ana4Stats: Statistical analysis tools

probAna

probAna is used to derive simple probability maps for a set of simulations for one avalanche track. These maps show for each point in space the probability for a chosen parameter to exceed a given threshold. For example, it is possible to compute the probability map of an avalanche to exceed a peak pressure of 1kPa, but is also possible to chose other parameters and threshold values.

A set of multiple avalanche simulations is required to generate these maps. The simulations can be generated with com1DFA using a parameter variation, different release-, entrainment- or resistance scenarios. runScripts.runProbAna gives an example: avalanche simulations for the hockey topography are performed with varying release thickness. A probability map based on peak pressure is generated. The output is a raster file (.asc) with values ranging from 0-1. 0 meaning that no simulation exceeded the threshold in this point in space. 1 on the contrary means that all simulations exceeded the threshold. Details on this function, as for example required inputs can be found in: ana4Stats.probAna.

To run - example run scripts

An example on how to generate probability maps for avalanche simulations performed with com1DFA is given in runScripts.runProbAna, where for avaHockeyChannel simulations are performed with varying release thickness values ranging from 0.75 to 1.75 meters in steps of 0.05 meters. The resulting simulations are then used to generate the probability map with out3Plot.statsPlots.plotProbMap(). There is also the option to filter the simulations further - using the function in3Utils.fileHandlerUtils.getFilterDict() which generates a parameter dictionary for filtering according to the filter criteria set in the configuration file (ana4Stats/probAnaCfg.ini) of the ana4Stats.probAna function. In order to run this example:

  • first go to AvaFrame/avaframe

  • copy ana4Stats/probAnaCfg.ini to ana4Stats/local_probAnaCfg.ini

  • uncomment 'FILTER' section in local_probAnaCfg.ini and insert filter parameters if you want to first filter simulations

  • run:

    python3 runScripts/runProbAna.py
    
_images/avaHockeyChannel_probMap_lim1.0.png

Another example is given in runScripts.runProbAnaCom1DFA.py, but here only one parameter is varied at a time. Avalanche simulations are performed with the settings defined in the configuration file of com1DFA and in addition a parameter variation is performed according to the parameters set in ana4Stats/probAnaCfg.ini in the section PROBRUN. All the parameters set in PROBRUN are varied on at a time, i.e. simulations are performed for the standard settings of all parameters, except the one parameter to be varied, subsequently the other variations are performed. In the beginning of the script, filtering criteria for the probability maps can be set.

Theory

This point-wise probability is expressed by the relative frequency of avalanche peak flow field exceeding a certain threshold for a set of deterministic avalanche simulations derived from a range of input parameters (see [HBB19]).

getStats

In ana4Stats.getStats, functions that help to compute statistical properties of simulation results are gathered. ana4Stats.getStats.extractMaxValues() can be used to determine the maximum peak values of the simulation results. These values can then be plotted using the functions in out3Plot.statsPlots in order to visualise the statistics of a set of avalanche simulations. For further details on the specific functions, have a look at: ana4Stats.getStats.

To run

An example on how to use these statistical functions is given in runScripts.runStatsExample, where for avaHockeyChannel simulations are performed for two different release area scenarios and the release thickness is varied from 0.75 to 1.75 meters in steps of 0.05 meters. The resulting simulations are then analysed using the ana4Stats.getStats.extractMaxValues() function and plots are generated using the plotting routines from out3Plot.statsPlots . If in the configuration file ana4Stats/getStats.ini the flag aimec is set to True, additionally an ana3AIMEC: Aimec analysis is performed.

  • first go to AvaFrame/avaframe

  • copy ana4Stats/getStats.ini to ana4Stats/local_getStatsCfg.ini

  • uncomment 'FILTER' section in ana4Stats/local_getStatsCfg.ini and insert filter parameters if you want to first filter simulations

  • run:

    python3 runScripts/runStatsExample.py
    
_images/Scatter_pft_vs_pfv_dist_test.png

Fig. 24 Scatter plot of the hockey example with color-coded release thickness values.

_images/Scatterkde_pft_vs_pfv_dist_test.png

Fig. 25 Scatter plot of the hockey example including a marginal kde plot and color coded with release area scenario.