How to use the pydmd.dmdbase.DMDBase function in PyDMD

To help you get started, we’ve selected a few PyDMD examples, based on popular ways it is used in public projects.

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github mathLab / PyDMD / tests / test_dmdbase.py View on Github external
def test_opt(self):
        dmd = DMDBase(opt=True)
        assert dmd.opt == True
github mathLab / PyDMD / tests / test_dmdbase.py View on Github external
def test_exact_default(self):
        dmd = DMDBase()
        assert dmd.exact == False
github mathLab / PyDMD / tests / test_dmdbase.py View on Github external
def test_opt_default(self):
        dmd = DMDBase()
        assert dmd.opt == False
github mathLab / PyDMD / tests / test_dmdbase.py View on Github external
def test_tlsq_rank(self):
        dmd = DMDBase(tlsq_rank=2)
        assert dmd.tlsq_rank == 2
github mathLab / PyDMD / tests / test_dmdbase.py View on Github external
def test_plot_snaps_2D(self):
        dmd = DMDBase()
        with self.assertRaises(ValueError):
            dmd.plot_snapshots_2D()
github mathLab / PyDMD / tests / test_dmdbase.py View on Github external
def test_tlsq_rank_default(self):
        dmd = DMDBase()
        assert dmd.tlsq_rank == 0
github mathLab / PyDMD / tests / test_dmdbase.py View on Github external
def test_svd_rank_default(self):
        dmd = DMDBase()
        assert dmd.svd_rank == 0
github mathLab / PyDMD / pydmd / fbdmd.py View on Github external
"""
Derived module from dmdbase.py for forward/backward dmd.
"""
import numpy as np

from scipy.linalg import sqrtm
from .dmdbase import DMDBase


class FbDMD(DMDBase):
    """
    Forward/backward DMD class.

    :param svd_rank: the rank for the truncation; If 0, the method computes the
        optimal rank and uses it for truncation; if positive interger, the
        method uses the argument for the truncation; if float between 0 and 1,
        the rank is the number of the biggest singular values that are needed
        to reach the 'energy' specified by `svd_rank`; if -1, the method does
        not compute truncation.
    :type svd_rank: int or float
    :param int tlsq_rank: rank truncation computing Total Least Square. Default
        is 0, that means TLSQ is not applied.
    :param bool exact: flag to compute either exact DMD or projected DMD.
        Default is False.
    :param bool opt: flag to compute optimal amplitudes. See :class:`DMDBase`.
        Default is False.
github mathLab / PyDMD / pydmd / mrdmd.py View on Github external
Reference:
- Kutz, J. Nathan, Xing Fu, and Steven L. Brunton. Multiresolution Dynamic Mode
Decomposition. SIAM Journal on Applied Dynamical Systems 15.2 (2016): 713-735.
"""
from __future__ import division
from builtins import range
from past.utils import old_div
import numpy as np
import scipy.linalg
import matplotlib.pyplot as plt

from .dmdbase import DMDBase


class MrDMD(DMDBase):
    """
    Multi-resolution Dynamic Mode Decomposition

    :param svd_rank: the rank for the truncation; If 0, the method computes the
        optimal rank and uses it for truncation; if positive interger, the
        method uses the argument for the truncation; if float between 0 and 1,
        the rank is the number of the biggest singular values that are needed
        to reach the 'energy' specified by `svd_rank`; if -1, the method does
        not compute truncation.
    :type svd_rank: int or float
    :param int tlsq_rank: rank truncation computing Total Least Square. Default
        is 0, that means TLSQ is not applied.
    :param bool exact: flag to compute either exact DMD or projected DMD.
        Default is False.
    :param bool opt: flag to compute optimal amplitudes. See :class:`DMDBase`.
        Default is False.
github mathLab / PyDMD / pydmd / dmdc.py View on Github external
"""
Derived module from dmdbase.py for dmd with control.

Reference:
- Proctor, J.L., Brunton, S.L. and Kutz, J.N., 2016. Dynamic mode decomposition
with control. SIAM Journal on Applied Dynamical Systems, 15(1), pp.142-161.
"""
from .dmdbase import DMDBase
from past.utils import old_div
import numpy as np


class DMDc(DMDBase):
    """
    Dynamic Mode Decomposition with control.
    This version does not allow to manipulate the temporal window within the
    system is reconstructed.

    :param svd_rank: the rank for the truncation; If 0, the method computes the
        optimal rank and uses it for truncation; if positive interger, the
        method uses the argument for the truncation; if float between 0 and 1,
        the rank is the number of the biggest singular values that are needed
        to reach the 'energy' specified by `svd_rank`; if -1, the method does
        not compute truncation.
    :type svd_rank: int or float
    :param int tlsq_rank: rank truncation computing Total Least Square. Default
        is 0, that means no truncation.
    :param bool opt: flag to compute optimal amplitudes. See :class:`DMDBase`.
        Default is False.