def simulation_rlc_cpp():
rlc = core.__deepcopy__()
# Define the simulation parameters
config = {
'fs': 48e3, # Sample rate
'gradient': 'discret', # in {'discret', 'theta', 'trapez'}
'theta': 0.5, # theta-scheme for the structure
'split': True, # apply core.split_linear() beforehand
'maxit': 10, # Max iteration for NL solvers
'numtol': 1e-16, # Global numerical tolerance
'path': None, # Path to the results folder
'progressbar': True, # Display a progress bar
'timer': True, # Display minimal timing infos
'language': 'python', # in {'python', 'c++'}
'cpp_build_and_run_script': None, # compile and exec binary
'eigen_path': None, # path to Eigen library
}
simu = PHSSimulation(rlc, config=config)
dur = 0.01
u = signalgenerator(which='sin', f0=800., tsig=dur, fs=simu.fs)
def sequ():
for el in u():
yield (el, )
simu.init(sequ=sequ(), nt=int(dur * simu.fs))
simu2cpp(simu)
return True
def plot_rlc_with_split():
# Define the simulation parameters
config = {
'fs': 48e3, # Sample rate
'gradient': 'discret', # in {'discret', 'theta', 'trapez'}
'theta': 0.5, # theta-scheme for the structure
'split': False, # apply core.split_linear() beforehand
'maxit': 10, # Max iteration for NL solvers
'numtol': 1e-16, # Global numerical tolerance
'path': None, # Path to the results folder
'progressbar': True, # Display a progress bar
'timer': True, # Display minimal timing infos
'language': 'python', # in {'python', 'c++'}
'cpp_build_and_run_script': None, # compile and exec binary
'eigen_path': None, # path to Eigen library
}
# retrieve the pyphs.PHSCore of a linear RLC from the examples
from pyphs.examples.rlc.rlc import core as rlc
print(rlc.w)
print(rlc.z)
simu = PHSSimulation(rlc, config=config)
dur = 0.01
u = signalgenerator(which='sin', f0=800., tsig=dur, fs=simu.fs)
def sequ():
for el in u():
yield (el, )
simu.init(sequ=sequ(), nt=int(dur * simu.fs))
simu.process()
print(simu.nums.method.core.w)
print(simu.nums.method.core.z)
dims = simu.nums.method.core.dims
# plot u, y
simu.data.plot([('u', i)
for i in range(dims.y())] + [('y', i)
for i in range(dims.y())],
show=False)
# plot w, z
simu.data.plot([('w', 0), ('z', 0)], show=False)
simu.data.plot([('dtx', i)
for i in range(dims.x())] + [('dxH', i)
for i in range(dims.x())],
show=False)
return True
def plot_power_balance_rlc_with_split():
# Define the simulation parameters
config = {
'fs': 48e3, # Sample rate
'gradient': 'discret', # in {'discret', 'theta', 'trapez'}
'theta': 0.5, # theta-scheme for the structure
'split': True, # apply core.split_linear() beforehand
'maxit': 10, # Max iteration for NL solvers
'numtol': 1e-16, # Global numerical tolerance
'path': None, # Path to the results folder
'progressbar': True, # Display a progress bar
'timer': True, # Display minimal timing infos
'language': 'python', # in {'python', 'c++'}
'cpp_build_and_run_script': None, # compile and exec binary
'eigen_path': None, # path to Eigen library
}
# retrieve the pyphs.PHSCore of a linear RLC from the examples
from pyphs.examples.rlc.rlc import core as rlc
rlc_ = rlc.__copy__()
rlc_.build_R()
simu = PHSSimulation(rlc_, config=config)
dur = 0.01
u = signalgenerator(which='sin', f0=800., tsig=dur, fs=simu.fs)
def sequ():
for el in u():
yield (el, )
simu.init(sequ=sequ(), nt=int(dur * simu.fs))
simu.process()
simu.data.plot_powerbal(mode='single', show=False)
simu.data.plot_powerbal(mode='multi', show=False)
return True
config = {'fs': 48e3, # Sample rate (Hz)
'grad': 'discret', # in {'discret', 'theta', 'trapez'}
'theta': 0.5, # theta-scheme for the structure
'split': False, # split implicit from explicit part
'maxit': 10, # Max number of iterations for NL solvers
'eps': 1e-16, # Global numerical tolerance
'path': None, # Path to the results folder
'pbar': False, # Display a progress bar
'timer': False, # Display minimal timing infos
'lang': 'python', # language in {'python', 'c++'}
'script': None, # call to C++ compiler and exec binary
'eigen': None, # path to Eigen C++ library
}
# Instantiate a pyphs.PHSSimulation object associated with a given core PHS
simu = PHSSimulation(core, config=config)
# def simulation time
tmax = 0.02
nmax = int(tmax*simu.fs)
t = [n/simu.fs for n in range(nmax)]
nt = len(t)
# def input signal
def sig(tn, mode='impact'):
freq = 1000.
amp = 1000.
if mode == 'sin':
pi = numpy.pi
sin = numpy.sin
netlist = PHSNetlist(netlist_filename)
graph = PHSGraph(netlist=netlist)
core = graph.buildCore()
if __name__ == '__main__':
config = {
'fs': 48e3,
'split': True,
'pbar': True,
'timer': True,
'path': path
}
simu = PHSSimulation(core, config=config)
dur = 0.01
u = signalgenerator(which='sin', f0=800., tsig=dur, fs=simu.fs)
def sequ():
for el in u():
yield (el, )
simu.init(sequ=sequ(), nt=int(dur * simu.fs))
simu.process()
simu.data.plot_powerbal(mode='multi')
simu.data.plot([('u', 0), ('x', 1), ('x', 0), ('dtx', 0), ('dxH', 2),
def simulation_nlcore_full():
# Define the simulation parameters
config = {
'fs': 48e3, # Sample rate
'grad': 'discret', # in {'discret', 'theta', 'trapez'}
'theta': 0.5, # theta-scheme for the structure
'split': False, # apply core.split_linear() beforehand
'maxit': 10, # Max number of iterations for NL solvers
'eps': 1e-16, # Global numerical tolerance
'path': None, # Path to the folder to save the results
'pbar': False, # Display a progress bar
'timer': False, # Display minimal timing infos
'lang': 'python', # in {'python', 'c++'}
'script': None, # call to compiler and exec binary
'eigen': None, # path to Eigen C++ linear algebra library
}
# Instantiate a pyphs.PHSSimulation object associated with a given core PHS
simu = PHSSimulation(nlcore, config=config)
# def simulation time
tmax = 0.02
nmax = int(tmax * simu.fs)
t = [n / simu.fs for n in range(nmax)]
nt = len(t)
# def input signal
def sig(tn, mode='impact'):
freq = 1000.
amp = 1000.
if mode == 'sin':
pi = numpy.pi
sin = numpy.sin
out = amp * sin(2 * pi * freq * tn)
elif mode == 'impact':
dur = 0.5 * 1e-3 # duration: 0.5ms
start = 0.001 # start at 1ms
out = amp if start <= tn < start + dur else 0.
elif mode == 'const':
out = 1.
return out
# def generator for sequence of inputs to feed in the PHSSimulation object
def sequ():
"""
generator of input sequence for PHSSimulation
"""
for tn in t:
u1 = sig(tn)
# !!! must be array with shape (core.dims.u(), )
yield numpy.array([
u1,
]) # numpy.array([u1, u2, ...])
# state initialization
# !!! must be array with shape (core.dims.x(), )
x0 = (0., 0.)
# Initialize the simulation
simu.init(sequ=sequ(), x0=x0, nt=nt)
# Proceed
simu.process()
return True
'pbar': True, # Display a progress bar
'timer': False, # Display minimal timing infos
'lang': 'python', # Language in {'python', 'c++'}
# 'script': None, # Call to C++ compiler and exec binary
# 'eigen': None, # Path to Eigen C++ library
# Options for the data reader. The data are read from index imin
# to index imax, rendering one element out of the number decim
'load': {
'imin': 0,
'imax': None,
'decim': 1
}
}
# Instantiate a pyphs.PHSSimulation object associated with a given core PHS
simu = PHSSimulation(core, config=config)
# def simulation time
tmax = 1e-2
nmax = int(tmax * simu.fs)
t = [n / simu.fs for n in range(nmax)]
nt = len(t)
# def input signal
def sig(tn, mode='sin'):
freq = 300.
amp = 1000.
if mode == 'sin':
pi = numpy.pi
sin = numpy.sin
