Todo

Improve autoapi module

circadapt.model.benchmark

Benchmark models

Package Contents

Classes

Patch

Wrapper to communicate with c++ code.

Patch

Wrapper to communicate with c++ code.

Chamber2022

Wrapper to communicate with c++ code.

Valve2022

Wrapper to communicate with c++ code.

Valve

Wrapper to communicate with c++ code.

Objects

class circadapt.model.benchmark.Patch(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)

Bases: circadapt.model.Model

Wrapper to communicate with c++ code.

Parameters

solver: str (optional)

Name of solver to be build. If not given, the default models solver is used.

model: str

Name of the model to be build.

path_to_circadapt: str (optional)

Path to CircAdapt library. If not given, the default_path_to_circadapt is used.

model_state: (multi)

Model state to be loaded. (default) -> load model reference from package False -> do nothing str -> load filename dict -> load given model state

build()

Build pre-afterload model with Patch.

This model is designed for illustrating the Patch isolated from the circulation and for benchmarking the Patch module.

set_reference()
assert_1_beat()

Test status after 1 beat, used in unit tests.

This function can be tested after creating the model with the implemented reference and after 1 beat has been calculated. In case the initial model state deviates from the implemented reference, test settings might be changed accordingly.

Test for:

l_si == l_si_init on t=t0 l_se_norm == 1 on t=tend

plot(fig=None)

Simple plot to illustrate the model state.

plot_extended(fig=None)

Extended plot to illustrate the model state.

get_unittest_targets()

Hardcoded results after initializing and running 1 beat.

get_unittest_results(model)

Real-time results after initializing and running 1 beat.

health_check()

Manually perform tests to check compatibility of model with version.

install()
__del__()

Destroy object.

This function is triggered when the python wrapper object is deleted or overwritten. As this wrapper only has pointers to the c++ object, the destructor of the c++ object will be triggered.

get_model_reference(model_state: any = None) → dict

Return reference model state as a dictionary.

If model_state is string, it is assumed to be a file location. This file will be loaded and returned. If is none, the default reference will be loaded. If no default reference available, it will be created and stored in the current active directory.

Parameters
model_statestr or None, optional

Location of model state. The default is None.

Raises
ValueError

DESCRIPTION.

Returns
dict

Dictonary with model state.

load_reference()

Load reference of current model from the package.

load_plugin_components(path_to_library: str)

Load a plugin

Parameters
path_to_librarystr

Path to library.

run(n_beats: int = 1, stable: bool = False, export: bool = True) → None

Run the model by solving the ODEs for n_beats.

The currently loaded model, model state, and parameterization will be used to run n_beats. Optional, more beats are performed until the model is hemodynamically stable (stable=True). By default, all data will be exported (export=True). By disabling this (export=False), the model runs faster by only solving the state variables in case a backward ODE solver is used.

Parameters
n_beats: int, optional (default: True)

Number of beats

stable: bool, optional (default: False)

Run beats until simulation is hemodynamically stable

export: bool, optional (default: False)

Future

is_stable() → bool

Check if simulation is hemodynamically stable.

get(par: str, dtype: any = None) → any

Get parameter from the model.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns
Get value: type depending on dtype.

Returns the value stored in the c++ object

set(par: str, val: any, dtype=None) → bool

Set parameter from dtype with value val.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

val: any

Value to be set. The value must be the same as the parameter used.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns

bool: success or not

trigger(par) → bool

Trigger a function.

Objects in the model may have a function that can be triggered. This can be done by triggering the function using the ‘par’ parameter similar to the set function, only without a parameter.

Parameters
parstr

Function in object that will be triggered. It has a similar form to the set/get par, i.e. ‘Component.subcomponent.function_name’

Returns

is_success (bool)

add(comp_type: str) → bool
add_component(comp_type: str, comp_name: str, base: str = '') → bool

Add component to CircAdapt object.

Parameters
comp_type: str

Type of object to create in the ComponentFactory

comp_name: str

Name of the new object to create

base: char, optional (default=’’)

Parent object of new component

Returns

is_success (bool)

set_component(par, obj) → bool

Set component to the parameter of a CircAdapt object.

Parameters
par: str

Parameter of object to link object obj to

obj: str

Object to set

model_import(model_state, check_model_state=False) → None

Load model_state into CircAdapt object.

Style and model_state version is automatically recognized.

Parameters
model_state: dict

model_state with data to set

obj: str

Object to set

model_export(style: str = None) → dict

Return the stored model state.

Parameters
style: str (optional)

Style to follow. If not given, the default style from the model is used.

Returns

dict

save(filename: str, ext: str = None) → None

Save model to filename with extention.

Parameters
filename: str

Filename to save file to. Filename must have extention .npy or .mat

ext: str (optional)

Extention of the file. If not given, the last 3 letters of the filename is used to determine the save method.

load(filename: str) → None

Load a model dataset from a filename.

Parameters
filename: str

Path to file that will be loaded. The extension must be .npy or .mat.

is_success() → bool

Return false if vectors contain nan.

Returns

bool

__iter__()

Iterate over export dictionary.

Designed to create a dictionary of the object using dict(self).

Yields
key: str

key of dictionary

data[key]: dict

subdictionary of Pdict

__setitem__(arg, val) → bool

Make self subscriptable.

Parameters
arg: str or slice(None, None, None)

If self[:], arg = slice(None, None, None) and set model import dictionary. If self[’…’], return self.set(arg, val)

val: dict or any

Dictionary of the model or single value to set.

__getitem__(arg: any) → any

Make self object subscriptable.

Parameters
arg: slice or str

If self[:], arg = slice(None, None, None) and return model export dictionary. If self[’…’], return self.get(arg)

Returns

model_export dictionary or self.get() type

__getstate__()

Get state manually, because ctypes can not be pickled.

__setstate__(state)

Set state manually, because ctypes can not be pickled.

__repr__()

Object representation in string format.

abstract copy()

Return a copy of itself.

class circadapt.model.benchmark.Patch(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)

Bases: circadapt.model.Model

Wrapper to communicate with c++ code.

Parameters

solver: str (optional)

Name of solver to be build. If not given, the default models solver is used.

model: str

Name of the model to be build.

path_to_circadapt: str (optional)

Path to CircAdapt library. If not given, the default_path_to_circadapt is used.

model_state: (multi)

Model state to be loaded. (default) -> load model reference from package False -> do nothing str -> load filename dict -> load given model state

build()

Build pre-afterload model with Patch.

This model is designed for illustrating the Patch isolated from the circulation and for benchmarking the Patch module.

set_reference()
assert_1_beat()

Test status after 1 beat, used in unit tests.

This function can be tested after creating the model with the implemented reference and after 1 beat has been calculated. In case the initial model state deviates from the implemented reference, test settings might be changed accordingly.

Test for:

l_si == l_si_init on t=t0 l_se_norm == 1 on t=tend

plot(fig=None)

Simple plot to illustrate the model state.

plot_extended(fig=None)

Extended plot to illustrate the model state.

get_unittest_targets()

Hardcoded results after initializing and running 1 beat.

get_unittest_results(model)

Real-time results after initializing and running 1 beat.

health_check()

Manually perform tests to check compatibility of model with version.

install()
__del__()

Destroy object.

This function is triggered when the python wrapper object is deleted or overwritten. As this wrapper only has pointers to the c++ object, the destructor of the c++ object will be triggered.

get_model_reference(model_state: any = None) → dict

Return reference model state as a dictionary.

If model_state is string, it is assumed to be a file location. This file will be loaded and returned. If is none, the default reference will be loaded. If no default reference available, it will be created and stored in the current active directory.

Parameters
model_statestr or None, optional

Location of model state. The default is None.

Raises
ValueError

DESCRIPTION.

Returns
dict

Dictonary with model state.

load_reference()

Load reference of current model from the package.

load_plugin_components(path_to_library: str)

Load a plugin

Parameters
path_to_librarystr

Path to library.

run(n_beats: int = 1, stable: bool = False, export: bool = True) → None

Run the model by solving the ODEs for n_beats.

The currently loaded model, model state, and parameterization will be used to run n_beats. Optional, more beats are performed until the model is hemodynamically stable (stable=True). By default, all data will be exported (export=True). By disabling this (export=False), the model runs faster by only solving the state variables in case a backward ODE solver is used.

Parameters
n_beats: int, optional (default: True)

Number of beats

stable: bool, optional (default: False)

Run beats until simulation is hemodynamically stable

export: bool, optional (default: False)

Future

is_stable() → bool

Check if simulation is hemodynamically stable.

get(par: str, dtype: any = None) → any

Get parameter from the model.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns
Get value: type depending on dtype.

Returns the value stored in the c++ object

set(par: str, val: any, dtype=None) → bool

Set parameter from dtype with value val.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

val: any

Value to be set. The value must be the same as the parameter used.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns

bool: success or not

trigger(par) → bool

Trigger a function.

Objects in the model may have a function that can be triggered. This can be done by triggering the function using the ‘par’ parameter similar to the set function, only without a parameter.

Parameters
parstr

Function in object that will be triggered. It has a similar form to the set/get par, i.e. ‘Component.subcomponent.function_name’

Returns

is_success (bool)

add(comp_type: str) → bool
add_component(comp_type: str, comp_name: str, base: str = '') → bool

Add component to CircAdapt object.

Parameters
comp_type: str

Type of object to create in the ComponentFactory

comp_name: str

Name of the new object to create

base: char, optional (default=’’)

Parent object of new component

Returns

is_success (bool)

set_component(par, obj) → bool

Set component to the parameter of a CircAdapt object.

Parameters
par: str

Parameter of object to link object obj to

obj: str

Object to set

model_import(model_state, check_model_state=False) → None

Load model_state into CircAdapt object.

Style and model_state version is automatically recognized.

Parameters
model_state: dict

model_state with data to set

obj: str

Object to set

model_export(style: str = None) → dict

Return the stored model state.

Parameters
style: str (optional)

Style to follow. If not given, the default style from the model is used.

Returns

dict

save(filename: str, ext: str = None) → None

Save model to filename with extention.

Parameters
filename: str

Filename to save file to. Filename must have extention .npy or .mat

ext: str (optional)

Extention of the file. If not given, the last 3 letters of the filename is used to determine the save method.

load(filename: str) → None

Load a model dataset from a filename.

Parameters
filename: str

Path to file that will be loaded. The extension must be .npy or .mat.

is_success() → bool

Return false if vectors contain nan.

Returns

bool

__iter__()

Iterate over export dictionary.

Designed to create a dictionary of the object using dict(self).

Yields
key: str

key of dictionary

data[key]: dict

subdictionary of Pdict

__setitem__(arg, val) → bool

Make self subscriptable.

Parameters
arg: str or slice(None, None, None)

If self[:], arg = slice(None, None, None) and set model import dictionary. If self[’…’], return self.set(arg, val)

val: dict or any

Dictionary of the model or single value to set.

__getitem__(arg: any) → any

Make self object subscriptable.

Parameters
arg: slice or str

If self[:], arg = slice(None, None, None) and return model export dictionary. If self[’…’], return self.get(arg)

Returns

model_export dictionary or self.get() type

__getstate__()

Get state manually, because ctypes can not be pickled.

__setstate__(state)

Set state manually, because ctypes can not be pickled.

__repr__()

Object representation in string format.

abstract copy()

Return a copy of itself.

class circadapt.model.benchmark.Chamber2022(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)

Bases: circadapt.model.Model

Wrapper to communicate with c++ code.

Parameters

solver: str (optional)

Name of solver to be build. If not given, the default models solver is used.

model: str

Name of the model to be build.

path_to_circadapt: str (optional)

Path to CircAdapt library. If not given, the default_path_to_circadapt is used.

model_state: (multi)

Model state to be loaded. (default) -> load model reference from package False -> do nothing str -> load filename dict -> load given model state

build()

Build pre-afterload model with Patch2022.

This model is designed for illustrating the Patch2022 isolated from the circulation and for benchmarking the Patch2022 module.

plot(fig=None)

Simple plot to illustrate the model state.

plot_extended(fig=None)

Extended plot to illustrate the model state.

assert_1_beat()

Test status after 1 beat, used in unit tests.

get_unittest_targets()

Hardcoded results after initializing and running 1 beat.

get_unittest_results(model)

Real-time results after initializing and running 1 beat.

health_check()

Manually perform tests to check compatibility of model with version.

install()
__del__()

Destroy object.

This function is triggered when the python wrapper object is deleted or overwritten. As this wrapper only has pointers to the c++ object, the destructor of the c++ object will be triggered.

get_model_reference(model_state: any = None) → dict

Return reference model state as a dictionary.

If model_state is string, it is assumed to be a file location. This file will be loaded and returned. If is none, the default reference will be loaded. If no default reference available, it will be created and stored in the current active directory.

Parameters
model_statestr or None, optional

Location of model state. The default is None.

Raises
ValueError

DESCRIPTION.

Returns
dict

Dictonary with model state.

load_reference()

Load reference of current model from the package.

load_plugin_components(path_to_library: str)

Load a plugin

Parameters
path_to_librarystr

Path to library.

run(n_beats: int = 1, stable: bool = False, export: bool = True) → None

Run the model by solving the ODEs for n_beats.

The currently loaded model, model state, and parameterization will be used to run n_beats. Optional, more beats are performed until the model is hemodynamically stable (stable=True). By default, all data will be exported (export=True). By disabling this (export=False), the model runs faster by only solving the state variables in case a backward ODE solver is used.

Parameters
n_beats: int, optional (default: True)

Number of beats

stable: bool, optional (default: False)

Run beats until simulation is hemodynamically stable

export: bool, optional (default: False)

Future

is_stable() → bool

Check if simulation is hemodynamically stable.

get(par: str, dtype: any = None) → any

Get parameter from the model.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns
Get value: type depending on dtype.

Returns the value stored in the c++ object

set(par: str, val: any, dtype=None) → bool

Set parameter from dtype with value val.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

val: any

Value to be set. The value must be the same as the parameter used.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns

bool: success or not

trigger(par) → bool

Trigger a function.

Objects in the model may have a function that can be triggered. This can be done by triggering the function using the ‘par’ parameter similar to the set function, only without a parameter.

Parameters
parstr

Function in object that will be triggered. It has a similar form to the set/get par, i.e. ‘Component.subcomponent.function_name’

Returns

is_success (bool)

add(comp_type: str) → bool
add_component(comp_type: str, comp_name: str, base: str = '') → bool

Add component to CircAdapt object.

Parameters
comp_type: str

Type of object to create in the ComponentFactory

comp_name: str

Name of the new object to create

base: char, optional (default=’’)

Parent object of new component

Returns

is_success (bool)

set_component(par, obj) → bool

Set component to the parameter of a CircAdapt object.

Parameters
par: str

Parameter of object to link object obj to

obj: str

Object to set

model_import(model_state, check_model_state=False) → None

Load model_state into CircAdapt object.

Style and model_state version is automatically recognized.

Parameters
model_state: dict

model_state with data to set

obj: str

Object to set

model_export(style: str = None) → dict

Return the stored model state.

Parameters
style: str (optional)

Style to follow. If not given, the default style from the model is used.

Returns

dict

save(filename: str, ext: str = None) → None

Save model to filename with extention.

Parameters
filename: str

Filename to save file to. Filename must have extention .npy or .mat

ext: str (optional)

Extention of the file. If not given, the last 3 letters of the filename is used to determine the save method.

load(filename: str) → None

Load a model dataset from a filename.

Parameters
filename: str

Path to file that will be loaded. The extension must be .npy or .mat.

is_success() → bool

Return false if vectors contain nan.

Returns

bool

__iter__()

Iterate over export dictionary.

Designed to create a dictionary of the object using dict(self).

Yields
key: str

key of dictionary

data[key]: dict

subdictionary of Pdict

__setitem__(arg, val) → bool

Make self subscriptable.

Parameters
arg: str or slice(None, None, None)

If self[:], arg = slice(None, None, None) and set model import dictionary. If self[’…’], return self.set(arg, val)

val: dict or any

Dictionary of the model or single value to set.

__getitem__(arg: any) → any

Make self object subscriptable.

Parameters
arg: slice or str

If self[:], arg = slice(None, None, None) and return model export dictionary. If self[’…’], return self.get(arg)

Returns

model_export dictionary or self.get() type

__getstate__()

Get state manually, because ctypes can not be pickled.

__setstate__(state)

Set state manually, because ctypes can not be pickled.

__repr__()

Object representation in string format.

abstract copy()

Return a copy of itself.

class circadapt.model.benchmark.Valve2022(solver: str = None, path_to_circadapt: str = None, model_state: dict = None, model_options: dict = {})

Bases: circadapt.model.Model

Wrapper to communicate with c++ code.

Parameters

solver: str (optional)

Name of solver to be build. If not given, the default models solver is used.

model: str

Name of the model to be build.

path_to_circadapt: str (optional)

Path to CircAdapt library. If not given, the default_path_to_circadapt is used.

model_state: (multi)

Model state to be loaded. (default) -> load model reference from package False -> do nothing str -> load filename dict -> load given model state

model_options
build()

Build benchmark for Valve2022.

This model has a Valve2022 module with a prescribed proximal and distal pressure using the NodePressure module.

set_reference()
plot(fig=None)

Simple plot to illustrate the model state.

plot_extended(fig=None)

Extended plot to illustrate the model state.

assert_1_beat()

Test status after 1 beat, used in unit tests.

get_unittest_targets()

Hardcoded results after initializing and running 1 beat.

get_unittest_results(model)

Real-time results after initializing and running 1 beat.

health_check()

Manually perform tests to check compatibility of model with version.

install()
__del__()

Destroy object.

This function is triggered when the python wrapper object is deleted or overwritten. As this wrapper only has pointers to the c++ object, the destructor of the c++ object will be triggered.

get_model_reference(model_state: any = None) → dict

Return reference model state as a dictionary.

If model_state is string, it is assumed to be a file location. This file will be loaded and returned. If is none, the default reference will be loaded. If no default reference available, it will be created and stored in the current active directory.

Parameters
model_statestr or None, optional

Location of model state. The default is None.

Raises
ValueError

DESCRIPTION.

Returns
dict

Dictonary with model state.

load_reference()

Load reference of current model from the package.

load_plugin_components(path_to_library: str)

Load a plugin

Parameters
path_to_librarystr

Path to library.

run(n_beats: int = 1, stable: bool = False, export: bool = True) → None

Run the model by solving the ODEs for n_beats.

The currently loaded model, model state, and parameterization will be used to run n_beats. Optional, more beats are performed until the model is hemodynamically stable (stable=True). By default, all data will be exported (export=True). By disabling this (export=False), the model runs faster by only solving the state variables in case a backward ODE solver is used.

Parameters
n_beats: int, optional (default: True)

Number of beats

stable: bool, optional (default: False)

Run beats until simulation is hemodynamically stable

export: bool, optional (default: False)

Future

is_stable() → bool

Check if simulation is hemodynamically stable.

get(par: str, dtype: any = None) → any

Get parameter from the model.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns
Get value: type depending on dtype.

Returns the value stored in the c++ object

set(par: str, val: any, dtype=None) → bool

Set parameter from dtype with value val.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

val: any

Value to be set. The value must be the same as the parameter used.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns

bool: success or not

trigger(par) → bool

Trigger a function.

Objects in the model may have a function that can be triggered. This can be done by triggering the function using the ‘par’ parameter similar to the set function, only without a parameter.

Parameters
parstr

Function in object that will be triggered. It has a similar form to the set/get par, i.e. ‘Component.subcomponent.function_name’

Returns

is_success (bool)

add(comp_type: str) → bool
add_component(comp_type: str, comp_name: str, base: str = '') → bool

Add component to CircAdapt object.

Parameters
comp_type: str

Type of object to create in the ComponentFactory

comp_name: str

Name of the new object to create

base: char, optional (default=’’)

Parent object of new component

Returns

is_success (bool)

set_component(par, obj) → bool

Set component to the parameter of a CircAdapt object.

Parameters
par: str

Parameter of object to link object obj to

obj: str

Object to set

model_import(model_state, check_model_state=False) → None

Load model_state into CircAdapt object.

Style and model_state version is automatically recognized.

Parameters
model_state: dict

model_state with data to set

obj: str

Object to set

model_export(style: str = None) → dict

Return the stored model state.

Parameters
style: str (optional)

Style to follow. If not given, the default style from the model is used.

Returns

dict

save(filename: str, ext: str = None) → None

Save model to filename with extention.

Parameters
filename: str

Filename to save file to. Filename must have extention .npy or .mat

ext: str (optional)

Extention of the file. If not given, the last 3 letters of the filename is used to determine the save method.

load(filename: str) → None

Load a model dataset from a filename.

Parameters
filename: str

Path to file that will be loaded. The extension must be .npy or .mat.

is_success() → bool

Return false if vectors contain nan.

Returns

bool

__iter__()

Iterate over export dictionary.

Designed to create a dictionary of the object using dict(self).

Yields
key: str

key of dictionary

data[key]: dict

subdictionary of Pdict

__setitem__(arg, val) → bool

Make self subscriptable.

Parameters
arg: str or slice(None, None, None)

If self[:], arg = slice(None, None, None) and set model import dictionary. If self[’…’], return self.set(arg, val)

val: dict or any

Dictionary of the model or single value to set.

__getitem__(arg: any) → any

Make self object subscriptable.

Parameters
arg: slice or str

If self[:], arg = slice(None, None, None) and return model export dictionary. If self[’…’], return self.get(arg)

Returns

model_export dictionary or self.get() type

__getstate__()

Get state manually, because ctypes can not be pickled.

__setstate__(state)

Set state manually, because ctypes can not be pickled.

__repr__()

Object representation in string format.

abstract copy()

Return a copy of itself.

class circadapt.model.benchmark.Valve(solver: str = None, path_to_circadapt: str = None, model_state: dict = None, model_options: dict = {})

Bases: circadapt.model.Model

Wrapper to communicate with c++ code.

Parameters

solver: str (optional)

Name of solver to be build. If not given, the default models solver is used.

model: str

Name of the model to be build.

path_to_circadapt: str (optional)

Path to CircAdapt library. If not given, the default_path_to_circadapt is used.

model_state: (multi)

Model state to be loaded. (default) -> load model reference from package False -> do nothing str -> load filename dict -> load given model state

model_options
build()

Build benchmark for Valve.

This model has a Valve module with a prescribed proximal and distal pressure using the NodePressure module.

set_reference()
plot(fig=None)

Simple plot to illustrate the model state.

plot_extended(fig=None)

Extended plot to illustrate the model state.

assert_1_beat()

Test status after 1 beat, used in unit tests.

get_unittest_targets()

Hardcoded results after initializing and running 1 beat.

get_unittest_results(model)

Real-time results after initializing and running 1 beat.

health_check()

Manually perform tests to check compatibility of model with version.

install()
__del__()

Destroy object.

This function is triggered when the python wrapper object is deleted or overwritten. As this wrapper only has pointers to the c++ object, the destructor of the c++ object will be triggered.

get_model_reference(model_state: any = None) → dict

Return reference model state as a dictionary.

If model_state is string, it is assumed to be a file location. This file will be loaded and returned. If is none, the default reference will be loaded. If no default reference available, it will be created and stored in the current active directory.

Parameters
model_statestr or None, optional

Location of model state. The default is None.

Raises
ValueError

DESCRIPTION.

Returns
dict

Dictonary with model state.

load_reference()

Load reference of current model from the package.

load_plugin_components(path_to_library: str)

Load a plugin

Parameters
path_to_librarystr

Path to library.

run(n_beats: int = 1, stable: bool = False, export: bool = True) → None

Run the model by solving the ODEs for n_beats.

The currently loaded model, model state, and parameterization will be used to run n_beats. Optional, more beats are performed until the model is hemodynamically stable (stable=True). By default, all data will be exported (export=True). By disabling this (export=False), the model runs faster by only solving the state variables in case a backward ODE solver is used.

Parameters
n_beats: int, optional (default: True)

Number of beats

stable: bool, optional (default: False)

Run beats until simulation is hemodynamically stable

export: bool, optional (default: False)

Future

is_stable() → bool

Check if simulation is hemodynamically stable.

get(par: str, dtype: any = None) → any

Get parameter from the model.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns
Get value: type depending on dtype.

Returns the value stored in the c++ object

set(par: str, val: any, dtype=None) → bool

Set parameter from dtype with value val.

Parameters
par: str

Parameter name to get. This string value contains the parameter that will be obtained and the component from which it will be obtained. Components, its subcomponents, and the parameter name at the and are separated with a dot.

val: any

Value to be set. The value must be the same as the parameter used.

dtype: string or type, optional (default = None)

The type of parameter that will be obtained. If not specified, it will be detairmined automatically. If computational cost is important, it is better to specify the dtype.

Returns

bool: success or not

trigger(par) → bool

Trigger a function.

Objects in the model may have a function that can be triggered. This can be done by triggering the function using the ‘par’ parameter similar to the set function, only without a parameter.

Parameters
parstr

Function in object that will be triggered. It has a similar form to the set/get par, i.e. ‘Component.subcomponent.function_name’

Returns

is_success (bool)

add(comp_type: str) → bool
add_component(comp_type: str, comp_name: str, base: str = '') → bool

Add component to CircAdapt object.

Parameters
comp_type: str

Type of object to create in the ComponentFactory

comp_name: str

Name of the new object to create

base: char, optional (default=’’)

Parent object of new component

Returns

is_success (bool)

set_component(par, obj) → bool

Set component to the parameter of a CircAdapt object.

Parameters
par: str

Parameter of object to link object obj to

obj: str

Object to set

model_import(model_state, check_model_state=False) → None

Load model_state into CircAdapt object.

Style and model_state version is automatically recognized.

Parameters
model_state: dict

model_state with data to set

obj: str

Object to set

model_export(style: str = None) → dict

Return the stored model state.

Parameters
style: str (optional)

Style to follow. If not given, the default style from the model is used.

Returns

dict

save(filename: str, ext: str = None) → None

Save model to filename with extention.

Parameters
filename: str

Filename to save file to. Filename must have extention .npy or .mat

ext: str (optional)

Extention of the file. If not given, the last 3 letters of the filename is used to determine the save method.

load(filename: str) → None

Load a model dataset from a filename.

Parameters
filename: str

Path to file that will be loaded. The extension must be .npy or .mat.

is_success() → bool

Return false if vectors contain nan.

Returns

bool

__iter__()

Iterate over export dictionary.

Designed to create a dictionary of the object using dict(self).

Yields
key: str

key of dictionary

data[key]: dict

subdictionary of Pdict

__setitem__(arg, val) → bool

Make self subscriptable.

Parameters
arg: str or slice(None, None, None)

If self[:], arg = slice(None, None, None) and set model import dictionary. If self[’…’], return self.set(arg, val)

val: dict or any

Dictionary of the model or single value to set.

__getitem__(arg: any) → any

Make self object subscriptable.

Parameters
arg: slice or str

If self[:], arg = slice(None, None, None) and return model export dictionary. If self[’…’], return self.get(arg)

Returns

model_export dictionary or self.get() type

__getstate__()

Get state manually, because ctypes can not be pickled.

__setstate__(state)

Set state manually, because ctypes can not be pickled.

__repr__()

Object representation in string format.

abstract copy()

Return a copy of itself.