def plot_GraphAnalysis():
netlist = NetlistThieleSmallNL()
graph = Graph(netlist=netlist)
graph.to_core()
graph.analysis.plot(show=False)
os.remove(path)
return True
def __init__(self, label, edges, w, z, **kwargs):
if not hasattr(w, '__len__'):
w = [
w,
]
if not hasattr(z, '__len__'):
z = [
z,
]
assert len(w) == len(z),\
'len(z)={0!s} is not equal to len(w)={1!s}.'.format(len(z), len(w))
# init PortHamiltonianObject
Graph.__init__(self, label=label)
# build correspondance between labels in subs and pars (dicpars)...
# ... and build the correspondance between symbols and subs (subs)
dicpars, subs = mappars(self, **kwargs)
# update dict of subs in phs
self.core.subs.update(subs)
# replace parameters in z by correspondances in 'dicpars'
for i, zz in enumerate(z):
z[i] = zz.subs(dicpars)
for e, edge in enumerate(edges):
if 'z' in edge[2].keys():
for k in ['e_ctrl', 'f_ctrl']:
edges[e][2]['z'][k] = edge[2]['z'][k].subs(dicpars)
# add dissipative component
self.core.add_dissipations(w, z)
# update phs.Graph with edges
self.add_edges_from(edges)
def split_sp():
netlist = NetlistThieleSmallNL()
graph = Graph(netlist=netlist)
print(graph.edges(data=True))
graph.split_sp()
os.remove(path)
return True
def split_sp():
netlist = NetlistThieleSmallNL()
graph = Graph(netlist=netlist)
print(graph.edges(data=True))
graph.split_sp()
os.remove(path)
return True
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if not isinstance(kwargs['value'], Argument):
coeff = Argument(label + 'coeff', kwargs['value'])
else:
coeff = kwargs['value']
x = nicevarlabel("x", label)
x = self.core.symbols(x)
if kwargs['inv_coeff']:
coeff.symb = coeff.symb**-1
H = coeff.symb * x**2 / 2.
self.core.add_storages([x], H)
edge_data_dic = {
'label': x,
'type': 'storage',
'ctrl': kwargs['ctrl'],
'link': None
}
edge = (nodes[0], nodes[1], edge_data_dic)
self.add_edges_from([edge])
self.core.subs.update(coeff.sub)
if len(coeff.sub) == 0 and kwargs['inv_coeff']:
self.core.p += [
coeff.symb**-1,
]
elif len(coeff.sub) == 0:
self.core.p += [
coeff.symb,
]
def plot_GraphAnalysis():
netlist = NetlistThieleSmallNL()
graph = Graph(netlist=netlist)
graph.buildCore()
graph.analysis.plot(show=False)
os.remove(path)
return True
def __init__(self, label, edges, w, z, **kwargs):
if not hasattr(w, '__len__'):
w = [w, ]
if not hasattr(z, '__len__'):
z = [z, ]
assert len(w) == len(z),\
'len(z)={0!s} is not equal to len(w)={1!s}.'.format(len(z), len(w))
# init PortHamiltonianObject
Graph.__init__(self, label=label)
# build correspondance between labels in subs and pars (dicpars)...
# ... and build the correspondance between symbols and subs (subs)
dicpars, subs = mappars(self, **kwargs)
# update dict of subs in phs
self.core.subs.update(subs)
# replace parameters in z by correspondances in 'dicpars'
for i, zz in enumerate(z):
z[i] = zz.subs(dicpars)
for e, edge in enumerate(edges):
if 'z' in edge[2].keys():
for k in ['e_ctrl', 'f_ctrl']:
edges[e][2]['z'][k] = edge[2]['z'][k].subs(dicpars)
# add dissipative component
self.core.add_dissipations(w, z)
# update phs.Graph with edges
self.add_edges_from(edges)
def __init__(self, label, nodes, **kwargs):
# update default parameters
parameters = {'ctrl': '?', 'const': None}
parameters.update(kwargs)
Graph.__init__(self, label=label)
# set starting node to datum if not provided
if nodes.__len__() == 1:
node1 = datum
node2 = nodes[0]
elif nodes.__len__() == 2:
node1 = nodes[0]
node2 = nodes[1]
# define symbols
u, y = symbols((nicevarlabel('u', label),
nicevarlabel('y', label)))
# add port to phs
self.core.add_ports([u], [y])
# check edge control type (dual of input control type in values[0])
assert parameters['ctrl'] in ('e', 'f', '?')
# define edge data
edge_data = {'label': y,
'type': 'port',
'ctrl': parameters['ctrl'],
'link': None}
# add edge to phs.Graph
self.add_edges_from([(node1, node2, edge_data)])
# check if constant value is provided
if parameters['const'] is not None:
self.core.subs.update({u: parameters['const']})
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if not isinstance(kwargs['coeff'], Argument):
coeff = Argument(label + 'coeff', kwargs['coeff'])
else:
coeff = kwargs['coeff']
w_label = nicevarlabel("w", label)
w = self.core.symbols(w_label)
z_f_ctrl = coeff.symb * w
z_e_ctrl = w / coeff.symb
if 'inv_coeff' in kwargs and kwargs['inv_coeff']:
z_f_ctrl, z_e_ctrl = z_e_ctrl, z_f_ctrl
self.core.add_dissipations([w], [z_f_ctrl])
edge_data_dic = {
'label': w,
'type': 'dissipative',
'ctrl': '?',
'z': {
'e_ctrl': z_e_ctrl,
'f_ctrl': z_f_ctrl
},
'link': None
}
edge = (nodes[0], nodes[1], edge_data_dic)
self.add_edges_from([edge])
self.core.subs.update(coeff.sub)
if len(coeff.sub) == 0:
self.core.p += [
coeff.symb,
]
def __init__(self, label, edges, **kwargs):
# init PortHamiltonianObject
Graph.__init__(self, label=label)
# build correspondance between labels in subs and pars (dicpars)...
# ... and build the correspondance between symbols and subs (subs)
dicpars, subs = mappars(self, **kwargs)
# update dict of subs in phs
self.core.subs.update(subs)
# update phs.Graph with edges
self.add_edges_from(edges)
def TestCore2Tex():
netlist = NetlistThieleSmallNL()
graph = Graph(netlist=netlist)
core = graph.to_core()
content = netlist2tex(netlist)
content += graphplot2tex(graph)
content += core2tex(core)
texdocument(content, path, title='test core2tex')
os.remove(path)
return True
def __init__(self, label, nodes, **kwargs):
# instanciate a Graph object
Graph.__init__(self, label=label)
path = kwargs.pop('file')
data = np.vstack(map(np.array, data_generator(path)))
w_vals = data[0, :]
z_vals = data[1, :]
assert all(z_vals[np.nonzero(w_vals >= 0)] >= 0), 'All values z(w) for\
w>=0 must be non-negative (component {})'.format(label)
assert all(z_vals[np.nonzero(w_vals < 0)] < 0), 'All values z(w) for\
w<0 must be negative (component {})'.format(label)
assert all(z_vals[np.nonzero(w_vals == 0)] == 0), 'z(0) must be zero \
(component {})'.format(label)
assert all(np.diff(z_vals) > 0), "z'(0) must be positive\
(component {})".format(label)
ctrl = kwargs.pop('ctrl')
# state variable
w = symbols("w" + label)
# dissipative funcion
z = pwl_func(w_vals, z_vals, w, **kwargs)
if ctrl == 'e':
not_ctrl = 'f'
else:
assert ctrl == 'f'
not_ctrl = 'e'
# edge data
data = {
'label': w,
'type': 'dissipative',
'ctrl': ctrl,
'z': {
ctrl + '_ctrl': z,
not_ctrl + '_ctrl': sp.sympify(0)
},
'link': None
}
N1, N2 = nodes
# edge
edge = (N1, N2, data)
# init component
self += edges.DissipativeNonLinear(label, [
edge,
], w, z, **kwargs)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
pars = parameters_JSV2016()
pars.update(kwargs)
Ccoil = float(pars.pop('Ccoil'))
Ncoil = float(pars.pop('Ncoil'))
# remove H0
pars.pop('H0')
dicpars, subs = mappars(self, **pars)
# parameters
pars = ['Rb', 'Rp', 'Lh', 'Lv']
Rb, Rp, Lh, Lv = self.core.symbols(pars)
# nodes
MASS, ELEC1, ELEC2 = nodes
NMagnet = 'N' + label + 'Magnet'
NCcoil = 'N' + label + 'Ccoil'
self += Source(
label + 'Magnet',
(self.datum, NMagnet),
**{
'type': 'mmf',
# 'const': H0,
})
MASS_obs = Observerec(label + 'OBS', (self.datum, MASS))
self += MASS_obs
q, dtq = MASS_obs.core.o()
def f(q, dtq):
"""
cf JSV Rhodes eq (25)
set dmu = (murel-1)/(murel + 1) to 1
"""
dmu = 1
f1 = (q - Rp + Lv)**2 + Lh**2
f2 = (q + Rp + Lv)**2 + Lh**2
return 2 * Rb**2 * dmu * Rp * ((f1 - 2 * Lh**2) / f1**2 -
(f2 - 2 * Lh**2) / f2**2) * dtq
falpha = (f(q, dtq)**-1).subs(dicpars)
self += Gyrator(label + 'MecToMag',
(self.datum, NCcoil, self.datum, NMagnet),
alpha=(label + 'f', falpha))
self += Capacitor(label + 'Ccoil', (self.datum, NCcoil), C=Ccoil)
self += Gyrator(label + 'MagToElec',
(self.datum, NCcoil, ELEC1, ELEC2),
alpha=(label + 'Ncoil', Ncoil))
self.core.subs.update(subs)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
pars = parameters_JSV2016()
pars.update(kwargs)
Ccoil = float(pars.pop('Ccoil'))
Ncoil = float(pars.pop('Ncoil'))
# remove H0
pars.pop('H0')
dicpars, subs = mappars(self, **pars)
# parameters
pars = ['Rb', 'Rp', 'Lh', 'Lv']
Rb, Rp, Lh, Lv = self.core.symbols(pars)
# nodes
MASS, ELEC1, ELEC2 = nodes
NMagnet = 'N' + label + 'Magnet'
NCcoil = 'N' + label + 'Ccoil'
self += Source(label+'Magnet',
(self.datum, NMagnet),
**{'type': 'mmf',
# 'const': H0,
})
MASS_obs = Observerec(label+'OBS', (self.datum, MASS))
self += MASS_obs
q, dtq = MASS_obs.core.o()
def f(q, dtq):
"""
cf JSV Rhodes eq (25)
set dmu = (murel-1)/(murel + 1) to 1
"""
dmu = 1
f1 = (q - Rp + Lv)**2 + Lh**2
f2 = (q + Rp + Lv)**2 + Lh**2
return 2*Rb**2*dmu*Rp*((f1-2*Lh**2)/f1**2 -
(f2-2*Lh**2)/f2**2) * dtq
falpha = (f(q, dtq)**-1).subs(dicpars)
self += Gyrator(label+'MecToMag',
(self.datum, NCcoil, self.datum, NMagnet),
alpha=(label+'f', falpha))
self += Capacitor(label+'Ccoil',
(self.datum, NCcoil),
C=Ccoil)
self += Gyrator(label+'MagToElec',
(self.datum, NCcoil, ELEC1, ELEC2),
alpha=(label+'Ncoil', Ncoil))
self.core.subs.update(subs)
def __init__(self, label, edges, x, H, **kwargs):
# init PortHamiltonianObject
Graph.__init__(self, label=label)
# build correspondance between labels in subs and pars (dicpars)...
# ... and build the correspondance between symbols and subs (subs)
dicpars, subs = mappars(self, **kwargs)
# update dict of subs in phs
self.core.subs.update(subs)
# replace parameters in H by correspondances in 'dicpars'
H = H.subs(dicpars)
# add dissipative component
self.core.add_storages(x, H)
# update phs.Graph with edges
self.add_edges_from(edges)
def TestCore2Tex():
netlist = NetlistThieleSmallNL()
graph = Graph(netlist=netlist)
core = graph.to_core()
folder = os.path.join(here, 'temp')
if not os.path.exists(folder):
os.mkdir(folder)
path = os.path.join(folder, 'test_core2tex.tex')
content = netlist2tex(netlist)
content += graphplot2tex(graph, folder=folder)
content += core2tex(core)
texdocument(content, path, title='test core2tex')
shutil.rmtree(folder)
return True
def __init__(self, label, edges, x, H, **kwargs):
# init PortHamiltonianObject
Graph.__init__(self, label=label)
# build correspondance between labels in subs and pars (dicpars)...
# ... and build the correspondance between symbols and subs (subs)
dicpars, subs = mappars(self, **kwargs)
# update dict of subs in phs
self.core.subs.update(subs)
# replace parameters in H by correspondances in 'dicpars'
H = H.subs(dicpars)
# add dissipative component
self.core.add_storages(x, H)
# update phs.Graph with edges
self.add_edges_from(edges)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
dic = {
'A': 1e2, # [N.s/m] Felt damping coefficient
'B': 2.5, # [#] Hysteresis coefficient for the felt
'F': 13.8, # [N/m] Elastic characteristic force
'L': 1.5 * 1e-2, # [m] Height of the felt at rest
}
dic.update(kwargs)
dicpars, subs = mappars(self, **dic)
# parameters
pars = ['L', 'F', 'A', 'B']
L, F, A, B = symbols(pars)
N1, N2 = nodes
xnl = symbols('q' + label)
hnl = sp.Piecewise((0., xnl <= 0.),
((L * F / (B + 1)) * (xnl / L)**(B + 1), True))
hnl = hnl.subs(dicpars)
# edge data
data = {'label': xnl, 'type': 'storage', 'ctrl': 'e', 'link': None}
self.add_edges_from([
(N1, N2, data),
])
self.core.add_storages(xnl, hnl)
r = sp.Piecewise((0., xnl <= 0.),
((A * L / B) * (xnl / L)**(B - 1), True))
r = r.subs(dicpars)
wnl = symbols('dtq' + label)
# edge data
data = {
'label': wnl,
'type': 'dissipative',
'ctrl': 'e',
'z': {
'e_ctrl': r * wnl,
'f_ctrl': sp.sympify(0)
},
'link': None
}
self.add_edges_from([
(N1, N2, data),
])
self.core.add_dissipations(wnl, r * wnl)
self.core.subs.update(subs)
def __init__(self, label, nodes, **kwargs):
# instanciate a Graph object
Graph.__init__(self, label=label)
assert 'file' in kwargs, "pwl.storage component need 'file' argument"
path = kwargs.pop('file')
vals = np.vstack(map(np.array, data_generator(path)))
x_vals = vals[0, :]
h_vals = vals[1, :]
assert all(h_vals[np.nonzero(x_vals >= 0)] >= 0), 'All values h(x) for\
x>=0 must be non-negative (component {})'.format(label)
if kwargs['integ']:
assert all(h_vals[np.nonzero(x_vals < 0)] < 0), 'All values dxh(x)\
for x<0 must be negative (component {})'.format(label)
else:
assert all(h_vals[np.nonzero(x_vals < 0)] >= 0), 'All values h(x)\
for x<0 must be non-negative (component {})'.format(label)
assert h_vals[np.nonzero(x_vals == 0)] == 0, 'dxh(0) and h(0) must be \
zero (component {})'.format(label)
ctrl = kwargs.pop('ctrl')
# state variable
x = symbols("x" + label)
# storage funcion
h = pwl_func(x_vals, h_vals, x, **kwargs)
# edge data
data = {
'label': x,
'type': 'storage',
'ctrl': ctrl,
'file': path,
'link': None
}
N1, N2 = nodes
# edge
edge = (N1, N2, data)
# init component
self += edges.StorageNonLinear(label, [edge], x, h, **kwargs)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'alpha' not in kwargs:
alpha = 0.5
else:
alpha = kwargs.pop('alpha')
diagR, diagQ = fractionalDifferenciatorWeights(p, alpha, **kwargs)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
Ndeb, Nend = nodes
N1 = Ndeb
for n in range(nbPoles):
if n < nbPoles-1:
N2 = 'N'+label+str(n)+"_1"
else:
N2 = Nend
Rn = diagR[n] # here, diagR[n] is a res (flux-controlled)
self += DissipativeLinear(label+'R'+str(n),
(N2, N1),
ctrl='f',
coeff=Rn,
inv_coef=False)
Qn = diagQ[n]
N3 = 'N'+label+str(n)+"_2"
self += StorageLinear(label+'Q'+str(n),
(N3, datum),
value=Qn,
inv_coeff=False,
ctrl='e')
Nend = nodes[1]
self += Transformer(label+'alpha'+str(n),
(N1, N2, N3, datum),
alpha=Rn)
N1 = N2
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
parameters = parametersDefault(self.metadata['parameters'])
parameters.update(kwargs)
dicpars, subs = mappars(self, **parameters)
# parameters
pars = ['L', 'F', 'A', 'B']
L, F, A, B = symbols(pars)
N1, N2 = nodes
xnl = symbols('q' + label)
hnl = sp.Piecewise((0., xnl <= 0.),
((L * F / (B + 1)) * (xnl / L)**(B + 1), True))
hnl = hnl.subs(dicpars)
# edge data
data = {'label': xnl, 'type': 'storage', 'ctrl': 'e', 'link': None}
self.add_edges_from([
(N1, N2, data),
])
self.core.add_storages(xnl, hnl)
r = sp.Piecewise((0., xnl <= 0.),
((A * L / B) * (xnl / L)**(B - 1), True))
r = r.subs(dicpars)
wnl = symbols('dtq' + label)
# edge data
data = {
'label': wnl,
'type': 'dissipative',
'ctrl': 'e',
'z': {
'e_ctrl': r * wnl,
'f_ctrl': sp.sympify(0)
},
'link': None
}
self.add_edges_from([
(N1, N2, data),
])
self.core.add_dissipations(wnl, r * wnl)
self.core.subs.update(subs)
def __init__(self, label, nodes, **kwargs):
# instanciate a Graph object
Graph.__init__(self, label=label)
assert 'file' in kwargs, "pwl.storage component need 'file' argument"
path = kwargs.pop('file')
vals = np.vstack(map(np.array, data_generator(path)))
x_vals = vals[0, :]
h_vals = vals[1, :]
assert all(h_vals[np.nonzero(x_vals >= 0)] >= 0), 'All values h(x) for\
x>=0 must be non-negative (component {})'.format(label)
if kwargs['integ']:
assert all(h_vals[np.nonzero(x_vals < 0)] < 0), 'All values dxh(x)\
for x<0 must be negative (component {})'.format(label)
else:
assert all(h_vals[np.nonzero(x_vals < 0)] >= 0), 'All values h(x)\
for x<0 must be non-negative (component {})'.format(label)
assert h_vals[np.nonzero(x_vals == 0)] == 0, 'dxh(0) and h(0) must be \
zero (component {})'.format(label)
ctrl = kwargs.pop('ctrl')
# state variable
x = symbols("x"+label)
# storage funcion
h = pwl_func(x_vals, h_vals, x, **kwargs)
# edge data
data = {'label': x,
'type': 'storage',
'ctrl': ctrl,
'link': None}
N1, N2 = nodes
# edge
edge = (N1, N2, data)
# init component
self += edges.StorageNonLinear(label, [edge], x, h, **kwargs)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'alpha' not in kwargs:
alpha = 0.5
else:
alpha = kwargs.pop('alpha')
diagR, diagQ = fractionalDifferenciatorWeights(p, alpha, **kwargs)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
Ndeb, Nend = nodes
for n in range(nbPoles):
Rn = diagR[n] # here, diagR[n] is a conductance (e-ctrl)
N1 = 'N'+label+str(n)+"_1"
N2 = 'N'+label+str(n)+"_2"
self += DissipativeLinear(label+'R'+str(n),
(N1, Ndeb),
inv_coeff=True,
coeff=Rn,
ctrl='e')
Qn = diagQ[n]
self += StorageLinear(label+'Q'+str(n),
(N2, datum),
value=Qn,
ctrl='f',
inv_coeff=False)
self += Transformer(label+'alpha'+str(n),
(N1, Nend, N2, datum),
alpha=Rn**-1)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'alpha' not in kwargs:
alpha = 0.5
else:
alpha = kwargs.pop('alpha')
diagR, diagQ = fractionalDifferenciatorWeights(p, alpha, **kwargs)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
Ndeb, Nend = nodes
N1 = Ndeb
for n in range(nbPoles):
if n < nbPoles - 1:
N2 = 'N' + label + str(n) + "_1"
else:
N2 = Nend
Rn = diagR[n] # here, diagR[n] is a res (flux-controlled)
self += DissipativeLinear(label + 'R' + str(n), (N2, N1),
ctrl='f',
coeff=Rn,
inv_coef=False)
Qn = diagQ[n]
N3 = 'N' + label + str(n) + "_2"
self += StorageLinear(label + 'Q' + str(n), (N3, datum),
value=Qn,
inv_coeff=False,
ctrl='e')
Nend = nodes[1]
self += Transformer(label + 'alpha' + str(n), (N1, N2, N3, datum),
alpha=Rn)
N1 = N2
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'beta' not in kwargs:
beta = 0.5
else:
beta = kwargs.pop('beta')
self.core.subs.update({self.core.symbols('p_'+label): p,
self.core.symbols('beta_'+label): beta})
diagRmu, diagQmu = fractionalIntegratorWeights(p, beta, **kwargs)
# Truncation of poles with null Q
nbPoles = diagRmu.__len__()
for n in range(nbPoles):
Rn = diagRmu[n] # here, diagRmu[n] is a resistance (f-ctrl)
Nend = nodes[1]
Ncomp = 'iN_'+label + str(n)
comp = DissipativeLinear('R_'+label+str(n),
(Ncomp, Nend),
coeff=Rn,
ctrl='f')
self += comp
Qn = diagQmu[n]
Ndeb = nodes[0]
comp = StorageLinear(label+str(n),
(Ndeb, Ncomp),
value=Qn,
name='pL_',
inv_coeff=False,
ctrl='e')
self += comp
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'beta' not in kwargs:
beta = 0.5
else:
beta = kwargs.pop('beta')
self.core.subs.update({
self.core.symbols('p_' + label): p,
self.core.symbols('beta_' + label): beta
})
diagRmu, diagQmu = fractionalIntegratorWeights(p, beta, **kwargs)
# Truncation of poles with null Q
nbPoles = diagRmu.__len__()
for n in range(nbPoles):
Rn = diagRmu[n] # here, diagRmu[n] is a resistance (f-ctrl)
Nend = nodes[1]
Ncomp = 'iN_' + label + str(n)
comp = DissipativeLinear('R_' + label + str(n), (Ncomp, Nend),
coeff=Rn,
ctrl='f')
self += comp
Qn = diagQmu[n]
Ndeb = nodes[0]
comp = StorageLinear(label + str(n), (Ndeb, Ncomp),
value=Qn,
name='pL_',
inv_coeff=False,
ctrl='e')
self += comp
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'beta' not in kwargs:
beta = 0.5
else:
beta = kwargs.pop('beta')
diagR, diagQ = fractionalIntegratorWeights(p, beta, **kwargs)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
N, Nend = nodes
for n in range(nbPoles):
if n < nbPoles - 1:
Ncomp = 'iN_' + label + str(n) + 'to' + str(n + 1)
else:
Ncomp = Nend
nodes = (N, Ncomp)
# here, diagRmu[n] is a conductance (effort-controlled)
Rn = diagR[n]
self += DissipativeLinear(label + 'R' + str(n),
nodes,
coeff=Rn,
inv_coeff=True,
ctrl='e')
Qn = diagQ[n]
self += StorageLinear(label + 'Q' + str(n),
nodes,
value=Qn,
inv_coeff=False,
ctrl='f')
N = Ncomp
def __init__(self, label, nodes, **kwargs):
# init PortHamiltonianObject
Graph.__init__(self, label=label)
# pop connector type
connector_type = kwargs.pop('connector_type')
# build correspondance between labels in subs and pars (dicpars)...
# ... and build the correspondance between symbols and subs (subs)
dicpars, subs = mappars(self, **kwargs)
# update dict of subs in phs
self.core.subs.update(subs)
# replace parameters in alpha by correspondances in 'dicpars'
alpha = self.core.symbols('alpha')
alpha = alpha.subs(dicpars)
# symbols for inputs and outputs:
u1, u2 = self.core.symbols([nicevarlabel('u', label + str(el))
for el in (1, 2)])
y1, y2 = self.core.symbols([nicevarlabel('y', label + str(el))
for el in (1, 2)])
# add connector component
ny = self.core.dims.y()
self.core.add_ports((u1, u2), (y1, y2))
self.core.add_connector((ny, ny+1), alpha)
# update phs.Graph with edges
edge1_data = {'type': 'connector',
'connector_type': connector_type,
'alpha': alpha,
'ctrl': '?',
'label': y1,
'link': y2}
edge2_data = {'type': 'connector',
'connector_type': connector_type,
'alpha': None,
'ctrl': '?',
'label': y2,
'link': y1}
N1, N2, N3, N4 = nodes
edges = [(N1, N2, edge1_data), (N3, N4, edge2_data)]
# update phs.Graph with edges
self.add_edges_from(edges)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'beta' not in kwargs:
beta = 0.5
else:
beta = kwargs.pop('beta')
diagR, diagQ = fractionalIntegratorWeights(p, beta, **kwargs)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
N, Nend = nodes
for n in range(nbPoles):
if n < nbPoles-1:
Ncomp = 'iN_'+label + str(n) + 'to' + str(n+1)
else:
Ncomp = Nend
nodes = (N, Ncomp)
# here, diagRmu[n] is a conductance (effort-controlled)
Rn = diagR[n]
self += DissipativeLinear(label + 'R' + str(n),
nodes,
coeff=Rn,
inv_coeff=True,
ctrl='e')
Qn = diagQ[n]
self += StorageLinear(label + 'Q' + str(n),
nodes,
value=Qn,
inv_coeff=False,
ctrl='f')
N = Ncomp
def __init__(self, label, nodes, **kwargs):
# instanciate a Graph object
Graph.__init__(self, label=label)
assert 'file' in kwargs, "pwl.dissipative component need 'file' argument"
path = kwargs.pop('file')
data = np.vstack(map(np.array, data_generator(path)))
w_vals = data[0, :]
z_vals = data[1, :]
assert all(z_vals[np.nonzero(w_vals >= 0)] >= 0), 'All values z(w) for\
w>=0 must be non-negative (component {})'.format(label)
assert all(z_vals[np.nonzero(w_vals >= 0)] >= 0), 'All values z(w) for\
w<0 must be negative (component {})'.format(label)
assert all(z_vals[np.nonzero(w_vals == 0)] == 0), 'z(0) must be zero \
(component {})'.format(label)
ctrl = kwargs.pop('ctrl')
# state variable
w = symbols("w" + label)
# storage funcion
z = pwl_func(w_vals, z_vals, w, **kwargs)
# edge data
data = {'label': w, 'type': 'dissipative', 'ctrl': ctrl, 'link': None}
N1, N2 = nodes
# edge
edge = (N1, N2, data)
# init component
self += edges.DissipativeNonLinear(label, [
edge,
], w, z, **kwargs)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
dic = {'A': 1e2, # [N.s/m] Felt damping coefficient
'B': 2.5, # [#] Hysteresis coefficient for the felt
'F': 13.8, # [N/m] Elastic characteristic force
'L': 1.5*1e-2, # [m] Height of the felt at rest
}
dic.update(kwargs)
dicpars, subs = mappars(self, **dic)
# parameters
pars = ['L', 'F', 'A', 'B']
L, F, A, B = symbols(pars)
N1, N2 = nodes
xnl = symbols('q'+label)
hnl = sp.Piecewise((0., xnl <= 0.), ((L*F/(B+1))*(xnl/L)**(B+1), True))
hnl = hnl.subs(dicpars)
# edge data
data = {'label': xnl,
'type': 'storage',
'ctrl': 'e',
'link': None}
self.add_edges_from([(N1, N2, data), ])
self.core.add_storages(xnl, hnl)
r = sp.Piecewise((0., xnl <= 0.), ((A * L/B)*(xnl/L)**(B-1), True))
r = r.subs(dicpars)
wnl = symbols('dtq'+label)
# edge data
data = {'label': wnl,
'type': 'dissipative',
'ctrl': 'e',
'z': {'e_ctrl': r*wnl, 'f_ctrl': sp.sympify(0)},
'link': None}
self.add_edges_from([(N1, N2, data), ])
self.core.add_dissipations(wnl, r*wnl)
self.core.subs.update(subs)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if 'p' not in kwargs:
p = 1
else:
p = kwargs.pop('p')
if 'alpha' not in kwargs:
alpha = 0.5
else:
alpha = kwargs.pop('alpha')
diagR, diagQ = fractionalDifferenciatorWeights(p, alpha, **kwargs)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
Ndeb, Nend = nodes
for n in range(nbPoles):
Rn = diagR[n] # here, diagR[n] is a conductance (e-ctrl)
N1 = 'N' + label + str(n) + "_1"
N2 = 'N' + label + str(n) + "_2"
self += DissipativeLinear(label + 'R' + str(n), (N1, Ndeb),
inv_coeff=True,
coeff=Rn,
ctrl='e')
Qn = diagQ[n]
self += StorageLinear(label + 'Q' + str(n), (N2, datum),
value=Qn,
ctrl='f',
inv_coeff=False)
self += Transformer(label + 'alpha' + str(n),
(N1, Nend, N2, datum),
alpha=Rn**-1)
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
parameters = parametersDefault(self.metadata['parameters'])
parameters.update(kwargs)
g = parameters.pop('g')
alpha = parameters.pop('alpha')
diagR, diagQ = fractionalDifferenciatorWeights(g, alpha, **parameters)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
Ndeb, Nend = nodes
N1 = Ndeb
for n in range(nbPoles):
if n < nbPoles - 1:
N2 = 'N' + label + str(n) + "_1"
else:
N2 = Nend
Rn = diagR[n] # here, diagR[n] is a res (flux-controlled)
self += DissipativeLinear(label + 'R' + str(n), (N2, N1),
ctrl='f',
coeff=Rn,
inv_coef=False)
Qn = diagQ[n]
N3 = 'N' + label + str(n) + "_2"
self += StorageLinear(label + 'Q' + str(n), (N3, datum),
value=Qn,
inv_coeff=False,
ctrl='e')
Nend = nodes[1]
self += Transformer(label + 'alpha' + str(n), (N1, N2, N3, datum),
alpha=Rn)
N1 = N2
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if not isinstance(kwargs['value'], Argument):
coeff = Argument(label + 'coeff', kwargs['value'])
else:
coeff = kwargs['value']
x = nicevarlabel("x", label)
x = self.core.symbols(x)
if kwargs['inv_coeff']:
coeff.symb = coeff.symb**-1
H = coeff.symb * x**2/2.
self.core.add_storages([x], H)
edge_data_dic = {'label': x,
'type': 'storage',
'ctrl': kwargs['ctrl'],
'link': None}
edge = (nodes[0], nodes[1], edge_data_dic)
self.add_edges_from([edge])
self.core.subs.update(coeff.sub)
if len(coeff.sub) == 0 and kwargs['inv_coeff']:
self.core.p += [coeff.symb**-1, ]
elif len(coeff.sub) == 0:
self.core.p += [coeff.symb, ]
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
if not isinstance(kwargs['coeff'], Argument):
coeff = Argument(label + 'coeff', kwargs['coeff'])
else:
coeff = kwargs['coeff']
w_label = nicevarlabel("w", label)
w = self.core.symbols(w_label)
z_f_ctrl = coeff.symb*w
z_e_ctrl = w/coeff.symb
if 'inv_coeff' in kwargs and kwargs['inv_coeff']:
z_f_ctrl, z_e_ctrl = z_e_ctrl, z_f_ctrl
self.core.add_dissipations([w], [z_f_ctrl])
edge_data_dic = {'label': w,
'type': 'dissipative',
'ctrl': '?',
'z': {'e_ctrl': z_e_ctrl, 'f_ctrl': z_f_ctrl},
'link': None}
edge = (nodes[0], nodes[1], edge_data_dic)
self.add_edges_from([edge])
self.core.subs.update(coeff.sub)
if len(coeff.sub) == 0:
self.core.p += [coeff.symb, ]
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
parameters = parametersDefault(self.metadata['parameters'])
parameters.update(kwargs)
g = parameters.pop('g')
beta = parameters.pop('beta')
diagR, diagQ = fractionalIntegratorWeights(g, beta, **parameters)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
N, Nend = nodes
for n in range(nbPoles):
if n < nbPoles - 1:
Ncomp = 'iN_' + label + str(n) + 'to' + str(n + 1)
else:
Ncomp = Nend
nodes = (N, Ncomp)
# here, diagRmu[n] is a conductance (effort-controlled)
Rn = diagR[n]
self += DissipativeLinear(label + 'R' + str(n),
nodes,
coeff=Rn,
inv_coeff=True,
ctrl='e')
Qn = diagQ[n]
self += StorageLinear(label + 'Q' + str(n),
nodes,
value=Qn,
inv_coeff=False,
ctrl='f')
N = Ncomp
def __init__(self, label, nodes, **kwargs):
Graph.__init__(self, label=label)
parameters = parametersDefault(self.metadata['parameters'])
parameters.update(kwargs)
g = parameters.pop('g')
beta = parameters.pop('beta')
self.core.subs.update({
self.core.symbols('g_' + label): g,
self.core.symbols('beta_' + label): beta
})
diagRmu, diagQmu = fractionalIntegratorWeights(g, beta, **parameters)
# Truncation of poles with null Q
nbPoles = diagRmu.__len__()
for n in range(nbPoles):
Rn = diagRmu[n] # here, diagRmu[n] is a resistance (f-ctrl)
Nend = nodes[1]
Ncomp = 'iN_' + label + str(n)
comp = DissipativeLinear('R_' + label + str(n), (Ncomp, Nend),
coeff=Rn,
ctrl='f')
self += comp
Qn = diagQmu[n]
Ndeb = nodes[0]
comp = StorageLinear(label + str(n), (Ndeb, Ncomp),
value=Qn,
name='pL_',
inv_coeff=False,
ctrl='e')
self += comp
def __init__(self, label, nodes, **kwargs):
parameters = parametersDefault(self.metadata['parameters'])
parameters.update(kwargs)
Graph.__init__(self, label=label)
g = parameters.pop('g')
alpha = parameters.pop('alpha')
diagR, diagQ = fractionalDifferenciatorWeights(g, alpha, **parameters)
# Truncation of poles with null Q
nbPoles = diagR.__len__()
Ndeb, Nend = nodes
for n in range(nbPoles):
Rn = diagR[n] # here, diagR[n] is a conductance (e-ctrl)
N1 = 'N' + label + str(n) + "_1"
N2 = 'N' + label + str(n) + "_2"
self += DissipativeLinear(label + 'R' + str(n), (N1, Ndeb),
inv_coeff=True,
coeff=Rn,
ctrl='e')
Qn = diagQ[n]
self += StorageLinear(label + 'Q' + str(n), (N2, datum),
value=Qn,
ctrl='f',
inv_coeff=False)
self += Transformer(label + 'alpha' + str(n),
(N1, Nend, N2, datum),
alpha=Rn**-1)
"""
from __future__ import absolute_import, division, print_function
import os
from pyphs import Netlist, Graph
label = 'triodeamp'
path = os.path.realpath(__file__)[:os.path.realpath(__file__).rfind(os.sep)]
netlist_filename = path + os.sep + label + '.net'
netlist = Netlist(netlist_filename)
graph = Graph(netlist=netlist)
core = graph.to_core(verbose=False)
core.linear_nonlinear()
core.subsinverse()
#core.reduce_z()
#if __name__ == '__main__':
#
# from pyphs import signalgenerator
#
# config = {'fs': 96e3,
# 'split': True,
# 'pbar': True,
# 'maxit': 100,
"""
Created on Sat Jan 14 11:50:23 2017
@author: Falaize
"""
from __future__ import absolute_import, division, print_function
import os
from pyphs import Netlist, Graph
label = 'mka_dual'
path = os.path.realpath(__file__)[:os.path.realpath(__file__).rfind(os.sep)]
netlist_filename = path + os.sep + label + '.net'
netlist = Netlist(netlist_filename)
graph = Graph(netlist=netlist)
core = graph.buildCore()
#if __name__ == '__main__':
#
# from pyphs import Simulation, signalgenerator
# import numpy as np
#
#
# tsig = 0.01
# fs = 48000.
#
# config = {'fs': 48e3,
# 'progressbar': True,
# }
# simu = Simulation(core, config)
from __future__ import absolute_import, division, print_function import os from pyphs import Netlist, Graph # --------------------------- NETLIST ------------------------------------- # label = 'piano_hammer' this_script = os.path.realpath(__file__) here = this_script[:this_script.rfind(os.sep)] netlist_filename = here + os.sep + label + '.net' netlist = Netlist(netlist_filename) # --------------------------- GRAPH --------------------------------------- # graph = Graph(netlist=netlist) # --------------------------- CORE ---------------------------------------- # core = graph.to_core() ## --------------------------- SIMULATION ---------------------------------- # #if __name__ == '__main__': # # import numpy # import matplotlib.pyplot as plt # from pyphs import Simulation # # core.reduce_z() #
""" from __future__ import absolute_import, division, print_function import os from pyphs import Netlist, Graph # --------------------------- NETLIST ------------------------------------- # label = 'pickup' this_script = os.path.realpath(__file__) here = this_script[:this_script.rfind(os.sep)] netlist_filename = here + os.sep + label + '.net' netlist = Netlist(netlist_filename) # --------------------------- GRAPH --------------------------------------- # graph = Graph(netlist=netlist, label=label) # --------------------------- CORE ---------------------------------------- # core = graph.buildCore() ## --------------------------- SIMULATION ---------------------------------- # #if __name__ == '__main__': # # import numpy # import matplotlib.pyplot as plt # from pyphs import Netlist, Graph # from pyphs.misc.tools import interleave # # core.reduce_z() # # # Define the simulation parameters
"""
from __future__ import absolute_import, division, print_function
import os
from pyphs import Netlist, Graph
# --------------------------- NETLIST ------------------------------------- #
label = 'piano_hammer'
this_script = os.path.realpath(__file__)
here = this_script[:this_script.rfind(os.sep)]
netlist_filename = here + os.sep + label + '.net'
netlist = Netlist(netlist_filename)
# --------------------------- GRAPH --------------------------------------- #
graph = Graph(netlist=netlist)
# --------------------------- CORE ---------------------------------------- #
core = graph.to_core()
## --------------------------- SIMULATION ---------------------------------- #
#if __name__ == '__main__':
#
# import numpy
# import matplotlib.pyplot as plt
# from pyphs import Simulation
#
# core.reduce_z()
#
# # Define the simulation parameters
# config = {'fs': 48e3, # Sample rate (Hz)
from __future__ import absolute_import, division, print_function
import os
from pyphs import Netlist, Graph
label = 'triodeamp'
path = os.path.realpath(__file__)[:os.path.realpath(__file__).rfind(os.sep)]
netlist_filename = path + os.sep + label + '.net'
netlist = Netlist(netlist_filename)
graph = Graph(netlist=netlist)
core = graph.to_core(verbose=False)
core.linear_nonlinear()
core.subsinverse()
#core.reduce_z()
#if __name__ == '__main__':
#
# from pyphs import signalgenerator
#
# config = {'fs': 96e3,
# 'split': True,
# 'pbar': True,
# 'maxit': 100,
def plot_Graph():
netlist = NetlistThieleSmallNL()
graph = Graph(netlist=netlist)
graph.plot(show=False)
os.remove(path)
return True
def __init__(self, label, nodes, **kwargs):
pars = parameters_JSV2016()
for k in kwargs.keys():
if k not in pars.keys() and str(k)[0] not in 'zw':
raise AttributeError('parameter {} unknown'.format(k))
Graph.__init__(self, label=label)
pars.update(kwargs)
pars.update({
# [kg] Modal mass density
'Mb': pi*(pars['R']**2)*pars['M'],
# [N/m] Modal stiffness
'Kb': (pars['E']*pi*pars['R']**4.)/4.,
})
pars.update({
# [m] Tine length for the fondamental frequency f0[Hz]
'Lb': beamLength(pars['F'], pars['Kb'], pars['Mb'])
})
# [1/m] list of the nkmax first cantilever beam modes with length L
k, fk = waveNumbers(pars['N'], pars['Lb'], pars['Kb'], pars['Mb'])
# truncate below the Nyquist frequency fe/2
# list of the nk first modes below the Nyquist frequency fe/2 [1/m]
# k = k[(fk < pars['n']/2).nonzero()]
# list of the nk first frequencies below the Nyquist frequency fe/2 [Hz]
# fk = fk[(fk < pars['fs']/2).nonzero()]
# [#] number of simulated modes
pars.update({'kmodes': k,
'fmodes': fk})
pars['N'] = len(pars['kmodes'])
# [N/m**1] Modal damping coefficient
pars.update({'Ab_array': pars['A']*10**(linspace(0, pars['D'],
pars['N']))})
# definition of stiffnesses values
coeffs = pars['Kb']*(k.flatten()**4)
# definition of stiffnesses components
for i, c in enumerate(coeffs):
stiffness = Stiffness(label+'K'+str(i),
(datum, label+'M'+str(i)),
K=(label+'K'+str(i), c))
self += stiffness
# definition of masses values
coeffs = [pars['Mb']]*pars['N']
# definition of masses components
for i, c in enumerate(coeffs):
mass = Mass(label+'M'+str(i),
(label+'M'+str(i), ),
M=(label+'M'+str(i), c))
self += mass
# definition of dampers components
coeffs = list(pars['Ab_array'])
# definition of dampers components
for i, c in enumerate(coeffs):
damper = Damper(label+'A'+str(i),
(datum, label+'M'+str(i)),
A=(label+'A'+str(i), c))
self += damper
for n, Nn in enumerate(nodes):
label_n = label+'T'+str(n)
Omega = omega_cosine(pars['z'+str(n+1)]*pars['Lb'],
pars['w'+str(n+1)],
pars['Lb'], pars['kmodes'])
# transformers associated with the coefficients of modal projection
# Begining of the serial connection of transformers primals
A1 = Nn
# tail node for the serial connection of transformers primals
if pars['N'] == 1:
A2 = datum
else:
A2 = label_n + str(0)
# iterate over coefficients values
for i, o in enumerate(Omega):
# define transfomer
transfo = Transformer(label_n+str(i),
(A1, A2,
datum, label+'M'+str(i)),
alpha=(label_n+'alpha'+str(i), o))
self += transfo
# update nodes
A1 = label_n+str(i)
if i == pars['N']-2:
A2 = datum
else:
A2 = label_n+str(i+1)
