Project: s41467-024-44907-x | Function: get_mating (python)

system: You are an expert Python programmer implementing algorithms from scientific papers.
Complete the masked function based on the algorithm description.
Follow Python best practices and maintain consistent code style.
Return **only** the complete Python function code.

user: Complete this Python function:

**DESCRIPTION:** Calculate mating probability based on genotype, sex, and fitness costs associated with gene drive and anti-drive alleles

**KEY TERMS:** {
  "mating_probability": "baseline mating probability",
  "MATING_MOD": "genotype-specific mating modifier",
  "intersex": "sterile intersex phenotype",
  "NON_FUNCTIONAL": "sterile genotypes"
}

**CONTEXT CODE:**         # MASKED: Initialize individual mosquito agent with genotype, sex, and calculate survival probabilities for different life stages based on gene drive and anti-drive alleles implementation
        raise NotImplementedError("This function is masked for testing purposes.")

    def get_genotype(self):
        '''Get the full genotype at both loci

        Returns
           genotype (str)
               The first two chars are the dsx locus, the last the antidote

        Examples
        >>> i.get_genotype() # wild-type
        WWWW
        >>> i.get_genotype() # hom. drive, het. antidote
        DDAW
        >>> i.get_genotype() # het. drive, hom. antidote
        DWAA
        '''
        gt = ''
        for genotype in (self.genotype1, self.genotype2):
            if len(genotype) == 1:
                gt += list(genotype)[0]
                gt += list(genotype)[0]
            else:
                gt += ''.join(sorted(genotype))
        return gt

    def _is_intersex(self):
        if self.p['DRIVE'] in self.genotype1 and (self.nucl_from_father and self.nucl_from_mother):
            intersex = 0
        elif self.p['DRIVE'] in self.genotype1 and self.nucl_from_father and self.sex == 'f':
            intersex = get_rvs('norm', (self.p['INTERSEX_NUCL_FROM_FATHER']['loc'],
                                        self.p['INTERSEX_NUCL_FROM_FATHER']['scale']))
        elif self.p['DRIVE'] in self.genotype1 and self.nucl_from_mother and self.sex == 'f':
            intersex = get_rvs('norm', (self.p['INTERSEX_NUCL_FROM_MOTHER']['loc'],
                                        self.p['INTERSEX_NUCL_FROM_MOTHER']['scale']))
        else:
            intersex = 0
        if random.random() <= intersex:
            return True
        return False

    def _mating_probability(self):
        if self.sex == 'm':
            mating_probability = self.p['MATING_PROBABILITY_MALE']
        else:
            mating_probability = self.p['MATING_PROBABILITY']
        return mating_probability * self.p['MATING_MOD'][self.sex
                ].get(self.get_genotype(), 1)

    def get_mating(self):
        '''Generate the probability that this individual will mate

        Returns
            mating (bool)
               Wether the individual will mate

        The decision is based on sex, genotype and intersex phenotype
        '''
        # MASKED: Calculate mating probability based on genotype, sex, and fitness costs associated with gene drive and anti-drive alleles implementation
        raise NotImplementedError("This function is masked for testing purposes.")

    def deposes_eggs(self, modifier):
        '''Generate the probability that this individual will depose eggs

        Args:
            modifier (float)
               Modifier for the eggs deposition modifier

        Returns
            deposes (bool)
               Wether the individual will depose eggs

        The decision is based on sex and modifier
        '''
        if self.sex == 'm':
            return None
        elif random.random() <= self.p['EGG_DEPOSITION_PROBABILITY'] * modifier:
            return True
        return False

    def change_age(self, time_step):
        '''Increase the age of the individual

        As a result it may change its stage (i.e. egg -> larva)

        Args:
            time_step (float)
                Increase in age, in days
        '''
        self.age += time_step
        if self.stage == 'egg' and self.hatching and self.age >= self.time_to_hatch:
            self.stage = 'larva'
        elif self.stage == 'larva' and self.larva and self.age >= self.time_to_pupa:
            self.stage = 'pupa'
        elif self.stage == 'pupa' and self.pupa and self.age >= self.time_to_maturation:
            self.age = 0
            self.stage = 'adult'

    def will_develop(self):
        '''Will this individual develop into an adult?

        Returns:
           will_develop (bool)
               Wether the individual will eventually develop into an adult
        '''
        if self.stage == 'egg' and not self.hatching:
            return False
        elif self.stage == 'larva' and not self.larva:
            return False
        else:
            return True

    def is_alive(self):
        '''Is this individual still alive?

        Based on age, stage and development probabilities

        Returns:
           is_alive (bool)
               Wether the individual is still alive
        '''
        if self.stage == 'adult' and self.age > self.death:
            return False
        elif self.stage == 'egg' and not self.hatching:
            return False
        elif self.stage == 'larva' and not self.larva:
            return False
        elif self.stage == 'pupa' and not self.pupa:
            return False
        else:
            return True

    def _mendelian(self, genotype):
        if random.random() < 0.5:
            return sorted(genotype)[0]
        else:
            return sorted(genotype)[1]

    def form_gamete1(self, ):
        '''Form a gamete for locus 1 (dsx)

        If het. DRIVE homing may happen;
        the genotype at locus 2 may block homing

        Returns:
            genotype (str)
                Genotype at locus 1 for this gamete

        Example:


Complete the function implementation replacing "raise NotImplementedError".