Get LEXI Data (lexi.get_lexi_data)
- lexi_xray.lexi.get_lexi_data(time_range=None, time_zone='UTC', time_pad=300, data_clip=True, verbose=True, spc_prams=False, return_data_type='merged', spc_prams_kwargs={})[source]
Function to get LEXI data from the CDAweb website (eventually). Currently the code is set up to download the data from the GitHub repository. This function will be updated to download the data from the CDAweb website once the data is available and hosted on the website.
Parameters
- time_rangelist, required
Time range to consider. [start time, end time]. Times can be expressed in the following formats:
A string in the format ‘YYYY-MM-DDTHH:MM:SS’ (e.g. ‘2022-01-01T00:00:00’)
A datetime object
A float in the format of a UNIX timestamp (e.g. 1640995200.0)
This time range defines the time range of the ephemeris data and the time range of he LEXI data.
Note
The endpoints are inclusive (the end time is a closed interval); this is because he time range slicing is done with pandas, and label slicing in pandas is inclusive.
- time_zonestr, optional
The timezone of the time range of interest. Default is “UTC”
- verbosebool, optional
If True, print messages. Default is True
- time_padfloat, optional
Time padding in seconds to add to the time range value. Default is 300 seconds
- data_clipbool, optional
If True, clip the data to the original time range specified, else, keep the entire dataframe. Default is True
- spc_pramsbool, optional
If True, get the spacecraft parameters for the same time range as LEXI data. Default is False
- return_data_typestr, optional
Type of data to return. This parameter is only used when spc_prams is True. This defines what kind of dataframes to return. Valid options are:
‘merged’: Merged LEXI and spacecraft parameters dataframes using the ‘pd.merge_asof’ function with a tolerance of 1 minute and direction of ‘nearest’. Default option.
‘lexi’: LEXI data only
‘spc_prams’: Spacecraft parameters data only
‘both’: Both LEXI and spacecraft parameters dataframes
‘all’: All three dataframes
Default is ‘merged’
- spc_prams_kwargsdict, optional
Keyword arguments to pass to the get_spc_prams function. Default is None. If None, then the default values of the get_spc_prams function are used.
Returns
- dfpandas DataFrame
LEXI data
- df_spc_pramspandas DataFrame
Spacecraft parameters data
- df_mergedpandas DataFrame
Merged LEXI and spacecraft parameters data
Example Usage
The following example shows how to use the get_lexi_data function to get LEXI data for a specific time range:
>>> from lexi_xray.lexi import get_lexi_data
>>> df_lexi = get_lexi_data( time_range=["2025-03-04 08:50:00", "2025-03-04 09:23:00"], verbose=True )
Jupyter Notebook Usage:
from lexi_xray.lexi import get_lexi_data df_lexi = get_lexi_data( time_range=["2025-03-04 08:50:00", "2025-03-04 09:23:00"], verbose=False ) print(df_lexi.head())
Downloading files from [95mdata/level_1c/cdf/1.0.0[00m on branch [92mstable[00m: A total of [1;92m1917[0m files found Files to download: [1;92m9[0m Downloading [96mlexi_payload_1741077968_26406_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741077968_26406_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741077968_26406_level_1c_1.0.0.cdf[00m Downloading [96mlexi_payload_1741078268_29290_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741078268_29290_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741078268_29290_level_1c_1.0.0.cdf[00m Downloading [96mlexi_payload_1741078869_2840_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741078869_2840_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741078869_2840_level_1c_1.0.0.cdf[00m Downloading [96mlexi_payload_1741079169_5198_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741079169_5198_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741079169_5198_level_1c_1.0.0.cdf[00m Downloading [96mlexi_payload_1741079469_9233_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741079469_9233_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741079469_9233_level_1c_1.0.0.cdf[00m Downloading [96mlexi_payload_1741079769_20852_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741079769_20852_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741079769_20852_level_1c_1.0.0.cdf[00m Downloading [96mlexi_payload_1741080069_25191_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741080069_25191_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741080069_25191_level_1c_1.0.0.cdf[00m Downloading [96mlexi_payload_1741080369_31310_level_1c_1.0.0.cdf[00m...
Saved [96mlexi_payload_1741080369_31310_level_1c_1.0.0.cdf[00m to [92mdownloaded_data/lexi_payload_1741080369_31310_level_1c_1.0.0.cdf[00m Epoch_unix ra_J2000_deg dec_J2000_deg Epoch_utc 2025-03-04 08:50:00+00:00 1741078200 233.365814 -23.028013 2025-03-04 08:50:00+00:00 1741078200 233.247787 -22.549011 2025-03-04 08:50:00+00:00 1741078200 229.612396 -24.492270 2025-03-04 08:50:00+00:00 1741078200 232.682541 -24.332512 2025-03-04 08:50:00+00:00 1741078200 228.622574 -23.796873