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working on mpf
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@SteveDoyle2
SteveDoyle2 committed Dec 18, 2024
1 parent 81e7fb2 commit 5e2efa3
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Showing 3 changed files with 231 additions and 41 deletions.
206 changes: 174 additions & 32 deletions pyNastran/f06/flutter_response.py
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Original file line number Diff line number Diff line change
Expand Up @@ -251,9 +251,14 @@ def __init__(self, subcase: int, configuration: str,
"""
if eigr_eigi_velocity is None:
eigr_eigi_velocity = np.array((0,3), dtype='float64')
eigr_eigi_velocity = np.zeros((0,3), dtype='float64')
if eigenvector is None:
eigenvector = np.array([], dtype='complex128')
else:
assert eigenvector.ndim == 2, eigenvector.shape

assert eigr_eigi_velocity.ndim == 2, eigr_eigi_velocity
assert eigr_eigi_velocity.shape[1] == 3, eigr_eigi_velocity
self.eigenvector = eigenvector
self.eigr_eigi_velocity = eigr_eigi_velocity

Expand Down Expand Up @@ -650,6 +655,138 @@ def plot_root_locus(self, modes=None,
png_filename=png_filename,
**legend_kwargs)

def plot_modal_participation(self, modes=None,
fig=None, axes=None,
#eigr_lim=None, eigi_lim=None,
ncol: int=0,
show: bool=True, clear: bool=False,
close: bool=False, legend: bool=True,
#noline: bool=False, nopoints: bool=False,
freq_tol: float=-1.0,
png_filename=None,
**legend_kwargs):
"""
Plots a root locus
Parameters
----------
modes : list[int] / int ndarray; (default=None -> all)
the modes; typically 1 to N
fig : plt.Figure
the figure object
axes : plt.Axes
the axes object
eigr_lim : list[float/None, float/None]
the x plot limits
eigi_lim : list[float/None, float/None]
the y plot limits
show : bool; default=True
show the plot
clear : bool; default=False
clear the plot
legend : bool; default=True
show the legend
kwargs : dict; default=None
key : various matplotlib parameters
value : depends
Legend kwargs
-------------
loc : str
'best'
fancybox : bool; default=False
makes the box look cool
framealpha : float; 0.0 <= alpha <= 1.0
1.0 - no transparency / opaque
0.0 - fully transparent
"""
modes, imodes = _get_modes_imodes(self.modes, modes)
legend_kwargs = get_legend_kwargs(legend_kwargs)
if fig is None:
fig = plt.figure()
axes = fig.add_subplot(111)

xlabel = r'Eigenvalue (Real); $\omega \zeta$'
ylabel = r'Eigenvalue (Imaginary); $\omega$'
# ix = self.ieigr
# iy = self.ieigi
# scatter = True

ivel = 0
imode = 1
#print(f'eigr_eigi_velocity.shape: {self.eigr_eigi_velocity.shape}')
#print(f'eigenvector.shape: {self.eigenvector.shape}')
#print(f'eigr_eigi_velocity:\n{self.eigr_eigi_velocity}')

# MSC
#eigr_eigi_velocity:
#[[-9.88553e-02 1.71977e+01 1.52383e+02]
# [-1.71903e-01 6.60547e+01 1.52383e+02]]
eigr_eigi_velocity = self.eigr_eigi_velocity[ivel, :]
eigri, eigii, velocityi = eigr_eigi_velocity

omega_damping = eigri
omega = eigii

#xlabel = r'Eigenvalue (Real); $\omega \gamma$'
#xlabel = r'Eigenvalue (Imaginary); $\omega$'
freq = omega / (2 * np.pi)
damping_g = 2 * omega_damping / omega
title = f'Modal Participation Factors of Mode {imode+1}\n'
title += f'omega={omega:.2f}; freq={freq:.2f} Hz; g={damping_g:.4g}'
if np.isfinite(velocityi):
title += f' V={velocityi:.1f}'
#print(title)
axes.set_title(title)
axes.grid(True)
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)

#print(f'eigr_eigi_velocity:\n{self.eigr_eigi_velocity}')
#print(f'eigenvector:\n{self.eigenvector}')

eig = self.eigenvector[imodes, :]
eigr = eig.real
eigi = eig.imag
# abs_eigr = np.linalg.norm(eigr)
# abs_eigi = np.linalg.norm(eigi)
# if abs_eigr == 0.0:
# abs_eigr = 1.0
# if abs_eigi == 0.0:
# abs_eigi = 1.0

# don't normalize
abs_eigr = 1.0
abs_eigi = 1.0

reals = eigr / abs_eigr
imags = eigi / abs_eigi
for i, imodei, mode in zip(count(), imodes, modes):
#real = self.eigenvector[imode1, :].real, label=f'iMode1={imode1+1}')
reali = reals[i, imode]
imagi = imags[i, imode]
text = str(mode)
axes.scatter(reali, imagi, label=f'Mode {mode}')
#print(f'{i}: {reali}, {imagi}, {text!r}')
axes.text(reali, imagi, text, ha='center', va='center')

if legend:
# bbox_to_anchor=(1.125, 1.), ncol=ncol,
axes.legend(**legend_kwargs)

if show:
plt.show()
if png_filename:
plt.savefig(png_filename)
if clear:
fig.clear()
if close:
plt.close()
# for imode1 in range(nmodes1):
# ax11.plot(self.eigenvector[imode1, :].real, label=f'iMode1={imode1+1}')
# ax12.plot(self.eigenvector[imode1, :].imag, label=f'iMode1={imode1+1}')

def _plot_x_y(self, ix: int, iy: int,
xlabel: str, ylabel: str,
scatter: bool,
Expand Down Expand Up @@ -1191,7 +1328,7 @@ def export_to_csv(self, csv_filename: PathLike,
' 1, 0.0000E+00, 0.0000E+00, 0.0000E+00, 0.0000E+00'
' 2, 4.9374E-01, -1.6398E-03, -5.4768E-04, -2.3136E-04'
"""
imodes = self._imodes(modes)
imodes = _imodes(self.results.shape, modes)
assert len(imodes) > 0, imodes
headers = ['ipoint']
for name in self.names:
Expand Down Expand Up @@ -1240,7 +1377,7 @@ def export_to_veas(self, veas_filename: PathLike,
' 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 1.4277E+01 7.7705E+01 8.8016E+01 2.2346E+02 2.4656E+02 3.2366E+02 4.5518E+02 4.9613E+02 6.7245E+02 7.3197E+02 8.0646E+02 0.0000E+00'
' 4.9374E-01 -1.6398E-03 -5.4768E-04 -2.3136E-04 -3.5776E-04 -6.2358E-05 -3.0348E-04 -7.7492E-05 -2.0301E-05 -1.7733E-04 -9.2383E-05 -1.2849E-05 -2.8854E-05 4.9374E-01 1.4272E+01 7.7726E+01 8.8010E+01 2.2347E+02 2.4655E+02 3.2364E+02 4.5516E+02 4.9612E+02 6.7245E+02 7.3195E+02 8.0646E+02 0.0000E+00'
"""
modes, nmodes = self._modes_nmodes(modes)
modes, nmodes = _modes_nmodes(self.results.shape, modes)

damping_modes = []
omega_modes = []
Expand All @@ -1266,32 +1403,6 @@ def export_to_veas(self, veas_filename: PathLike,
str_values = (' %11.4E' % value for value in values)
veas_file.write(''.join(str_values) + '\n')

def _imodes(self, modes: Optional[np.ndarray, slice[int] |
tuple[int] | list[int]]) -> np.ndarray:
"""gets the imodes from the modes"""
if modes is None:
nmodes = self.results.shape[0]
imodes = range(nmodes)
elif isinstance(modes, slice):
nmodes = self.results.shape[0]
all_modes = np.arange(0, nmodes, dtype='int32')
imodes = all_modes[modes]
elif isinstance(modes, (list, tuple)):
modes = np.array(modes, dtype='int32')
imodes = modes - 1
else:
imodes = modes - 1
return imodes

def _modes_nmodes(self, modes: Optional[Iterable[int]]) -> tuple[Iterable[int], int]:
"""gets the modes and nmodes"""
if modes is None:
nmodes = self.results.shape[0]
modes = range(1, nmodes + 1)
else:
nmodes = max(modes)
return modes, nmodes

def export_to_f06(self, f06_filename: PathLike,
modes: Optional[list[int]]=None,
page_stamp: Optional[str]=None,
Expand All @@ -1307,7 +1418,7 @@ def export_to_f06_file(self, f06_file: str,
modes: Optional[list[int]]=None,
page_stamp: Optional[str]=None,
page_num: int=1) -> int:
imodes = self._imodes(modes)
imodes = _imodes(self.results.shape, modes)
if page_stamp is None:
page_stamp = 'PAGE %i'
for imode in imodes:
Expand Down Expand Up @@ -1355,7 +1466,7 @@ def export_to_zona(self, zona_filename: PathLike,

modes, imodes = _get_modes_imodes(self.modes, modes)
#unused_legend_items = ['Mode %i' % mode for mode in modes]
ix, unused_xlabel = self._plot_type_to_ix_xlabel(plot_type)
ix, unused_xlabel, xunit = self._plot_type_to_ix_xlabel(plot_type)

# these are the required damping levels to plot
msg = ''
Expand Down Expand Up @@ -1532,7 +1643,38 @@ def object_methods(self, mode: str='public', keys_to_skip=None):
return object_methods(self, mode=mode, keys_to_skip=keys_to_skip)


def _get_modes_imodes(all_modes, modes):
def _imodes(results_shape: tuple[int, int],
modes: Optional[np.ndarray, slice[int] |
tuple[int] | list[int]]) -> np.ndarray:
"""gets the imodes from the modes"""
if modes is None:
nmodes = results_shape[0]
imodes = range(nmodes)
elif isinstance(modes, slice):
nmodes = results_shape[0]
all_modes = np.arange(0, nmodes, dtype='int32')
imodes = all_modes[modes]
elif isinstance(modes, (list, tuple)):
modes = np.array(modes, dtype='int32')
imodes = modes - 1
else:
imodes = modes - 1
return imodes


def _modes_nmodes(results_shape: tuple[int, int],
modes: Optional[Iterable[int]]) -> tuple[Iterable[int], int]:
"""gets the modes and nmodes"""
if modes is None:
nmodes = results_shape[0]
modes = range(1, nmodes + 1)
else:
nmodes = max(modes)
return modes, nmodes


def _get_modes_imodes(all_modes: np.ndaray,
modes: Optional[slice | np.ndarray]):
"""gets the index of the modes to plot"""
if modes is None:
modes = all_modes
Expand Down
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