Todo

Improve autoapi module

`circadapt.model.vanosta2023`

VanOsta2023 model.

Module Contents

Classes

`VanOsta2023`	Wrapper to communicate with c++ code.
`VanOsta2023_2310`	Wrapper to communicate with c++ code.
`VanOsta2023_2306`	Wrapper to communicate with c++ code.
`VanOsta2023_2308`	Wrapper to communicate with c++ code.
`Walmsley2015`	Wrapper to communicate with c++ code.

Attributes

colors

Objects

circadapt.model.vanosta2023.colors

class circadapt.model.vanosta2023.VanOsta2023(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)[source]

Bases: circadapt.model.Model, circadapt.adapt.ModelAdapt

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()[source]

Build model.

Add and link components in the model. By default, the model is empty. This function will be used in derived model builts.

set_reference()[source]

get_unittest_targets()[source]: Hardcoded results after initializing and running 1 beat.

get_unittest_results(model)[source]: Real-time results after initializing and running 1 beat.

plot(fig=None)[source]: Simple plot to illustrate the model state.

plot_extended(fig=None)[source]: Extended plot to illustrate the model state.

assert_1_beat(): Test status after 1 beat, used in unit tests.

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.

check_build()

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.

get_adapt_options(): Get default adapt options.

adapt(options: dict = {}, output: bool = False, verbose: bool = False) → None

Run adaptation protocol.

The adaptation protocol runs n_cycles cycles. Each cycle has two phases, namely rest adaptation and exercise adaptation. First, in exercise, the Patches and vessel wall volumes are adapted to load. In rest, vessels are adapted to flow.

Parameters

optionsdictionary, optional: Options for the protocol. To set options, use the function get_adapt_options(), which is used by default. The default is {}.
outputbool, optional: DESCRIPTION. The default is False.

Returns

senses_resultsTYPE: Only when output=True.
senses_normTYPE: Only when output=True.
actor_resultsTYPE: Only when output=True.
actor_vwallTYPE: Only when output=True.

adapt_exercise(options): Trigger all excercise adaptation functions.

adapt_rest(options): Trigger all rest adaptation functions.

calculate_and_set_matrix(verbose=False)

get_matrix(verbose=False)

class circadapt.model.vanosta2023.VanOsta2023_2310(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)[source]

Bases: VanOsta2023

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

set_reference()[source]

get_unittest_targets()[source]: Hardcoded results after initializing and running 1 beat.

build()

Build model.

Add and link components in the model. By default, the model is empty. This function will be used in derived model builts.

get_unittest_results(model): Real-time results after initializing and running 1 beat.

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.

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.

check_build()

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.

get_adapt_options(): Get default adapt options.

adapt(options: dict = {}, output: bool = False, verbose: bool = False) → None

Run adaptation protocol.

The adaptation protocol runs n_cycles cycles. Each cycle has two phases, namely rest adaptation and exercise adaptation. First, in exercise, the Patches and vessel wall volumes are adapted to load. In rest, vessels are adapted to flow.

Parameters

optionsdictionary, optional: Options for the protocol. To set options, use the function get_adapt_options(), which is used by default. The default is {}.
outputbool, optional: DESCRIPTION. The default is False.

Returns

senses_resultsTYPE: Only when output=True.
senses_normTYPE: Only when output=True.
actor_resultsTYPE: Only when output=True.
actor_vwallTYPE: Only when output=True.

adapt_exercise(options): Trigger all excercise adaptation functions.

adapt_rest(options): Trigger all rest adaptation functions.

calculate_and_set_matrix(verbose=False)

get_matrix(verbose=False)

class circadapt.model.vanosta2023.VanOsta2023_2306(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)[source]

Bases: VanOsta2023

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

set_reference()[source]

get_unittest_targets()[source]: Hardcoded results after initializing and running 1 beat.

build()

Build model.

Add and link components in the model. By default, the model is empty. This function will be used in derived model builts.

get_unittest_results(model): Real-time results after initializing and running 1 beat.

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.

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.

check_build()

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.

get_adapt_options(): Get default adapt options.

adapt(options: dict = {}, output: bool = False, verbose: bool = False) → None

Run adaptation protocol.

The adaptation protocol runs n_cycles cycles. Each cycle has two phases, namely rest adaptation and exercise adaptation. First, in exercise, the Patches and vessel wall volumes are adapted to load. In rest, vessels are adapted to flow.

Parameters

optionsdictionary, optional: Options for the protocol. To set options, use the function get_adapt_options(), which is used by default. The default is {}.
outputbool, optional: DESCRIPTION. The default is False.

Returns

senses_resultsTYPE: Only when output=True.
senses_normTYPE: Only when output=True.
actor_resultsTYPE: Only when output=True.
actor_vwallTYPE: Only when output=True.

adapt_exercise(options): Trigger all excercise adaptation functions.

adapt_rest(options): Trigger all rest adaptation functions.

calculate_and_set_matrix(verbose=False)

get_matrix(verbose=False)

class circadapt.model.vanosta2023.VanOsta2023_2308(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)[source]

Bases: VanOsta2023

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

set_reference()[source]

get_unittest_targets()[source]: Hardcoded results after initializing and running 1 beat.

build()

Build model.

Add and link components in the model. By default, the model is empty. This function will be used in derived model builts.

get_unittest_results(model): Real-time results after initializing and running 1 beat.

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.

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.

check_build()

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.

get_adapt_options(): Get default adapt options.

adapt(options: dict = {}, output: bool = False, verbose: bool = False) → None

Run adaptation protocol.

The adaptation protocol runs n_cycles cycles. Each cycle has two phases, namely rest adaptation and exercise adaptation. First, in exercise, the Patches and vessel wall volumes are adapted to load. In rest, vessels are adapted to flow.

Parameters

optionsdictionary, optional: Options for the protocol. To set options, use the function get_adapt_options(), which is used by default. The default is {}.
outputbool, optional: DESCRIPTION. The default is False.

Returns

senses_resultsTYPE: Only when output=True.
senses_normTYPE: Only when output=True.
actor_resultsTYPE: Only when output=True.
actor_vwallTYPE: Only when output=True.

adapt_exercise(options): Trigger all excercise adaptation functions.

adapt_rest(options): Trigger all rest adaptation functions.

calculate_and_set_matrix(verbose=False)

get_matrix(verbose=False)

class circadapt.model.vanosta2023.Walmsley2015(solver: str = None, path_to_circadapt: str = None, model_state: dict = None)[source]

Bases: VanOsta2023

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

set_reference()[source]

build()

Build model.

Add and link components in the model. By default, the model is empty. This function will be used in derived model builts.

get_unittest_targets(): Hardcoded results after initializing and running 1 beat.

get_unittest_results(model): Real-time results after initializing and running 1 beat.

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.

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.

check_build()

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.

get_adapt_options(): Get default adapt options.

adapt(options: dict = {}, output: bool = False, verbose: bool = False) → None

Run adaptation protocol.

The adaptation protocol runs n_cycles cycles. Each cycle has two phases, namely rest adaptation and exercise adaptation. First, in exercise, the Patches and vessel wall volumes are adapted to load. In rest, vessels are adapted to flow.

Parameters

optionsdictionary, optional: Options for the protocol. To set options, use the function get_adapt_options(), which is used by default. The default is {}.
outputbool, optional: DESCRIPTION. The default is False.

Returns

senses_resultsTYPE: Only when output=True.
senses_normTYPE: Only when output=True.
actor_resultsTYPE: Only when output=True.
actor_vwallTYPE: Only when output=True.

adapt_exercise(options): Trigger all excercise adaptation functions.

adapt_rest(options): Trigger all rest adaptation functions.

calculate_and_set_matrix(verbose=False)

get_matrix(verbose=False)

circadapt.model.vanosta2023

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`circadapt.model.vanosta2023`