#!/usr/bin/Rscript

args <- commandArgs(TRUE);
tag <- args[1];
file_prefix <- args[2];
title <- args[3];

data <- read.csv(file("stdin"));
times <- data$EPOCH;
clap <- data$CLAP;
psap <- data$PSAP;

weighting_function <- function(values) {
    #q <- quantile(values, probs=c(0.05, 0.95), na.rm=TRUE);
    #w <- (values - q[1]) / (q[2] - q[1]);
    #w[is.finite(w) & (w < 0)] <- 0;
    #w[is.finite(w) & (w > 0)] <- 1;
    #w[is.finite(values) & values < 0] <- 0;
    #w <- w * 0.9 + 0.1;

    w <- 1 / (2*sqrt( (0.05)^2 + (0.024 / values)^2 ));

    w[!is.finite(w)] <- 0;

    return (w);
}

# Use the least weight between the two
weights <- pmin( weighting_function(clap), weighting_function(psap) );

selected_data <- sample(length(clap), length(clap) * 10, replace=TRUE, prob=weights);
times <- times[selected_data];
clap <- clap[selected_data];
psap <- psap[selected_data];



source("code/output_fits.r");

# Currently disabled: use the fully filtered PCA data for distribution generation
#psap <- result$pcafilter$matrix[,1];
#clap <- result$pcafilter$matrix[,2];

source("code/output_distributions.r");