settings#
Customize the behavior of the module.
- ansys.dpf.core.settings.disable_off_screen_rendering()#
No pop up windows appears to plot data with
matplotlib
orpyvista
- Return type:
None
- ansys.dpf.core.settings.disable_interpreter_properties_evaluation()#
If
jedi
module is installed (autocompletion module for most of IDEs), disables the property evaluation when tab key is pressed.To use in Jupyter Notebook if autocompletion becomes slow.
- Returns:
Whether disabling the capability has been possible.
- Return type:
bool
- ansys.dpf.core.settings.set_dynamic_available_results_capability(value)#
Disables the evaluation of the available results and the dynamic creation of the results properties when a ‘’Model’’ is created.
- Parameters:
value (bool) – With ‘’True’’, models will dynamically generate results properties
- Return type:
None
Examples
>>> from ansys.dpf import core as dpf >>> dpf.settings.set_dynamic_available_results_capability(False) >>> dpf.settings.set_dynamic_available_results_capability(True)
- ansys.dpf.core.settings.get_runtime_client_config(server=None)#
Get the runtime configuration information of Ans.Dpf.GrpcClient binary.
- Parameters:
server (server.DPFServer, optional) – Server with channel connected to the remote or local instance. When
None
, attempts to use the global server.
Notes
Available from 4.0 server version. Can only be used for a gRPC communication protocol using DPF CLayer.
- Returns:
runtime_config – RuntimeClientConfig object that can be used to interact with Ans.Dpf.GrpcClient configuration.
- Return type:
- ansys.dpf.core.settings.get_runtime_core_config(server=None)#
Get the runtime configuration information of Ans.Dpf.GrpcClient binary.
- Parameters:
server (server.DPFServer, optional) – Server with channel connected to the remote or local instance. When
None
, attempts to use the global server.
Notes
Available from 4.0 server version.
- Returns:
core_config – RuntimeCoreConfig object that can be used to interact with DataProcessingCore configuration.
- Return type: