from dataclasses import dataclass

@dataclass
class ConfusionMatrix:
    tp: int
    tn: int
    fp: int
    fn: int

    @property
    def p(self):
        return self.tp + self.fn

    @property
    def n(self):
        return self.fp + self.tn

    @property
    def pp(self):
        return self.tp + self.fp

    @property
    def pn(self):
        return self.fn + self.tn
    
    @property
    def pop(self):
        return self.tp + self.fp + self.tn + self.fn

    @property
    def tpr(self):
        return self.tp / self.p
    
    @property
    def fnr(self):
        return self.fn / self.p
    
    @property
    def fpr(self):
        return self.fp / self.n
    
    @property
    def tnr(self):
        return self.tn / self.n
    
    @property
    def ppv(self):
        return self.tp / self.pp
    
    @property
    def npv(self):
        return self.tn / self.pn
    
    @property
    def fdr(self):
        return self.fp / self.pp
    
    @property
    def fOr(self):
        return self.fn / self.pn
    
    @property
    def f1(self):
        return 2*self.tp / (2*self.tp + self.fp + self.fn)

    def report(self, title):
        return f"""\
{title}
  Population: {self.pop}
  Confusion Matrix:
              PPos PNeg
    Positive: {self.tp: 4} {self.fn: 4}
    Negative: {self.fp: 4} {self.tn: 4}
  Positive Predictive Value: {self.ppv:%}
  False Positive Rate: {self.fpr:%}
  F1 Score: {self.f1}
"""

# 19 fail runs with only eintr
# 5 fail runs with only other failures (1 of them precluded eintr)
# 1 fail run with both
# 9 pass runs
print(ConfusionMatrix(
    tp = 5 + 1,
    fp = 19,
    tn = 9,
    fn = 0,
).report("Overall, by runs:"))

print(ConfusionMatrix(
    tp = 0,
    fp = 19 + 1,
    tn = 9 + 4,
    fn = 0,
).report("eintr, by runs:"))

# 28 fail jobs with only eintr
# 28 fail jobs with only other failures
# 1 fail job with both
# 327 pass jobs from fail runs
# 144 pass jobs from pass runs
print(ConfusionMatrix(
    tp = 28 + 1,
    fp = 28,
    tn = 327 + 144,
    fn = 0,
).report("Overall, by jobs:"))

print(ConfusionMatrix(
    tp = 0,
    fp = 28 + 1,
    tn = 327 + 144 + 28,
    fn = 0,
).report("eintr, by jobs:"))