MPAS-JEDI
Functions | Variables
bootstrap_demo Namespace Reference

Functions

def bootstrap_test ()
 
def main ()
 

Variables

 clustsN = np.multiply(NOMINAL_GROUP_SIZE,np.ones(NOMINAL_NUMBER_OF_GROUPS,dtype=int))
 alternative way to initialize cluster sizes clustsStart.append(0) nremain = N_SUPER_SAMPLE while nremain > 0: clustN = int(max([np.around(NOMINAL_GROUP_SIZE + np.random.randn(1)*SIGMAN), 1.0])) if np.sum(clustsN) + clustN > N_SUPER_SAMPLE - NOMINAL_GROUP_SIZE/4: clustN = N_SUPER_SAMPLE - np.sum(clustsN) clustsN.append( clustN ) nremain = nremain - clustN ntotal = np.sum(clustsN) clustsEnd.append(ntotal) clustsStart.append(clustsEnd[-1]) More...
 
 delta = NOMINAL_GROUP_SIZE - \
 
list X1ClustsValues = []
 
dictionary X1ClustsStats = {}
 
 clustStats = su.calcStats(X1ClustsValues[ic])
 
 X1ClustsStatsDF = pd.DataFrame.from_dict(X1ClustsStats)
 
 aggClustStats = su.aggStatsDF(X1ClustsStatsDF)
 
list X2ClustsValues = []
 
dictionary X2ClustsStats = {}
 
 X2ClustsStatsDF = pd.DataFrame.from_dict(X2ClustsStats)
 
 statsCIClustSamples
 
 xVals = nBootSamples
 
 ny = nFuncs
 
int nx = 2
 
 fig = pu.setup_fig(nx, ny, inch_width=2.2)
 
 bootFunc = bootFuncs[ifunc]
 
string sampleAggStat = "Mean"
 
 ax1 = fig.add_subplot(ny, nx, nx*ifunc+1)
 
list plotVals = []
 
 lineVals = deepcopy(statsCIFullSamples[ifunc]['VALUE'])
 
 lineValsMin = deepcopy(statsCIFullSamples[ifunc]['LO'])
 
 lineValsMax = deepcopy(statsCIFullSamples[ifunc]['HI'])
 
 label
 
 color
 
 ls
 
 linewidth
 
 alpha
 
 c
 
 markersize
 
 lh
 
 fontsize
 
 labelsize
 
 minyval
 
 maxyval
 
 symmetric
 
 ax2 = fig.add_subplot(ny, nx, nx*ifunc+2)
 
 bins
 
string filename = 'cluster_bootstrap_test/comparison' \
 

Function Documentation

◆ bootstrap_test()

def bootstrap_demo.bootstrap_test ( )

Definition at line 18 of file bootstrap_demo.py.

Here is the caller graph for this function:

◆ main()

def bootstrap_demo.main ( )

Definition at line 333 of file bootstrap_demo.py.

Here is the call graph for this function:

Variable Documentation

◆ aggClustStats

bootstrap_demo.aggClustStats = su.aggStatsDF(X1ClustsStatsDF)

Definition at line 161 of file bootstrap_demo.py.

◆ alpha

bootstrap_demo.alpha

Definition at line 242 of file bootstrap_demo.py.

◆ ax1

bootstrap_demo.ax1 = fig.add_subplot(ny, nx, nx*ifunc+1)

Definition at line 220 of file bootstrap_demo.py.

◆ ax2

bootstrap_demo.ax2 = fig.add_subplot(ny, nx, nx*ifunc+2)

Definition at line 319 of file bootstrap_demo.py.

◆ bins

bootstrap_demo.bins

Definition at line 320 of file bootstrap_demo.py.

◆ bootFunc

bootstrap_demo.bootFunc = bootFuncs[ifunc]

Definition at line 208 of file bootstrap_demo.py.

◆ c

bootstrap_demo.c

Definition at line 253 of file bootstrap_demo.py.

◆ clustsN

bootstrap_demo.clustsN = np.multiply(NOMINAL_GROUP_SIZE,np.ones(NOMINAL_NUMBER_OF_GROUPS,dtype=int))

alternative way to initialize cluster sizes clustsStart.append(0) nremain = N_SUPER_SAMPLE while nremain > 0: clustN = int(max([np.around(NOMINAL_GROUP_SIZE + np.random.randn(1)*SIGMAN), 1.0])) if np.sum(clustsN) + clustN > N_SUPER_SAMPLE - NOMINAL_GROUP_SIZE/4: clustN = N_SUPER_SAMPLE - np.sum(clustsN) clustsN.append( clustN ) nremain = nremain - clustN ntotal = np.sum(clustsN) clustsEnd.append(ntotal) clustsStart.append(clustsEnd[-1])

note: always causes non-negligible difference in CI

Definition at line 114 of file bootstrap_demo.py.

◆ clustStats

bootstrap_demo.clustStats = su.calcStats(X1ClustsValues[ic])

Definition at line 149 of file bootstrap_demo.py.

◆ color

bootstrap_demo.color

Definition at line 235 of file bootstrap_demo.py.

◆ delta

bootstrap_demo.delta = NOMINAL_GROUP_SIZE - \

Definition at line 116 of file bootstrap_demo.py.

◆ fig

bootstrap_demo.fig = pu.setup_fig(nx, ny, inch_width=2.2)

Definition at line 205 of file bootstrap_demo.py.

◆ filename

string bootstrap_demo.filename = 'cluster_bootstrap_test/comparison' \

Definition at line 325 of file bootstrap_demo.py.

◆ fontsize

bootstrap_demo.fontsize

Definition at line 308 of file bootstrap_demo.py.

◆ label

bootstrap_demo.label

Definition at line 234 of file bootstrap_demo.py.

◆ labelsize

bootstrap_demo.labelsize

Definition at line 311 of file bootstrap_demo.py.

◆ lh

bootstrap_demo.lh
Initial value:
1 = ax1.legend(loc='best',fontsize=3,frameon=True,\
2  framealpha=0.4,ncol=2)

Definition at line 304 of file bootstrap_demo.py.

◆ lineVals

bootstrap_demo.lineVals = deepcopy(statsCIFullSamples[ifunc]['VALUE'])

Definition at line 225 of file bootstrap_demo.py.

◆ lineValsMax

bootstrap_demo.lineValsMax = deepcopy(statsCIFullSamples[ifunc]['HI'])

Definition at line 227 of file bootstrap_demo.py.

◆ lineValsMin

bootstrap_demo.lineValsMin = deepcopy(statsCIFullSamples[ifunc]['LO'])

Definition at line 226 of file bootstrap_demo.py.

◆ linewidth

bootstrap_demo.linewidth

Definition at line 237 of file bootstrap_demo.py.

◆ ls

bootstrap_demo.ls

Definition at line 236 of file bootstrap_demo.py.

◆ markersize

bootstrap_demo.markersize

Definition at line 255 of file bootstrap_demo.py.

◆ maxyval

bootstrap_demo.maxyval

Definition at line 314 of file bootstrap_demo.py.

◆ minyval

bootstrap_demo.minyval

Definition at line 314 of file bootstrap_demo.py.

◆ nx

int bootstrap_demo.nx = 2

Definition at line 203 of file bootstrap_demo.py.

◆ ny

bootstrap_demo.ny = nFuncs

Definition at line 202 of file bootstrap_demo.py.

◆ plotVals

bootstrap_demo.plotVals = []

Definition at line 222 of file bootstrap_demo.py.

◆ sampleAggStat

string bootstrap_demo.sampleAggStat = "Mean"

Definition at line 210 of file bootstrap_demo.py.

◆ statsCIClustSamples

bootstrap_demo.statsCIClustSamples
Initial value:
1 = su.bootStrapClusterFunc( \
2  X2ClustsStatsDF, X1ClustsStatsDF, \
3  n_samples = nBootSamples, \
4  statFunc = statFunc)

Definition at line 193 of file bootstrap_demo.py.

◆ symmetric

bootstrap_demo.symmetric

Definition at line 314 of file bootstrap_demo.py.

◆ X1ClustsStats

dictionary bootstrap_demo.X1ClustsStats = {}

Definition at line 143 of file bootstrap_demo.py.

◆ X1ClustsStatsDF

bootstrap_demo.X1ClustsStatsDF = pd.DataFrame.from_dict(X1ClustsStats)

Definition at line 153 of file bootstrap_demo.py.

◆ X1ClustsValues

list bootstrap_demo.X1ClustsValues = []

Definition at line 142 of file bootstrap_demo.py.

◆ X2ClustsStats

dictionary bootstrap_demo.X2ClustsStats = {}

Definition at line 167 of file bootstrap_demo.py.

◆ X2ClustsStatsDF

bootstrap_demo.X2ClustsStatsDF = pd.DataFrame.from_dict(X2ClustsStats)

Definition at line 177 of file bootstrap_demo.py.

◆ X2ClustsValues

list bootstrap_demo.X2ClustsValues = []

Definition at line 166 of file bootstrap_demo.py.

◆ xVals

bootstrap_demo.xVals = nBootSamples

Definition at line 201 of file bootstrap_demo.py.