import os
from collections import Counter

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

def linesplit(line):
    """
    Splits line of file into useful components.

    Returns (dm, pulse width, originating filename).
    """

    dm, line = line.split("pc/cc")
    dm = int(dm)
    pw, fname = line.split(" s ")
    pw = float(pw)
    fname = fname.strip().removesuffix("_injected")
    return (dm, pw, fname)

def updateDic(lines, dic):
    """
    Processes a list of lines and adds them to given dictionary in-place.
    """

    for line in lines:
        dm, pw, fname = linesplit(line)
        dic["file"].append(fname)
        dic["dm"].append(dm)
        dic["pulseWidth"].append(pw)

injectedDic = {
    "file" : [],
    "dm" : [],
    "pulseWidth" : []
}

detectedDic = {
    "file" : [],
    "dm" : [],
    "pulseWidth" : []
}

#load injected data into dataframe
with open(os.path.join(".","out","2025-07-31T17-25-54.txt"), "r") as file:
    lines = file.readlines()
    updateDic(lines, injectedDic)

injections = pd.DataFrame(data=injectedDic) #this is our main object for injection data

#load detection data into dataframe
with open(os.path.join(".","out","plotOut.txt"), "r") as file:
    lines = file.readlines()
    updateDic(lines, detectedDic)

detections = pd.DataFrame(data=detectedDic) #this is our main object for detection data

#define summary printing for multiple steps
def summary(stage):
    print(f"Summary Stage {stage}")
    print(f"Number of files injected:        {len(Counter(injections['file']))}")
    print(f"Number of files with detections: {len(Counter(detections['file']))}")
    print("=========================")
    print(f"Number of pulses injected: {len(injections['dm'])}")
    print(f"Number of pulses detected: {len(detections['dm'])}")
    print("=========================")
    print(f"File ratio:      {round(len(Counter(detections['file']))/len(Counter(injections['file'])), 3)}")
    print(f"Detection ratio: {round(len(detections['dm'])/len(injections['dm']), 3)}")
    print("=========================")

#print initial summary
summary(1)

#many files contained pulsar bursts, so we filter those out via DM
minDM = (10**2.5) * 0.95 #as per signal generation, plus a bit of wiggle room
print(f"Filtering out pulsars (DM below {int(minDM)}...)")
detections = detections[detections['dm'] > minDM]
summary(2)

#Let's do detection matching! Yaaaay!
#What detections line up to which injections? This will determine which ones got missed entirely.
#Define some kind of epsilon for DM and pulse width; if detection is within epsilon in both DM and PW we can match it.
dmEps = 0.05
pwEps = 0.2
#and define an auxiliary array of bools for injections containing the "is matched?" information.
isMatched = [False] * len(injections['dm'])