library(reticulate)
use_python("/usr/local/bin/python3")
py_config()
levls <- read.table("/Users/npetraco/latex/class/fos705/Applied_Bayes/R/bayes705/tests/Dnest_Bullard_spike_test/levels.txt", header = F )
sampls <- read.table("/Users/npetraco/latex/class/fos705/Applied_Bayes/R/bayes705/tests/Dnest_Bullard_spike_test/sample.txt", header = F )
sampl.info <- read.table("/Users/npetraco/latex/class/fos705/Applied_Bayes/R/bayes705/tests/Dnest_Bullard_spike_test/sample_info.txt", header = F )
colnames(levls) <- c("log_X", "log_likelihood", "tiebreaker", "accepts", "tries", "exceeds", "visits")
colnames(sampls) <- c("alpha", "beta")
colnames(sampl.info) <- c("level assignment", "log likelihood", "tiebreaker", "ID")
dim(levls)
dim(sampls)
dim(sampl.info)
logl_levels <- levls[,c(2,3)] # logl, tiebreaker
logl_samples <- sampl.info[,c(2,3,4)] # logl, tiebreaker, id
# Find sandwiching level for each sample
# sandwich = sample_info[:,0].copy().astype('int')
# for i in range(0, sample_info.shape[0]):
# while sandwich[i] < levels_orig.shape[0]-1 and logl_samples[i] > logl_levels[sandwich[i] + 1]:
# sandwich[i] += 1
sandwichh <- sampl.info[,1]
max.lev <- dim(levls)[1] - 1
for(i in 1:length(sandwichh)){
while((sandwichh[i] < max.lev) & (logl_samples[i,1] > logl_levels[sandwichh[i]+1,1])){
sandwichh[i] <- sandwichh[i] + 1
}
}
plot(sampl.info[,1], sandwichh)
sfpy <- read.csv("/Users/npetraco/latex/class/fos705/Applied_Bayes/R/bayes705/tests/Dnest_Bullard_spike_test/csvfile2.csv",header = F)[,1]
head(sfpy)
#sum(sfpy - sampl.info[,1])
plot(sampl.info[,1], sfpy)
head(sandwichh-1)
sfpy - (sandwichh-1)
sandwichh[64]
logl_samples[64,1] > logl_levels[sandwichh[64]+1,1]
# Try to understand what Murry is doing in analysis.py
np <- import("numpy")
dn4 <- import("dnest4")
np$array(r_to_py(levls))
dn4$analysis$interpolate_samples(levels = r_to_py(levls),
sample_info = r_to_py(sampl.info),
resample = F)
os <- import("os")
os$getcwd()
backend <- dn4$backends$CSVBackend("/Users/npetraco/latex/class/fos705/Applied_Bayes/R/bayes705/tests/Dnest_Bullard_spike_test/")
backend$levels
head(levls)
head(sampl.info)
levls
py_run_file("tests/Dnest_Bullard_spike_test/analysis_expts1.py")
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