Defined as:
sdynpy.modal.sdynpy_smac.SMACAlso available as:
sdynpy.modal.SMAC
Module:
sdynpy.modal.sdynpy_smacSource: GitHub
Signature¶
class sdynpy.SMAC(frfs: sdynpy.core.sdynpy_data.TransferFunctionArray, min_frequency=None, max_frequency=None, complex_modes=False, displacement_derivative=2)Attributes¶
| Name | Summary |
|---|---|
angular_frequencies | |
frequencies | |
frequency_spacing | |
reference_coordinates |
angular_frequencies¶
frequencies¶
frequency_spacing¶
reference_coordinates¶
Methods¶
| Name | Summary |
|---|---|
__init__ | Initialize self. See help(type(self)) for accurate signature. |
autofit_root_alternate | |
autofit_root_paraboloid | |
autofit_roots | |
compute_correlation_matrix | |
compute_initial_rootlist | |
compute_pseudoinverse | |
compute_residues | |
compute_shapes | |
find_peaks | |
fit_damping | |
fit_frequency | |
fit_paraboloid | |
frf_sdof_complex | |
frf_sdof_real | |
get_num_roots | |
save |
__init__¶
Source: GitHub
def sdynpy.SMAC.__init__(self, frfs: sdynpy.core.sdynpy_data.TransferFunctionArray, min_frequency=None, max_frequency=None, complex_modes=False, displacement_derivative=2)Initialize self. See help(type(self)) for accurate signature.
autofit_root_alternate¶
Source: GitHub
def sdynpy.SMAC.autofit_root_alternate(self, initial_frequency, initial_damping, frequency_range=0.01, frequency_points=21, frequency_convergence=0.00025, damping_low=0.0025, damping_high=0.05, damping_points=21, damping_convergence=0.02, frequency_lines_for_correlation=20, max_iter=200, zoom_rate=0.75, plot_convergence=False)autofit_root_paraboloid¶
Source: GitHub
def sdynpy.SMAC.autofit_root_paraboloid(self, initial_frequency, initial_damping, frequency_range=0.01, frequency_points=21, frequency_convergence=0.00025, damping_low=0.0025, damping_high=0.05, damping_points=21, damping_convergence=0.02, frequency_lines_for_correlation=20, max_iter=200, zoom_rate=0.75, plot_convergence=False)autofit_roots¶
Source: GitHub
def sdynpy.SMAC.autofit_roots(self, frequency_range=0.01, frequency_points=21, frequency_convergence=0.00025, damping_low=0.0025, damping_high=0.05, damping_points=21, damping_convergence=0.02, frequency_lines_for_correlation=20, max_iter=200, zoom_rate=0.75, plot_convergence=False, autofit_type=<AutoFitTypes.ALTERNATE: 1>)compute_correlation_matrix¶
Source: GitHub
def sdynpy.SMAC.compute_correlation_matrix(self, low_frequency=None, high_frequency=None, frequency_samples=None, frequency_resolution=None, low_damping=0.0025, high_damping=0.05, damping_samples=21, frequency_lines_for_correlation=20, plot=False)compute_initial_rootlist¶
Source: GitHub
def sdynpy.SMAC.compute_initial_rootlist(self, frequency_samples=None, frequency_resolution=None, low_damping=0.0025, high_damping=0.05, damping_samples=21, frequency_lines_for_correlation=20, peak_finder_filter_size=3, correlation_threshold=0.9, num_roots_mif='cmif', num_roots_frequency_threshold=0.005, plot_correlation=False)compute_pseudoinverse¶
Source: GitHub
def sdynpy.SMAC.compute_pseudoinverse(self)compute_residues¶
Source: GitHub
def sdynpy.SMAC.compute_residues(self, roots, residuals=True, weighting='magnitude')compute_shapes¶
Source: GitHub
def sdynpy.SMAC.compute_shapes(self)find_peaks¶
Source: GitHub
def sdynpy.SMAC.find_peaks(self, correlation_matrix, size=3, threshold=0.9)fit_damping¶
Source: GitHub
def sdynpy.SMAC.fit_damping(self, min_damp, max_damp, frequency, damping_points=21, frequency_lines_for_correlation=20)fit_frequency¶
Source: GitHub
def sdynpy.SMAC.fit_frequency(self, min_freq, max_freq, damping, frequency_points=21, frequency_lines_for_correlation=20)fit_paraboloid¶
Source: GitHub
def sdynpy.SMAC.fit_paraboloid(self, x, y, z)frf_sdof_complex¶
Source: GitHub
def sdynpy.SMAC.frf_sdof_complex(self, frequencies, root_frequencies, root_dampings)frf_sdof_real¶
Source: GitHub
def sdynpy.SMAC.frf_sdof_real(self, frequencies, root_frequencies, root_dampings)get_num_roots¶
Source: GitHub
def sdynpy.SMAC.get_num_roots(self, frequencies, mif_type, frequency_threshold=0.005, plot=False)save¶
Source: GitHub
def sdynpy.SMAC.save(self, filename)