waxmorph.simulator.growth_step

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waxmorph.simulator.growth_step#

waxmorph.simulator.growth_step(R, R_eq, A, CT, keys, alpha_grow, ell_sw, dt, R_ref, R_max, particle_count, R_next, R_eq_next, device='cuda', grad_consist=True)[source]#

Apply bounded growth in model units.

Mesenchymal equilibrium radii use a stochastic rate in [0.8, 1) and

\[\dot r_i^{eq}=\lambda_i\frac{a_i^{\alpha}} {\ell_{sw}^{\alpha}+a_i^{\alpha}+EPS_DEN},\qquad \dot r_i=(1-r_i/r_i^{eq})^2.\]

Here \(a_i=A_i/(V_i+EPS_DEN)\); the physical-radius ratio is regularized by the same denominator constant. Physical radii below their target advance toward it and stop at that bound. Mesenchymal keys advance in place. Mesenchymal targets are capped at R_max; epithelial targets copy through and physical radii approach R_ref. dt and R_max must be finite and nonnegative; R_ref must be finite and positive.

Parameters:

  • R (array(ndim=1, dtype=float32))

  • R_eq (array(ndim=1, dtype=float32))

  • A (array(ndim=1, dtype=float32))

  • CT (array(ndim=1, dtype=uint32))

  • keys (array(ndim=1, dtype=uint32))

  • alpha_grow (array(ndim=1, dtype=float32))

  • ell_sw (array(ndim=1, dtype=float32))

  • dt (float)

  • R_ref (float32)

  • R_max (float32)

  • particle_count (int)

  • R_next (array(ndim=1, dtype=float32))

  • R_eq_next (array(ndim=1, dtype=float32))

  • device (str)

  • grad_consist (bool)

Return type:

None

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