#!/usr/bin/env python
#
# pyLOM - Python Low Order Modeling.
#
# DMD plotting utilities.
#
# Last rev: 27/10/2021
from __future__ import print_function, division
import numpy as np
import matplotlib.pyplot as plt
from .utils import extract_modes
from ..utils import gpu_to_cpu
from ..utils.plots import plotResidual, plotFieldStruct2D, plotSnapshot, plotLayout
from .. import Mesh, Dataset
[docs]
def plotMode(L:np.ndarray, P:np.ndarray, freqs:np.ndarray, mesh:Mesh, dset:Dataset, ivar:int, pointData:bool=True, modes:np.ndarray=np.array([1],np.int32),**kwargs):
r'''
Plot a SPOD mode, including both the real and imaginary parts
Args:
L (np.ndarray): modal energy spectra
P (np.ndarray): spatial SPOD modes
freqs (np.ndarray): frequencies at which the modes are computed
mesh (Mesh): mesh at which the data is represented
dset (Dataset): pyLOM Dataset containing the case information
ivar (int): index of the variable inside the dataset
pointData(bool, optional): whether the data is represented on points or cell (default, ``True``)
modes (np.ndarray, optinal): IDs of the modes to plot
'''
L, P = gpu_to_cpu(L), gpu_to_cpu(P)
# Extract the modes to be plotted
npoints = mesh.size(pointData)
P_modes = extract_modes(L,P,ivar,npoints,modes=modes)
# Add to the dataset
dset.add_field('P_MODES',len(modes),P_modes)
# Loop over the modes
screenshot = kwargs.pop('screenshot',None)
off_screen = kwargs.pop('off_screen',False)
for imode, mode in enumerate(modes):
if screenshot is not None: kwargs['screenshot'] = screenshot % imode
plotLayout(mesh,dset,1,1,mode-1,vars=['P_MODES'],title='Mode %d St = %.3f' % (mode-1, np.abs(freqs[mode-1])),off_screen=off_screen,**kwargs)
# Remove from dataset
dset.delete('P_MODES')
[docs]
def plotSpectra(f:np.ndarray, L:np.ndarray, fig:plt.figure=None, ax:plt.axes=None):
r'''
Plot the frequency-enegy spectrum
Args:
f (np.ndarray): frequencies at which the modes are computed
L (np.ndarray): energy of each frequency
fig (plt.figure, optional): figure object in which the plot will be done (default: ``[]``)
axs (plt.axes, optional): axes object in which the plot will be done (default: ``[]``)
Returns:
[plt.figure, plt.axes]: figure and axes objects of the plot
'''
L, f = gpu_to_cpu(L), gpu_to_cpu(f)
# Get or recover axis and figure
if fig is None:
fig = plt.figure(figsize=(8,6),dpi=100)
if ax is None:
ax = fig.add_subplot(1,1,1)
# Plot
for ii in range(L.shape[1]):
ax.loglog(np.sort(f), L[np.argsort(f),ii], 'o-')
ax.set_xlabel('St')
ax.set_ylabel(r'$\lambda_i$')
return fig, ax
