#bfastmonitor_cpu
This github repository contains scripts for using the python bfast algorithm in SEPAL.
NOTEBOOKS
- bfastmonitor_GPU_stack.ipynb
If you want to run over a big data set in one go, you may run this code on a timeseries data set.
- bfastmonitor_GPU.ipynb
This is a script for running over SEPAL time series tile directories within a time-series folder.
FROM TERMINAL
- bfastmonitor_GPU_stack.py -o [output_dir] -t [timeseries_dir]
You can run bfast_stack.py from the terminal, the terminal will prompt the user for parameters.
example: python3 bfast_stack.py -o Guyana -t ../../downloads/Time_series_2020-09-09_13-02-40/
example: python3 bfast_stack.py -o Australia -t /home/dven/downloads/Time_series_2020-09-09_13-02-40/
- bfastmonitor_GPU_array.sh
If you want to run bfastmonitor-GPU over folders in different folder locations, do multiple runs to test parameters etc. you may use this bash script. It calls bfastmonitor_GPU_stack_bash.py using parameters in bash arrays.
- bfastmonitor_GPU_stack_bash.py
Is called by bfastmonitor_GPU_array.sh.
PYTHON FUNCTIONS
- functions.py
Contains general functions.
- plotting_funcs.py
Contains functions for plotting.
- time_series.py
Contains the Timeseries Class.
- widgets.py
Contains the ipy widgets used in the notebooks.
TIF OUTPUTS
The scripts provide the following tif outputs
- breaks_indexed
Indexes of the breaks, base output of bfastmonitor_GPU. -1 denotes no break is found. -2 denotes absence of enough data to find breaks.
- breaks_binary
Presence of all breaks in 0 or 1.
- breaks_binary_negative
Presence of negative breaks 0 or 1.
- breaks_julian
Julian dates of breaks.
- breaks_julian_negative
Julian dates of negative breaks.
- magnitudes
All means of MOSUM process (deviation between model and data) floats.
- magnitudes_negative
Negative means of MOSUM process (deviation between model and data) floats.
- magnitudes_classified_result
COLORED Means of MOSUM process classified into 10 classes -999(no data), 1,2,3,4,5,6,7,8,9
# 1 = no change (mean +/- 1 standard deviation)
# 2 = negative small magnitude change (mean - 2 standard deviations)
# 3 = negative medium magnitude change (mean - 3 standard deviations)
# 4 = negative large magnitude change (mean - 4 standard deviations)
# 5 = negative very large magnitude change (mean - 4+ standard deviations)
# 6 = postive small magnitude change (mean + 2 standard deviations)
# 7 = postive medium magnitude change (mean + 3 standard deviations)
# 8 = postive large magnitude change (mean + 4 standard deviations)
# 9 = postive very large magnitude change (mean + 4+ standard deviations)
- magnitudes_classified
Same as above, but not colored