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A module for calculation of the geomagnetic K-Index from horizontal geomagnetic components.
This module uses the Finnish Meteorological Institute (FMI) method, details of which can be found here:
In a nutshell, this module takes horizontal geomagnetic components like this:
... and calculates the K-Index:
Assuming you have 4 days of geomagnetic data in the following format:
Times = array of datetime objects in second bins.
Bx, By, Bz = arrays of geomagnetic data in second bins.
First, convert the Times array into second floats:
>>> Times_float = Time2Float(Times)
Now convert all of the data to minute bins:
>>> minute_time, minute_bx, minute_by, minute_bz = MinuteBin(Times_float, Bx, By, Bz)
To get the K-Index for these 4 days:
>>> k_index, k_time, order = KIndexSuperCalc(minute_time, minute_bx, minute_by, n)
where n is the maximum threshold for a K9 event (dependent on latitude).
NOTE: The first few values in the array k_index are likely to be inaccurate. This is because of the way the K-Index is calculated. It is safest to dismiss the first 8 calculated K-Index values.
To plot the K-Index:
>>> KIndexPlotter(k_index[8:], k_time[8:], m)
where m is the figure number.
To install, type
pip install k_index_calculator
Written by Sean Blake in Trinity College Dublin, 2014-2016
Email: [email protected]
GITHUB: https://github.com/TerminusEst
Uses the MIT license.
Assuming you have 4 days of geomagnetic data in the following format:
minute_time = array of datetime objects in minute bins.
minute_bx, minute_by, minute_bz = arrays of geomagnetic data in minute bins.
Step 1
For each 3-hour block in the horizontal geomagnetic components, the max variation is found. This is then compared to the following table to get an initial K-index:
K-Index Value | nt Variation Range |
---|---|
0 | (0-5)*(n/500) |
2 | (10-20)*(n/500) |
3 | (20-40)*(n/500) |
4 | (40-70)*(n/500) |
5 | (70-120)*(n/500) |
6 | (120-200)*(n/500) |
7 | (200-330)*(n/500) |
8 | (330-500)*(n/500) |
9 | (500+)*(n/500) |
where n is the maximum threshold for a K9 event (this is dependent on geomagnetic latitude). This is calculated using the KIndex function.
Step 2
An estimation for the solar quiet or solar regular curve is calculated. This is calculated using the FMISmooth function, which is dependent on the preliminary K-Index.
Step 3
This solar quiet estimation is smoothed (SrSmooth), and subtracted from both horizontal components (Subtracted).
"Bx Component and Sr Curve"
Step 4 Steps 1-2 are repeated twice more with the reduced data to get a second and then final K-Index.
All of these steps can be combined in one call of KIndexSuperCalc. ##Functions List
KIndexSuperCalc
- Calculates the K-index using the FMI method.
KIndexPlotter
- Plots K-Index values in a nice Bar Plot
Time2Float
- Converts datetime object or array of datetime objects to floats.
Float2Time
- Converts float or array of floats to datetime objects.
MinuteBin
- Bin second data into minutes.
KIndex
- Calculate K-Index according to the FMI Method.
FMISmooth
- Calculates the Solar Regular (Sr) curve according to the FMI Method.
SrSmooth
- Smooths the solar regular curves.
Subtracted
- Subtracts the smoothed solar regular curves from the minute binned data.
KIndexBarColor -Colours K-index bar plot so it looks nice.