Model

Key randomization functions in model.

assay_performed(params)

Number of days between collection and assay being performed.

Parameters:

Name	Type	Description	Default
params	AssayParams	assay parameters	required

Returns:

Type	Description
timedelta	Number of days.

Source code in src/snailz/model.py

def assay_performed(params: AssayParams) -> timedelta:
    """Number of days between collection and assay being performed.

    Parameters:
        params: assay parameters

    Returns:
        Number of days.
    """
    return timedelta(days=random.randint(0, params.delay))

assay_reading(params, specimen, treatment, performed)

Calculate individual assay reading.

Parameters:

Name	Type	Description	Default
params	AssayParams	assay parameters	required
specimen	object	specimen being assayed	required
treatment	str	"C" for control or "S" for sample	required
performed	date	date assay performed	required

Returns:

Type	Description
float	Reading value.

Source code in src/snailz/model.py

def assay_reading(
    params: AssayParams, specimen: object, treatment: str, performed: date
) -> float:
    """
    Calculate individual assay reading.

    Parameters:
        params: assay parameters
        specimen: specimen being assayed
        treatment: "C" for control or "S" for sample
        performed: date assay performed

    Returns:
        Reading value.
    """
    degradation = max(
        0.0, 1.0 - (params.degrade * (performed - specimen.collected).days)
    )
    if treatment == "C":
        base_value = 0.0
        stdev = params.rel_stdev
    elif specimen.is_mutant:
        base_value = params.mutant * degradation
        stdev = base_value * params.rel_stdev
    else:
        base_value = params.baseline * degradation
        stdev = base_value * params.rel_stdev

    return abs(random.gauss(base_value, stdev))

assay_specimens(params, specimens)

Generate list of specimens to be assayed.

Parameters:

Name	Type	Description	Default
params	AssayParams	assay parameters	required
specimens	BaseModel	all available specimens	required

Returns:

Type	Description
list	List of specimens (possibly containing duplicates).

Source code in src/snailz/model.py

def assay_specimens(params: AssayParams, specimens: BaseModel) -> list:
    """Generate list of specimens to be assayed.

    Parameters:
        params: assay parameters
        specimens: all available specimens

    Returns:
        List of specimens (possibly containing duplicates).
    """
    extra = random.choices(
        specimens.items,
        k=math.floor(params.p_duplicate_assay * len(specimens.items)),
    )
    subjects = specimens.items + extra
    random.shuffle(subjects)
    return subjects

days_to_next_survey(params)

Choose the number of days between surveys.

Parameters:

Name	Type	Description	Default
params	SurveyParams	specimen generation parameters	required

Returns:

Type	Description
timedelta	Days to the next survey.

Source code in src/snailz/model.py

def days_to_next_survey(params: SurveyParams) -> timedelta:
    """Choose the number of days between surveys.

    Parameters:
        params: specimen generation parameters

    Returns:
        Days to the next survey.
    """
    return timedelta(days=random.randint(1, params.max_interval))

image_noise(params, img, img_size)

Add noise effects to image.

Parameters:

Name	Type	Description	Default
img	Image	pristine image	required

Returns:

Type	Description
Image	Distorted image.

Source code in src/snailz/model.py

def image_noise(params: AssayParams, img: PilImage, img_size: int) -> PilImage:
    """Add noise effects to image.

    Parameters:
        img: pristine image

    Returns:
        Distorted image.
    """
    # Add uniform noise (not provided by pillow).
    for x in range(img_size):
        for y in range(img_size):
            noise = random.randint(-params.image_noise, params.image_noise)
            old_val = img.getpixel((x, y))
            assert isinstance(old_val, int)  # for type checking
            val = max(utils.BLACK, min(utils.WHITE, old_val + noise))
            img.putpixel((x, y), val)

    # Blur.
    img = img.filter(ImageFilter.GaussianBlur(BLUR_RADIUS))

    return img

machine_brightness(params)

Choose relative brightness of this machine's camera.

Parameters:

Name	Type	Description	Default
params	MachineParams	machine parameters	required

Returns:

Type	Description
float	Brightness level in that range.

Source code in src/snailz/model.py

def machine_brightness(params: MachineParams) -> float:
    """Choose relative brightness of this machine's camera.

    Parameters:
        params: machine parameters

    Returns:
        Brightness level in that range.
    """

    return random.uniform(1.0 - params.variation, 1.0 + params.variation)

mutation_loci(params)

Make a list of mutable loci positions.

Parameters:

Name	Type	Description	Default
params	SpecimenParams	specimen generation parameters	required

Returns:

Type	Description
list[int]	Randomly selected positions that can be mutated.

Source code in src/snailz/model.py

def mutation_loci(params: SpecimenParams) -> list[int]:
    """Make a list of mutable loci positions.

    Parameters:
        params: specimen generation parameters

    Returns:
        Randomly selected positions that can be mutated.
    """
    return list(
        sorted(random.sample(list(range(params.genome_length)), params.max_mutations))
    )

specimen_adjust_mass(survey, max_pollution, specimen)

Adjust mass of specimen depending on pollution levels.

Parameters:

Name	Type	Description	Default
survey	Survey	survey that specimen is taken from	required
max_pollution	float	maximum pollution level seen across all surveys	required
specimen	Specimen	specimen to adjust	required

Source code in src/snailz/model.py

def specimen_adjust_mass(
    survey: Survey, max_pollution: float, specimen: Specimen
) -> float:
    """Adjust mass of specimen depending on pollution levels.

    Parameters:
        survey: survey that specimen is taken from
        max_pollution: maximum pollution level seen across all surveys
        specimen: specimen to adjust
    """
    pollution = survey.cells[specimen.location.x, specimen.location.y]
    if (pollution is None) or (pollution == 0.0):
        return specimen.mass
    scaling = 1.0 + 2.0 * utils.sigmoid(pollution / max_pollution)
    return specimen.mass * scaling

specimen_collection_date(survey)

Choose a collection date for a specimen.

Parameters:

Name	Type	Description	Default
survey	BaseModel	survey that specimen belongs to	required

Returns:

Type	Description
date	Date specimen was collected.

Source code in src/snailz/model.py

def specimen_collection_date(survey: BaseModel) -> date:
    """Choose a collection date for a specimen.

    Parameters:
        survey: survey that specimen belongs to

    Returns:
        Date specimen was collected.
    """
    return date.fromordinal(
        random.randint(survey.start_date.toordinal(), survey.end_date.toordinal())
    )

specimen_genome(params, specimens)

Generate genome for a particular specimen.

Parameters:

Name	Type	Description	Default
specimens	BaseModel	all specimens	required

Returns:

Type	Description
tuple[int, str]	Random genome produced by mutating reference genome.

Source code in src/snailz/model.py

def specimen_genome(params: SpecimenParams, specimens: BaseModel) -> tuple[int, str]:
    """Generate genome for a particular specimen.

    Parameters:
        specimens: all specimens

    Returns:
        Random genome produced by mutating reference genome.
    """
    num_species = len(specimens.references)
    species = utils.choose_one(list(range(num_species)), weights=params.prob_species)
    genome = list(specimens.references[species])
    max_mutations = random.randint(1, len(specimens.loci[species]))
    locations = random.sample(specimens.loci[species], max_mutations)
    for loc in locations:
        genome[loc] = utils.choose_one(utils.BASES)
    result = "".join(genome)
    return species, result

specimen_initial_mass(params, species, collected, is_mutant)

Generate mass of a specimen.

Parameters:

Name	Type	Description	Default
params	SpecimenParams	specimen generation parameters	required
collected	date	specimen collection date	required
is_mutant	bool	whether this specimen is a mutant	required

Returns:

Type	Description
float	Random mass.

Source code in src/snailz/model.py

def specimen_initial_mass(
    params: SpecimenParams,
    species: int,
    collected: date,
    is_mutant: bool,
) -> float:
    """Generate mass of a specimen.

    Parameters:
        params: specimen generation parameters
        collected: specimen collection date
        is_mutant: whether this specimen is a mutant

    Returns:
        Random mass.
    """

    # Initial mass
    mass_scale = params.mut_mass_scale if is_mutant else 1.0
    mean_mass = mass_scale * params.mean_masses[species]
    mass = abs(random.gauss(mean_mass, mean_mass * params.mass_rel_stdev))

    # Growth effects
    days_passed = (collected - params.start_date).days
    mass += params.daily_growth * days_passed * mass

    return mass

specimens_num_per_survey(params, survey)

Number of specimens per survey.

Parameters:

Name	Type	Description	Default
params	SpecimenParams	specimen generation parameters	required
survey	Survey	particular survey	required

Returns:

Type	Description
int	Number of specimens.

Source code in src/snailz/model.py

def specimens_num_per_survey(params: SpecimenParams, survey: Survey) -> int:
    """Number of specimens per survey.

    Parameters:
        params: specimen generation parameters
        survey: particular survey

    Returns:
        Number of specimens.
    """
    return random.randint(survey.size // 2, (3 * survey.size) // 2)

specimens_place(survey, specimens)

Place specimens in grid.

Parameters:

Name	Type	Description	Default
survey	Survey	survey from which specimens taken	required
specimens	list[Specimen]	to place	required

Source code in src/snailz/model.py

def specimens_place(survey: Survey, specimens: list[Specimen]) -> None:
    """Place specimens in grid.

    Parameters:
        survey: survey from which specimens taken
        specimens: to place
    """
    anneal(survey.size, specimens)

specimen_reference_genome(params)

Make a random reference genome.

Parameters:

Name	Type	Description	Default
params	SpecimenParams	SpecimenParams with length attribute	required

Returns:

Type	Description
str	A randomly generated genome string of the specified length

Source code in src/snailz/model.py

def specimen_reference_genome(params: SpecimenParams) -> str:
    """Make a random reference genome.

    Parameters:
        params: SpecimenParams with length attribute

    Returns:
        A randomly generated genome string of the specified length
    """
    return "".join(random.choices(utils.BASES, k=params.genome_length))

survey_initialize_grid(size)

Initialize values in survey grid.

Parameters:

Name	Type	Description	Default
size	int	size of survey grid	required

Returns:

Type	Description
Grid[int]	Initialized grid.

Source code in src/snailz/model.py

def survey_initialize_grid(size: int) -> Grid[int]:
    """Initialize values in survey grid.

    Parameters:
        size: size of survey grid

    Returns:
        Initialized grid.
    """
    cells = Grid(width=size, height=size, default=0)
    size_1 = size - 1
    center = size // 2
    moves = [[-1, 0], [1, 0], [0, -1], [0, 1]]
    x, y = center, center
    cells[x, y] = 1
    while (x != 0) and (x != size_1) and (y != 0) and (y != size_1):
        cells[x, y] += 1
        m = random.choice(moves)
        x += m[0]
        y += m[1]
    return cells