aegis_sim.parameterization.trait

  1class Trait:
  2    """Genetic trait
  3
  4    Contains data on traits encoded in the genome.
  5    """
  6
  7    def __init__(self, name, cnf, genarch_type, MODIF_GENOME_SIZE, start_position):
  8        def get(key):
  9            return getattr(cnf, f"G_{name}_{key}")
 10
 11        self.name = name
 12        self.start = start_position
 13
 14        # Relevant if genetic architecture is composite
 15        self.evolvable = get("evolvable")
 16        self.agespecific = get("agespecific")
 17        self.interpreter = get("interpreter")
 18        self.initgeno = get("initgeno")
 19        # Per-trait dominance coefficient h for diploid-to-haploid collapse.
 20        # None means "inherit global DOMINANCE_FACTOR". The architecture builds
 21        # a per-locus array from these values at init time.
 22        self.dominance = get("dominance")
 23
 24        # Relevant if genetic architecture is modifying
 25        self.initpheno = get("initpheno")
 26
 27        # Relevant under any genetic architecture
 28        self.lo = get("lo")
 29        self.hi = get("hi")
 30
 31        assert genarch_type in ("modifying", "composite")
 32
 33        if genarch_type == "composite":
 34
 35            # Determine the number of loci encoding the trait
 36            if self.evolvable:
 37                if self.agespecific is True:  # one locus per age
 38                    self.length = cnf.AGE_LIMIT
 39                elif self.agespecific is False:  # one locus for all ages
 40                    self.length = 1
 41                else:  # custom number of loci
 42                    self.length = self.agespecific
 43            else:  # no loci for a constant trait
 44                self.length = 0
 45
 46            self._validate()
 47
 48            # Infer positions in the genome
 49            # self.start = start
 50            # self.end = self.start + self.length
 51            # self.slice = slice(self.start, self.end)
 52
 53            # self.start = cnf.AGE_LIMIT * constants.starting_site(self.name)
 54            # self.end = self.start_position + cnf.AGE_LIMIT
 55
 56        elif genarch_type == "modifying":
 57            if name == "neut":
 58                self.length = MODIF_GENOME_SIZE
 59            else:
 60                self.length = 0
 61
 62        self.end = self.start + self.length
 63
 64        self.slice = slice(self.start, self.end)
 65
 66    def _validate(self):
 67        """Check whether input parameters are legal."""
 68        if not isinstance(self.evolvable, bool):
 69            raise TypeError
 70
 71        if not 0 <= self.initgeno <= 1:
 72            raise ValueError
 73
 74        if self.evolvable:
 75            # if not isinstance(self.agespecific, bool):
 76            #     raise TypeError
 77
 78            if self.interpreter not in (
 79                "uniform",
 80                "exp",
 81                "binary",
 82                "binary_exp",
 83                "binary_switch",
 84                "switch",
 85                "linear",
 86                "single_bit",
 87                "const1",
 88                "threshold",
 89            ):
 90                raise ValueError(f"{self.interpreter} is not a valid interpreter type")
 91
 92            if not 0 <= self.lo <= 1:
 93                raise ValueError
 94
 95            if not 0 <= self.hi <= 1:
 96                raise ValueError
 97
 98    def __len__(self):
 99        """Return number of loci used to encode the trait."""
100        return self.length
101
102    def __str__(self):
103        return self.name