpy.ndarray

property hdr: ndarray | None

Return DEM header as numpy compound array.

property lvds_clock: bool

enable).

Register address: 82

Type:

Return flag for LVDS clock (0

Type:

disable, 1

property number_channels: int

Return number of LVDS channels used.

property number_lines: int

Return number of lines (rows).

Register address: [1, 2]

property offset: int

Return digital offset including ADC offset.

Register address: [100, 101]

property pga_gain: float

Return PGA gain (Volt).

Register address: 102

pll_control() → tuple[source]

Return PLL control parameters: pll_range, pll_out_fre, pll_div.

PLL_range: range (0 or 1) PLL_out_fre: output frequency (0, 1, 2 or 5) PLL_div: 9 (10 bit) or 11 (12 bit)

Register address: 116

rot_time(t_mcp: float = 1e-07) → float[source]

Return image read-out time [s].

property temp_detector: int

Return detector temperature as raw counts.

Notes

Uncalibrated conversion: ((1184 - 1066) * 0.3 * 40 / 40Mhz) + offs [K]

pyspex.dem_io.img_sec_of_day(img_sec: ndarray, img_subsec: ndarray, img_hk: ndarray) → tuple[datetime, float | Any][source]

Convert Image CCSDS timestamp to seconds after midnight.

Parameters:

  • img_sec (numpy array (dtype='u4')) – Seconds since 1970-01-01 (or 1958-01-01)

  • img_subsec (numpy array (dtype='u2')) – Sub-seconds as (1 / 2**16) seconds

  • img_hk (numpy array) – DemHK telemetry packages

Returns:

reference day: datetime, sec_of_day: numpy.ndarray

Return type:

tuple

pyspex.egse_db module

Collection of routines to access EGSE data generated by ITOS.

pyspex.egse_db.add_egse_data(args: argparse.Namespace) → None[source]

Write EGSE records of a measurement to a level-1A product.

pyspex.egse_db.create_egse_db(args: argparse.Namespace) → None[source]

Write EGSE data to HDF5 database.

pyspex.hkt_io module

Contains the class HKTio to read PACE HKT products.

class pyspex.hkt_io.HKTio(filename: Path)[source]

Bases: object

Class to read housekeeping and navigation data from PACE-HKT products.

Parameters:

filename (Path) – name of the PACE HKT product

Notes

This class has the following methods:

- reference_date -> datetime
- set_reference_date()
- coverage() -> tuple[datetime, datetime]
- housekeeping(instrument: str) -> tuple[np.ndarray, ...]
- navigation() -> dict
coverage() → tuple[datetime, datetime][source]

Return data coverage.

housekeeping(instrument: str = 'spx') → tuple[ndarray, ...][source]

Get housekeeping telemetry data.

Parameters:

instrument ({'spx', 'oci', 'harp', 'sc'}, default='spx') – name of PACE instrument: ‘harp’: HARP2, ‘oci’: OCI, ‘sc’: spacecraft, ‘spx’: SPEXone.

Notes

Current implementation only works for SPEXone.

navigation() → dict[source]

Get navigation data.

property reference_date: datetime

Return reference date of all time_of_day variables.

set_reference_date() → None[source]

Set reference date of current PACE HKT product.

pyspex.hkt_io.check_coverage_nav(l1a_file: Path, xds_nav: xr.Dataset) → None[source]

Check time coverage of navigation data.

Parameters:

  • l1a_file (Path) – name of the SPEXone level-1A product

  • xds_nav (xr.Dataset) – xarray dataset with PACE navigation data

pyspex.hkt_io.read_hkt_nav(hkt_list: list[Path, ...]) → xr.Dataset[source]

Read navigation data from one or more HKT products.

Parameters:

hkt_list (list[Path, ...]) – list of PACE-HKT products collocated with SPEXone measurements

Returns:

xarray dataset with PACE navigation data

Return type:

xr.Dataset

pyspex.lv0_io module

pyspex.lv1_args module

pyspex.lv1_gse module

Collect EGSE/OGSE data and/or add this to a SPEXone Level-1A product.

class pyspex.lv1_gse.LV1gse(l1a_file: str)[source]

Bases: object

Adds EGSE/OGSE data to a SPEXone Level-1A product.

Parameters:

l1a_file (str) – Name of the Level-1A product

check_egse(egse_data: ndarray) → None[source]

Check consistency of OGSE/EGSE information during measurement.

close() → None[source]

Close all resources (currently a placeholder function).

set_attr(name: str, value: Any) → None[source]

Add attribute to group ‘gse_data’.

Parameters:

  • name (str) –

  • value (anything(?)) –

write_attr_act(angle: float, illumination: float | None = None) → None[source]

Add act rotation angle as a group attribute.

Parameters:

  • angle (float) –

  • illumination (float) –

write_attr_alt(angle: float, illumination: float | None = None) → None[source]

Add altitude rotation angle as a group attribute.

Parameters:

  • angle (float) –

  • illumination (float) –

write_attr_polarization(aolp: float, dolp: float) → None[source]

Add polarization parameters AoLP & DoLP as group attributes.

Parameters:

  • aolp (float) – Angle of linear polarization

  • dolp (float) – Degree of linear polarization

write_egse(egse_time: ndarray, egse_data: ndarray, egse_attrs: dict) → None[source]

Add EGSE parameters.

Parameters:

  • egse_time (ndarray) –

  • egse_data (ndarray) –

  • egse_attrs (dict) –

write_reference_diode(ref_time: ndarray, ref_data: ndarray, ref_attrs: dict) → None[source]

Add data measured by the reference diode during the measurement.

Parameters:

  • ref_time (ndarray) –

  • ref_data (ndarray) –

  • ref_attrs (dict) – fid[‘/ReferenceDiode/ref_diode’].__dict__

write_reference_signal(signal: ndarray, stdev: ndarray) → None[source]

Write reference detector signal and variance.

Parameters:

  • signal (float) – Mean of signal level measured during the measurement

  • stdev (float) – standard deviation of signal level measured during the measurement

Notes

Used for non-linearity measurements.

write_viewport(viewport: int) → None[source]

Add/update which viewports are illuminated.

Parameters:

viewport (int) –

write_wavelength_monitor(xds_wav_mon: xr.Dataset) → None[source]

Add wavelength monitoring data of the Avantas fibre-spectrometer.

Parameters:

xds_wav_mon (xarray::Dataset) – Contains xarray::DataArrays ‘signal’, ‘wavelength’, ‘wav_time’

pyspex.lv1_io module

pyspex.ogse_db module

Collect OGSE data in a database.

This module contain routines to read reference diode measurements and wavelength monitor data. These data are supposed to be written to a HDF5 database. From these database selected data can be added to a SPEXone Level-1a product.

pyspex.ogse_db.add_ogse_ref_diode(ref_db: Path, l1a_file: Path) → None[source]

Select reference data taken during a measurement and add to a L1A product.

pyspex.ogse_db.add_ogse_wav_mon(ref_db: Path, l1a_file: Path) → None[source]

Select reference data taken during a measurement and add to a L1A product.

pyspex.ogse_db.read_ref_diode(ogse_dir: Path, file_list: list, verbose: bool = False) → Dataset[source]

Read reference diode data into a xarray.Dataset.

(input: comma separated values).

pyspex.ogse_db.read_wav_mon(ogse_dir: Path, file_list: list, verbose: bool = False) → Dataset[source]

Read wavelength monitor data into a xarray.Dataset.

(input comma separated values).

pyspex.ogse_dolp module

Defines the spectral dependent DolP of the Moxtek polarizer.

pyspex.ogse_dolp.gsfc_polarizer() → Dataset[source]

Define table for spectral dependent DolP.

pyspex.ogse_grande module

Defines the Grande spectrum for a given number of lamps, used at NASA GSFC.

pyspex.ogse_grande.grande_spectrum(n_lamps: int) → Dataset[source]

Define Grande spectrum for a given number of lamps.

pyspex.ogse_helios module

Defines the Helios spectrum, used at SRON.

pyspex.ogse_helios.helios_spectrum() → Dataset[source]

Define Helios spectrum.

pyspex.ogse_laser module

Read settings of the OPO laser used at NASA GSFC.

The OPO laser is used for ISRF and stray-light calibration measurements.

pyspex.ogse_laser.read_gse_excel(gse_dir: Path, target_cwl: str) → Dataset | None[source]

Return GSE info on central wavelength, line-width and laser radiance.

Parameters:

  • target_cwl (str) – Target laser wavelength as provided in the filename

  • gse_dir (Path) – Name of folder with the Excel file

pyspex.tif_io module

Contains the class TIFio to read simulated SPEXone measurements.

pyspex.tlm module

SPXtlm can read telemetry house-keeping data from SPEXone.

class pyspex.tlm.SPXtlm[source]

Bases: object

Access/convert parameters of SPEXone Science telemetry data.

Notes

This class has the following methods:

- set_coverage(coverage: tuple[datetime, datetime] | None) -> None
- hk_hdr() -> np.ndarray | None
- hk_tlm() -> np.ndarray | None
- hk_tstamp() -> np.ndarray | None
- sci_hdr() -> np.ndarray | None
- sci_tlm() -> np.ndarray | None
- sci_tstamp() -> np.ndarray | None
- images() -> tuple | None
- reference_date() -> datetime
- time_coverage_start() -> datetime
- time_coverage_end() -> datetime
- from_hkt(flnames: Path | list[Path], *,
           instrument: str | None = None, dump: bool = False) -> None
- from_lv0(flnames: Path | list[Path], *,
           file_format: str, tlm_type: str | None = None,
           debug: bool = False, dump: bool = False) -> None
- from_l1a(flname: Path, *, tlm_type: str | None = None) -> None
- set_selection(mode: str) -> None
- gen_l1a(config: dataclass, mode: str) -> None
- convert(key: str, tm_type: str = 'both') -> np.ndarray
- units(key: str) -> str
convert(key: str, tm_type: str = 'both') → ndarray[source]

Convert telemetry parameter to physical units.

Parameters:

  • key (str) – Name of telemetry parameter

  • tm_type ({'hk', 'sci', 'both'}, default 'both') – Default is to check if key is present in sci_tlm else hk_tlm

Return type:

np.ndarray

from_hkt(flnames: Path | list[Path], *, instrument: str | None = None, dump: bool = False) → None[source]

Read telemetry data from a PACE HKT product.

Parameters:

  • flnames (Path | list[Path]) – list of PACE_HKT filenames (netCDF4 format)

  • instrument ({'spx', 'sc', 'oci', 'harp'}, optional) –

  • dump (bool, default=False) – dump header information of the telemetry packages @1Hz for debugging purposes

from_l1a(flname: Path, *, tlm_type: str | None = None) → None[source]

Read telemetry data from SPEXone Level-1A product.

Parameters:

  • flname (Path) – name of one SPEXone Level-1A product

  • tlm_type ({'hk', 'sci', 'all'}, optional) – select type of telemetry packages

from_lv0(flnames: Path | list[Path], *, file_format: str, tlm_type: str | None = None, debug: bool = False, dump: bool = False) → None[source]

Read telemetry data from SPEXone Level-0 product.

Parameters:

  • flnames (Path | list[Path]) – list of CCSDS filenames

  • file_format ({'raw', 'st3', 'dsb'}) – type of CCSDS data

  • tlm_type ({'hk', 'sci', 'all'}, optional) – select type of telemetry packages. Note that we allways read the complete Level-0 producs.

  • debug (bool, default=False) – run in debug mode, read only packages heades

  • dump (bool, default=False) – dump header information of the telemetry packages @1Hz for debugging purposes

gen_l1a(config: dataclass, mode: str) → None[source]

Generate a SPEXone Level-1A product.

property hk_hdr: ndarray | None

Return CCSDS header data of telemetry packages @1Hz.

property hk_tlm: ndarray | None

Return telemetry packages @1Hz.

property hk_tstamp: ndarray | None

Return timestamps of telemetry packages @1Hz.

property images: tuple[ndarray, ...] | None

Return image-frames of Science telemetry packages.

l1a_file(config: dataclass, mode: str) → Path[source]

Return filename of Level-1A product.

Parameters:

  • config (dataclass) – Settings for the L0->l1A processing.

  • mode ({'all', 'full', 'binned'}) – Select Science packages with full-frame image or binned images

Returns:

Filename of Level-1A product.

Return type:

Path

Notes

=== Inflight === L1A file name format, following the NASA … naming convention:

PACE_SPEXONE[_TTT].YYYYMMDDTHHMMSS.L1A[.Vnn].nc

where

TTT is an optional data type (e.g., for the calibration data files) YYYYMMDDTHHMMSS is time stamp of the first image in the file Vnn file-version number (omitted when nn=1)

for example (file-version=1):

[Science Product] PACE_SPEXONE.20230115T123456.L1A.nc [Calibration Product] PACE_SPEXONE_CAL.20230115T123456.L1A.nc [Dark science Product] PACE_SPEXONE_DARK.20230115T123456.L1A.nc

=== OCAL === L1A file name format:

SPX1_OCAL_<msm_id>[_YYYYMMDDTHHMMSS]_L1A_vvvvvvv.nc

where

msm_id is the measurement identifier YYYYMMDDTHHMMSS is time stamp of the first image in the file vvvvvvv is the git-hash string of the pyspex repository

property reference_date: datetime

Return date of reference day (tzone aware).

property sci_hdr: ndarray | None

Return CCSDS header data of Science telemetry packages.

property sci_tlm: ndarray | None

Return Science telemetry packages.

property sci_tstamp: ndarray | None

Return timestamps of Science telemetry packages.

set_coverage(coverage: tuple[datetime, datetime] | None) → None[source]

Store or update the class attribute coverage.

set_selection(mode: str) → None[source]

Obtain image and housekeeping dimensions.

Parameters:

mode ({'full', 'binned', 'all'}) –

property time_coverage_end: datetime

Return a string for the time_coverage_end.

property time_coverage_start: datetime

Return a string for the time_coverage_start.

static units(key: str) → str[source]

Obtain units of converted telemetry parameter.

Parameters:

key (str) – Name of telemetry parameter

Return type:

str

pyspex.version module

Provide access to the software version as obtained from git.

pyspex.version.pyspex_version(full: bool = False, githash: bool = False) → str[source]

Return the software version as obtained from git.

Module contents

This is the SRON Python package pyspex.

It contains software to read PACE HKT products and SPEXone Level-0 products, and read/write SPEXone Level-1A products.