Todo

Improve autoapi module

circadapt.components.patch

Patch objects.

Module Contents

Classes

Patch2022

Patch2022 is based on Patch in Walmsley 2015.

Objects

class circadapt.components.patch.Patch2022(model, objects=None, wall_locs=None)

Bases: circadapt.components.Component

Patch2022 is based on Patch in Walmsley 2015.

Parameters

Am_ref [\(m^2\)]: float

Reference wall area at \(l_{s} = l_{s,ref}\).

V_wall [\(m^3\)]: float

Wall volume

v_max [\(\mu m/s\)]: float

Maximum shortening velocity

l_se0 [\(\mu m\)]: float

lgth of the series elastic element, i.e. \(l_{s} -l_{si}\) for which stress is zero.

l_s0 [\(\mu m\)]: float

Reference sarcomere lgth for which at \(A_m (l_{s,ref}) = A_{m,ref}\).

dl_s_pas [\(\mu m\)]: float

Nonlinear exponent of Titin stress

Sf_pas [Pa]: float

Linear ECM stress coefficient

fac_Sf_tit [-]: float

Contribution factor of titen stress multiplied with Sf_act

k1 [-]: float

Nonlinear exponent ECM stress component

tr [s]: float

Contraction time constant

td [s]: float

Relaxation time constant

time_act [-]: float

Relative contraction duration

Sf_act [Pa]: float

Linear active stress component

dt [s]: float

Activation delay relative to intrinsic activation

C_rest [-]: float

Rest contractility

l_si0 [\(\mu m\)]: float

Reference lgth for zero-active-stress

LDAD [s]: float

strain dependend activation duration

ADO [s]: float

activation duration offset

LDCC [-]: float

stretch dependend contractility coefficient

Sf_pasMaxT: float

Maximum ecm stress (adaptation sens variable)

Sf_pasActT: float

Active weighted passive stress (adaptation sens variable)

FacSf_actT: float

Active stress (adaptation sens variable)

LsPasActT: float

Weighted sarcomere lgth average (adaptation sens variable)

adapt_gamma: bool

Adaptation constant

Signals

Signals are arrays. Each point in the array represents a point in time with step-size controlled by the solver.

l_s [\(\mu m\)]: array

Sarcomere lgth

l_si [\(\mu m\)]: array

State variable: Intrinsic sarcomere lgth

LsiDot [\(\mu m/s\)]: array

State variable: Intrinsic sarcomere lgth time-derivative

C [-]: array

State variable: contraction curve

C_dot [1/s]: array

State variable: contraction time-derivative

Am [m:sup:2]: array

Patch mid-wall area

Am0 [m:sup:2]: array

Patch mid-wall zero-stress area

Ef [-]: array

Natural strain

T [Nm]: array

Mid-wall tension

dA_dT [m / N]: array

Area-tension derivative

Sf [Pa]: array

Total fibre stress at mid-wall

Sf_pasT [Pa]: array

Total passive stress at mid-wall

SfEcm [Pa]: array

Total ECM stress at mid-wall

dSf_dEf [Pa]: array

Total stiffness coefficient

dSf_pas_dEf [Pa]: array

Total passive stiffness coefficient

SfEcmMax: array

Adaptation: Maximum ECM stress

Sf_actMax: array

Adaptation: maximum active stress

Sf_pasAct: array

Adaptation: active-weighted passive stress

LsPasAct: array

Adaptation: active-weigthed sarcomere lgth

parameters = ['Am_ref', 'V_wall', 'v_max', 'l_se0', 'l_s0', 'l_s_ref', 'dl_s_pas', 'Sf_pas', 'tr', 'td',...
signals = ['l_s', 'l_si', 'l_si_dot', 'C', 'C_dot', 'Cm', 'Am', 'Am0', 'Ef', 'T', 'dA_dT', 'Sf',...
parameter_on_set
build()

(re)build patch locations based on wall locations.

There is no compatibility with different types of patches used in the model. If you use different type of patches, please use the direct way of interacting with the c++ object, i.e. set() and get().

get_all_patches()

Get all patches of the walls included in this pointer object.

add_object(o)
__repr__()

Object representation in string format.

__getitem__(arg: any) any

Get data.

This function is called when self[arg].

Parameters
arg: slice or string

If slice, return a components object with locs obtained from slice. If str, return the parameter or signal for all locs

__setitem__(arg: str, val: any) any

Set data.

Set data of the parameter given in arg. Only parameter names can be used.

Parameters
arg: str

Parameter name

val: float/int/bool

Value will automatically be translated to type to

__iter__()

Iterate over object, used for dict(self).