def test_saveload_trajectory():
"""Test pickling for saving and loading 'Trajectory'"""
var1 = Variable(Pointset(coordarray=array(range(10), float) * 0.1,
indepvararray=array(range(10), float) * 0.5),
name='v1')
var2 = Variable(Pointset(coordarray=array(range(10), float) * 0.25 + 1.0,
indepvararray=array(range(10), float) * 0.5),
name='v2')
traj = Trajectory('traj1', [var1, var2])
saveObjects(traj, 'temp_objects.pkl', True)
traj_loaded = loadObjects('temp_objects.pkl')[0]
assert traj_loaded(2.0) == traj(2.0)
os.remove('temp_objects.pkl')
def setup(self):
# self.y = Point({'y': 4})
# self.v = Pointset({'coorddict': {'x0': 0.2, 'x1': -1.2},
# 'indepvardict': {'t': 0.01},
# 'coordtype': float64,
# 'indepvartype': float64})
# self.u = Pointset(
# {'coordarray': array([10., 20., 30., 40.])})
# self.w_x0 = self.wp['x0']
# self.w_at_1 = self.wp(1.).toarray()
self.wp = Pointset(
{'coordarray': array([ [4.456, 2.34634, 7.3431, 5.443],
[-10.0336, -5.2235, -3.23221, -0.01],
[3e5, 3.1e5, 3.3e5, 2.8e5]], float64),
'coordnames': ['x0', 'x1', 'x2'],
'indepvarname': 't',
'indepvararray': array([0.0, 1.0, 2.0, 3.0], float64)})
self.wp_ins = Pointset(
{'coorddict': {'x0': [-2.1, -4., -5., -4.5], 'x1': [50., 51., 52., 54.], 'x2': [0.01, 0.02, 0.4, 0.9]},
'indepvardict': {'t': [1.5, 5.2, 9., 10.]},
'coordtype': float64,
'indepvartype': float64,
'labels': {2: 'b', 3: {'a': {'bif': 'H'}}}
})
self.wp2 = Pointset(
{'coorddict': {'x0': [-4.5, 2, 3], 'x1': [54, 62, 64], 'x2': [0.9, 0.8, 0.2]},
'indepvardict': {'t': [10, 11, 12]},
'coordtype': float64,
'indepvartype': float64,
'labels': {0: {'a_different': {'bif': 'H'}}, 2: 'd'}
})
def test_eight(self):
# wnp = pointsToPointset(self.pointlist)
# wnp.labels[0] = ('b', {})
# wnp.addlabel(4, 'c', {'bif': 'H'}) # preferred syntax
vw = Pointset({
'coorddict': {
'x0': [0.1, 0.15],
'x1': [100., 102],
'x2': [0.2, 0.1]
},
'indepvardict': {
't': [4.5, 5.0]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
1: 'c'
}
})
self.wp.append(vw)
self.wp.append(
Point(
{'coorddict': {
't': 6.5,
'x0': 2,
'x1': -300,
'x2': -0.9997
}}))
self.wp.insert(self.wp_ins)
self.wp.append(self.wp2, skipMatchingIndepvar=True)
assert len(self.wp) == 13
def make_spike_signal(ts, dur, tmax, loval=0, hival=1, dt=0.1):
"""Helper function: Square-pulse spike signal between two levels, loval
and hival. Pulses occur at times given by ts array for duration given by
dur scalar, from time 0 to tmax.
Returns a single-entry dictionary of Variable objects with key 'Istim'.
Default loval = 0, hival = 1.
To improve performance with adaptive time-step solvers, three (two before,
one after) points are added before and after each pulse, with a minimum
step time given by dt.
"""
assert len(ts) > 0, "No spike time events provided!"
assert isincreasing(ts), "This function expects strictly increasing times"
assert ts[0] != 0, "This function does not support initial step up at t=0"
assert dur > dt, "Duration must be larger than dt"
times = [0]
vals = [loval]
# check that ts are separated by at least dur+4*dt
assert all(np.diff(ts) > dur+4*dt), "Separate events by at least 4*dt"
assert tmax > ts[-1]+dur, "tmax must be larger than last event end time"
for t in ts:
times.extend([t-2.9*dt, t-dt, t, t+dur-dt, t+dur, t+dur+dt])
vals.extend([loval, loval, hival, hival, hival, loval])
if tmax > ts[-1]+dur+dt:
times.append(tmax)
vals.append(loval)
coorddict = {'Istim': vals}
vpts = Pointset(coorddict=coorddict, indepvararray=times)
return pointset_to_vars(vpts, discrete=False)
def test_four(self):
vw = Pointset({
'coorddict': {
'x0': [0.1, 0.15],
'x1': [100., 102],
'x2': [0.2, 0.1]
},
'indepvardict': {
't': [4.5, 5.0]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
1: 'c'
}
})
self.wp.append(vw)
self.wp.append(
Point(
{'coorddict': {
't': 6.5,
'x0': 2,
'x1': -300,
'x2': -0.9997
}}))
assert type(self.wp.coordarray) == type(array([1, 2], float64))
def test_saveload_point_and_pointset(fname):
"""Test pickling for saving and loading 'Point' and 'Pointset'"""
x = Point(
coorddict={
'x0': [1.123456789],
'x1': [-0.4],
'x2': [4000]
},
coordtype=float64
)
v = Pointset(
coorddict={
'x0': 0.2,
'x1': -1.2
},
indepvardict={'t': 0.01},
coordtype=float,
indepvartype=float
)
saveObjects([x, v], fname, True)
objs_pts = loadObjects(fname)
assert objs_pts[0] == x
assert objs_pts[1] == v
os.remove(fname)
def test_two():
k = Pointset({
'coordarray': array(0.1),
'coordnames': 'k0',
'indepvarname': 't',
'indepvararray': array(0.0)
})
assert k.dimension == 1
def test_saveload_variable():
"""Test pickling for saving and loading 'Variable'"""
var1 = Variable(Pointset(coordarray=array(range(10), float) * 0.1,
indepvararray=array(range(10), float) * 0.5),
name='v1')
saveObjects(var1, 'temp_objects.pkl', True)
obj_var = loadObjects('temp_objects.pkl')[0]
assert obj_var(1.5) == var1(1.5)
os.remove('temp_objects.pkl')
def make_noise_signal(dt, t_end, mean, stddev, num_cells, seed=None):
"""Helper function: Gaussian white noise at sample rate = dt for 1 or more cells,
for a duration of t_end."""
if seed is not None:
np.random.seed(seed)
N = ceil(t_end*1./dt)
t = np.linspace(0, t_end, N)
coorddict = {}
for cellnum in range(num_cells):
coorddict['noise%i' % (cellnum+1)] = np.random.normal(0, stddev, N)
vpts = Pointset(coorddict=coorddict, indepvararray=t)
return pointset_to_vars(vpts, discrete=False)
def newCurve(self, initargs):
"""Create new curve with arguments specified in the dictionary initargs."""
curvetype = initargs['type']
curvetype = curvetype.upper()
if curvetype not in curve_list:
raise TypeError(curvetype + ' not an allowable curve type')
# Check name
if initargs['name'] in self.curves.keys():
raise AttributeError('Ambiguous name field: ' + initargs['name'] +
' already exists')
# Check parameters
if self.model.pars == {}:
raise ValueError('No parameters defined for this system!')
# Process initial point
if 'initpoint' not in initargs:
# Default to initial conditions for model
if self.model.icdict == {}:
raise ValueError('No initial point defined for this system!')
initargs['initpoint'] = self.model.icdict.copy()
#for p in initargs['freepars']:
# initargs['initpoint'][p] = self.model.pars[p]
else:
if isinstance(initargs['initpoint'], dict):
initargs['initpoint'] = initargs['initpoint'].copy()
#for p in initargs['freepars']:
# if p not in initargs['initpoint'].keys():
# initargs['initpoint'][p] = self.model.pars[p]
elif isinstance(initargs['initpoint'], str):
curvename, pointname = initargs['initpoint'].split(':')
pointtype = pointname.strip('0123456789')
if not self.curves.has_key(curvename):
raise KeyError('No curve of name ' + curvename +
' exists.')
else:
point = self.curves[curvename].getSpecialPoint(
pointtype, pointname)
if point is None:
raise KeyError('No point of name ' + pointname +
' exists.')
else:
initargs['initpoint'] = point
# Separate from if-else above since 'str' clause returns type Point
if isinstance(initargs['initpoint'], Point):
# Check to see if point contains a cycle. If it does, assume
# we are starting at a cycle and save it in initcycle
for v in initargs['initpoint'].labels.itervalues():
if v.has_key('cycle'):
initargs[
'initcycle'] = v # Dictionary w/ cycle, name, and tangent information
# Save initial point information
initargs['initpoint'] = initargs['initpoint'].todict()
#for p in initargs['freepars']:
# if p not in initargs['initpoint'].keys():
# initargs['initpoint'][p] = self.model.pars[p]
# Process cycle
if 'initcycle' in initargs:
if isinstance(initargs['initcycle'], NumArray):
c0 = {}
c0['data'] = args(V={'udotps': None, 'rldot': None})
c0['cycle'] = Pointset({
'coordnames':
self.gensys.funcspec.vars,
'coordarray':
num_transpose(initargs['initcycle'][:, 1:]).copy(),
'indepvarname':
't',
'indepvararray':
num_transpose(initargs['initcycle'][:, 0]).copy()
})
initargs['initcycle'] = c0
elif isinstance(initargs['initcycle'], Pointset):
c0 = {}
c0['data'] = args(V={'udotps': None, 'rldot': None})
c0['cycle'] = initargs['initcycle']
initargs['initcycle'] = c0
# Load auto module if required
automod = None
if curvetype in auto_list:
if self._autoMod is None:
self.loadAutoMod()
automod = self._autoMod
self.curves[initargs['name']] = curve_list[curvetype](self.model,
self.gensys,
automod,
self.plot,
initargs)
def newCurve(self, initargs):
"""Create new curve with arguments specified in the dictionary initargs."""
curvetype = initargs['type'].upper()
if curvetype not in self.curve_list:
raise PyDSTool_TypeError(
str(curvetype) + ' not an allowable curve type')
# Check name
cname = initargs['name']
if 'force' in initargs:
if initargs['force'] and cname in self.curves:
del self.curves[cname]
if cname in self.curves:
raise ValueError('Ambiguous name field: ' + cname \
+ ' already exists (use force=True to override)')
# Check parameters
if (curvetype != 'UD-C' and self.model.pars == {}) or \
(curvetype == 'UD-C' and 'userpars' not in initargs):
raise ValueError('No parameters defined for this system!')
# Process initial point
initargs = initargs.copy() # ensures no side-effects outside
if 'initpoint' not in initargs or initargs['initpoint'] is None:
# Default to initial conditions for model
if self.model.icdict == {}:
raise ValueError('No initial point defined for this system!')
elif 'uservars' in initargs:
if remain(initargs['uservars'],
self.model.icdict.keys()) == []:
# uservars just used to select a subset of system's regular state vars
initargs['initpoint'] = filteredDict(
self.model.icdict, initargs['uservars'])
else:
raise ValueError(
'No initial point defined for this system!')
else:
initargs['initpoint'] = self.model.icdict.copy()
#for p in initargs['freepars']:
# initargs['initpoint'][p] = self.model.pars[p]
else:
if isinstance(initargs['initpoint'], dict):
initargs['initpoint'] = initargs['initpoint'].copy()
#for p in initargs['freepars']:
# if p not in initargs['initpoint'].keys():
# initargs['initpoint'][p] = self.model.pars[p]
elif isinstance(initargs['initpoint'], str):
curvename, pointname = initargs['initpoint'].split(':')
pointtype = pointname.strip('0123456789')
if curvename not in self.curves:
raise KeyError('No curve of name ' + curvename +
' exists.')
else:
point = self.curves[curvename].getSpecialPoint(
pointtype, pointname)
if point is None:
raise KeyError('No point of name ' + pointname +
' exists.')
else:
initargs['initpoint'] = point
# Separate from if-else above since 'str' clause returns type Point
if isinstance(initargs['initpoint'], Point):
# Check to see if point contains a cycle. If it does, assume
# we are starting at a cycle and save it in initcycle
for v in initargs['initpoint'].labels.values():
if 'cycle' in v:
initargs[
'initcycle'] = v # Dictionary w/ cycle, name, and tangent information
# Save initial point information
initPoint = {}
if 'curvename' in locals() and curvename in self.curves:
initPoint = self.curves[curvename].parsdict.copy()
initPoint.update(initargs['initpoint'].copy().todict())
initargs['initpoint'] = initPoint
# initargs['initpoint'] = initargs['initpoint'].copy().todict()
#for p in initargs['freepars']:
# if p not in initargs['initpoint'].keys():
# initargs['initpoint'][p] = self.model.pars[p]
# Process cycle
if 'initcycle' in initargs:
if isinstance(initargs['initcycle'], ndarray):
c0 = {}
c0['data'] = args(V={'udotps': None, 'rldot': None})
c0['cycle'] = Pointset({
'coordnames':
self.gensys.funcspec.vars,
'coordarray':
initargs['initcycle'][1:, :].copy(),
'indepvarname':
't',
'indepvararray':
initargs['initcycle'][0, :].copy()
})
initargs['initcycle'] = c0
elif isinstance(initargs['initcycle'], Pointset):
c0 = {}
c0['data'] = args(V={'udotps': None, 'rldot': None})
c0['cycle'] = initargs['initcycle']
initargs['initcycle'] = c0
# Load auto module if required
automod = None
if curvetype in auto_list:
if self._autoMod is None:
self.loadAutoMod()
automod = self._autoMod
self.curves[cname] = self.curve_list[curvetype](self.model,
self.gensys, automod,
self.plot, initargs)
def finitePRC(model, ref_traj_period, evname, pertcoord, pertsize=0.05,
settle=5, verbose=False, skip=1, do_pert=_default_pert,
keep_trajs=False, stop_at_t=np.inf, force_T=np.nan):
"""Return a Pointset with dependent variable 'D_phase', measured from 0 to 1,
where D_phase > 0 is an advance.
Pass a Generator or Model instance for model.
Pass a Trajectory or Pointset for the ref_traj_period argument.
Pass the event name in the model that indicates the periodicity.
Use skip > 1 to sub-sample the points computed along the trajectory at
the skip rate.
Use a do_pert function to do any non-standard perturbation, e.g. if there
are domain boundary conditions that need special treatment. This function
takes four or five arguments (model, ic, pertcoord, pertsize, perttime=None)
and returns the new point ic (not just ic[pertcoord]).
Use settle=0 to perform no forward integration before the time window in
which the perturbation will be applied, or a fraction < 1 to ensure an
integration past the event point (e.g. for non-cycles).
Use stop_at_t to calculate a partial PRC, from perturbation time 0 to this
value.
Use force_T to force the period to be whatever value you like.
Note: Depending on your model, there may be regions of the PRC that are
offset by a constant amount to the rest of the PRC. This is a "wart" that
needs improvement.
"""
tag_pts = False
if not isinstance(model, Model.Model):
# temporarily embed into a model object
model = embed(model)
if keep_trajs:
tag_pts = True
print "Note: model object will be stored in PRC attribute _model"
try:
all_pts = ref_traj_period.sample()
ref_pts = all_pts[::skip]
if ref_pts[-1] != all_pts[-1]:
# ensure last point at t=T is present
ref_pts.append(all_pts[[-1]])
if np.isnan(force_T):
T = ref_traj_period.indepdomain[1]-ref_traj_period.indepdomain[0]
else:
T = force_T
except AttributeError:
# already passed points
ref_pts = ref_traj_period[::skip]
if ref_pts[-1] != ref_traj_period[-1]:
ref_pts.append(ref_traj_period[[-1]])
if np.isnan(force_T):
T = ref_traj_period.indepvararray[-1]-ref_traj_period.indepvararray[0]
else:
T = force_T
ref_ts = ref_pts.indepvararray
PRCvals = []
t_off = 0
if verbose:
print "Period T =", T
for i, t0 in enumerate(ref_ts):
if t0 > stop_at_t:
break
ic = do_pert(model, ref_pts[i], pertcoord, pertsize, t0)
if verbose:
print i, "of", len(ref_ts), ": t0 = ", t0, "of", T, " t_end", settle*T+t0
print " ", ic
model.set(ics=ic.copy(), tdata=[0, (settle+1)*T+t0])
if keep_trajs:
model.compute(trajname='pert_%i'%i, force=True)
evts = model.getTrajEventTimes('pert_%i'%i, evname)
else:
model.compute(trajname='pert', force=True)
evts = model.getTrajEventTimes('pert', evname)
if verbose:
print " Last event:", evts[-1]
if i == 0:
# make sure to always use the same event number
evnum = max(0,len(evts)-2)
val = (T-np.mod(evts[evnum]+t0, T))/T
## assume continuity of PRC: hack-fix modulo wart by testing these vals
# and using the closest to previous value
if i > 0:
test_vals = np.array([val-2, val-1, val-0.5, val, val+0.5, val+1, val+2])
m = np.argmin(abs(PRCvals[-1] - test_vals))
val = test_vals[m]
if verbose and abs(PRCvals[-1] - val) > 0.05:
print "\nCorrected value", i, PRCvals, val
else:
# i = 0. Check that value is adjusted to be closest to zero,
# given that we assume the minimum will be at the beginning of the run.
test_vals = np.array([val-1, val, val+1])
m = np.argmin(abs(test_vals))
val = test_vals[m]
PRCvals.append(val)
PRC = Pointset(coordarray=[PRCvals], coordnames=['D_phase'],
indepvararray=ref_ts[:len(PRCvals)], indepvarname='t')
if tag_pts:
PRC._model = model
else:
PRC._model = None
return PRC
def one_period_traj(model, ev_name, ev_t_tol, ev_norm_tol, T_est,
verbose=False, initial_settle=6, restore_old_ics=False,
use_quadratic_interp=False):
"""
Utility to extract a single period of a limit cycle of the model using forward
integration, up to a tolerance given in terms of both the period and the norm of the
vector of variables in the limit cycle at the period endpoints.
Requires a non-terminal event in the model that is detected exactly once per period.
Assumes model initial conditions are already in domain of attraction for limit cycle.
T_est is an initial estimate of period.
use_quadratic_interp option (default False) indicates whether to make the returned
trajectory interpolated more accurately using quadratic functions rather than linear ones.
This option takes a lot longer to complete!
The model argument can be an instance of a Generator class or Model class.
Returned trajectory will have name 'one_period'.
"""
if not isinstance(model, Model.Model):
# temporarily embed into a model object
model = embed(model)
if use_quadratic_interp:
old_interp_setting = model.query('algparams')['poly_interp']
model.set(algparams={'poly_interp': True})
trajname = '_test_period_'
old_ics = model.query('ics')
settle = initial_settle
tries = 1
success = False
while not success and tries < 8:
model.compute(trajname=trajname, tdata=[0,T_est*(settle+0.2)], force=True)
evts = model.getTrajEventTimes(trajname, ev_name)
all_evs = model.getTrajEventTimes(trajname)
if len(evts) <= 2:
raise RuntimeError("Not enough events found")
ref_ic = model(trajname, evts[-1])
t_check = 10000*np.ones((tries,),float)
norm_check = 10000*np.ones((tries,),float)
T = np.zeros((tries,),float)
look_range = list(range(1, min((tries+1, len(evts)))))
if verbose:
print("\n Tries: ", tries, "\n")
for lookback in look_range:
try:
d_evts = [evts[i]-evts[i-lookback] for i in \
range(lookback, len(evts))]
except KeyError:
# no more events left to look back at
break
else:
prev_val = model(trajname, evts[-(1+lookback)])
t_check[lookback-1] = abs(d_evts[-1]-d_evts[-2])
norm_check[lookback-1] = np.linalg.norm(ref_ic-prev_val)
T[lookback-1] = d_evts[-1]
T_est = T[0]
t_ix = np.argmin(t_check)
n_ix = np.argmin(norm_check)
ix1 = min((t_ix, n_ix))
ix2 = max((t_ix, n_ix))
if verbose:
print(t_check, norm_check, T)
print(ix1, ix2)
if t_check[ix1] < ev_t_tol and norm_check[ix1] < ev_norm_tol:
success = True
T_final = T[ix1]
elif ix1 != ix2 and t_check[ix2] < ev_t_tol and norm_check[ix2] < ev_norm_tol:
success = True
T_final = T[ix2]
else:
tries += 1
settle = tries*2
model.set(ics = ref_ic)
if success:
model.set(ics=ref_ic, tdata=[0, T_final])
model.compute(trajname='one_period', force=True)
ref_traj = model['one_period']
# insert the ON event at beginning of traj
ref_traj.events[ev_name] = Pointset(indepvararray=[0],
coordarray=np.array([ref_ic.coordarray]).T,
coordnames=ref_ic.coordnames)
ref_pts = ref_traj.sample()
# restore old ICs
if restore_old_ics:
model.set(ics=old_ics)
if use_quadratic_interp:
model.set(algparams={'poly_interp': old_interp_setting})
return ref_traj, ref_pts, T_final
else:
print("norm check was", norm_check)
print("t check was", t_check)
raise RuntimeError("Failure to converge after 80 iterations")
def finitePRC(model, ref_traj_period, evname, pertcoord, pertsize=0.05,
settle=5, verbose=False, skip=1, do_pert=_default_pert,
keep_trajs=False, stop_at_t=np.inf, force_T=np.nan):
"""Return a Pointset with dependent variable 'D_phase', measured from 0 to 1,
where D_phase > 0 is an advance.
Pass a Generator or Model instance for model.
Pass a Trajectory or Pointset for the ref_traj_period argument.
Pass the event name in the model that indicates the periodicity.
Use skip > 1 to sub-sample the points computed along the trajectory at
the skip rate.
Use a do_pert function to do any non-standard perturbation, e.g. if there
are domain boundary conditions that need special treatment. This function
takes four or five arguments (model, ic, pertcoord, pertsize, perttime=None)
and returns the new point ic (not just ic[pertcoord]).
Use settle=0 to perform no forward integration before the time window in
which the perturbation will be applied, or a fraction < 1 to ensure an
integration past the event point (e.g. for non-cycles).
Use stop_at_t to calculate a partial PRC, from perturbation time 0 to this
value.
Use force_T to force the period to be whatever value you like.
Note: Depending on your model, there may be regions of the PRC that are
offset by a constant amount to the rest of the PRC. This is a "wart" that
needs improvement.
"""
tag_pts = False
if not isinstance(model, Model.Model):
# temporarily embed into a model object
model = embed(model)
if keep_trajs:
tag_pts = True
print("Note: model object will be stored in PRC attribute _model")
try:
all_pts = ref_traj_period.sample()
ref_pts = all_pts[::skip]
if ref_pts[-1] != all_pts[-1]:
# ensure last point at t=T is present
ref_pts.append(all_pts[[-1]])
if np.isnan(force_T):
T = ref_traj_period.indepdomain[1]-ref_traj_period.indepdomain[0]
else:
T = force_T
except AttributeError:
# already passed points
ref_pts = ref_traj_period[::skip]
if ref_pts[-1] != ref_traj_period[-1]:
ref_pts.append(ref_traj_period[[-1]])
if np.isnan(force_T):
T = ref_traj_period.indepvararray[-1]-ref_traj_period.indepvararray[0]
else:
T = force_T
ref_ts = ref_pts.indepvararray
PRCvals = []
t_off = 0
if verbose:
print("Period T =", T)
for i, t0 in enumerate(ref_ts):
if t0 > stop_at_t:
break
ic = do_pert(model, ref_pts[i], pertcoord, pertsize, t0)
if verbose:
print(i, "of", len(ref_ts), ": t0 = ", t0, "of", T, " t_end", settle*T+t0)
print(" ", ic)
model.set(ics=ic.copy(), tdata=[0, (settle+1)*T+t0])
if keep_trajs:
model.compute(trajname='pert_%i'%i, force=True)
evts = model.getTrajEventTimes('pert_%i'%i, evname)
else:
model.compute(trajname='pert', force=True)
evts = model.getTrajEventTimes('pert', evname)
if verbose:
print(" Last event:", evts[-1])
if i == 0:
# make sure to always use the same event number
evnum = max(0,len(evts)-2)
val = (T-np.mod(evts[evnum]+t0, T))/T
## assume continuity of PRC: hack-fix modulo wart by testing these vals
# and using the closest to previous value
if i > 0:
test_vals = np.array([val-2, val-1, val-0.5, val, val+0.5, val+1, val+2])
m = np.argmin(abs(PRCvals[-1] - test_vals))
val = test_vals[m]
if verbose and abs(PRCvals[-1] - val) > 0.05:
print("\nCorrected value", i, PRCvals, val)
else:
# i = 0. Check that value is adjusted to be closest to zero,
# given that we assume the minimum will be at the beginning of the run.
test_vals = np.array([val-1, val, val+1])
m = np.argmin(abs(test_vals))
val = test_vals[m]
PRCvals.append(val)
PRC = Pointset(coordarray=[PRCvals], coordnames=['D_phase'],
indepvararray=ref_ts[:len(PRCvals)], indepvarname='t')
if tag_pts:
PRC._model = model
else:
PRC._model = None
return PRC
def setup(self):
# self.y = Point({'y': 4})
# self.v = Pointset({'coorddict': {'x0': 0.2, 'x1': -1.2},
# 'indepvardict': {'t': 0.01},
# 'coordtype': float64,
# 'indepvartype': float64})
# self.u = Pointset(
# {'coordarray': array([10., 20., 30., 40.])})
# self.w_x0 = self.wp['x0']
# self.w_at_1 = self.wp(1.).toarray()
self.wp = Pointset({
'coordarray':
array([[4.456, 2.34634, 7.3431, 5.443],
[-10.0336, -5.2235, -3.23221, -0.01],
[3e5, 3.1e5, 3.3e5, 2.8e5]], float64),
'coordnames': ['x0', 'x1', 'x2'],
'indepvarname':
't',
'indepvararray':
array([0.0, 1.0, 2.0, 3.0], float64)
})
self.wp_ins = Pointset({
'coorddict': {
'x0': [-2.1, -4., -5., -4.5],
'x1': [50., 51., 52., 54.],
'x2': [0.01, 0.02, 0.4, 0.9]
},
'indepvardict': {
't': [1.5, 5.2, 9., 10.]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
2: 'b',
3: {
'a': {
'bif': 'H'
}
}
}
})
self.wp2 = Pointset({
'coorddict': {
'x0': [-4.5, 2, 3],
'x1': [54, 62, 64],
'x2': [0.9, 0.8, 0.2]
},
'indepvardict': {
't': [10, 11, 12]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
0: {
'a_different': {
'bif': 'H'
}
},
2: 'd'
}
})
class TestPointSet(object):
def setup(self):
# self.y = Point({'y': 4})
# self.v = Pointset({'coorddict': {'x0': 0.2, 'x1': -1.2},
# 'indepvardict': {'t': 0.01},
# 'coordtype': float64,
# 'indepvartype': float64})
# self.u = Pointset(
# {'coordarray': array([10., 20., 30., 40.])})
# self.w_x0 = self.wp['x0']
# self.w_at_1 = self.wp(1.).toarray()
self.wp = Pointset({
'coordarray':
array([[4.456, 2.34634, 7.3431, 5.443],
[-10.0336, -5.2235, -3.23221, -0.01],
[3e5, 3.1e5, 3.3e5, 2.8e5]], float64),
'coordnames': ['x0', 'x1', 'x2'],
'indepvarname':
't',
'indepvararray':
array([0.0, 1.0, 2.0, 3.0], float64)
})
self.wp_ins = Pointset({
'coorddict': {
'x0': [-2.1, -4., -5., -4.5],
'x1': [50., 51., 52., 54.],
'x2': [0.01, 0.02, 0.4, 0.9]
},
'indepvardict': {
't': [1.5, 5.2, 9., 10.]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
2: 'b',
3: {
'a': {
'bif': 'H'
}
}
}
})
self.wp2 = Pointset({
'coorddict': {
'x0': [-4.5, 2, 3],
'x1': [54, 62, 64],
'x2': [0.9, 0.8, 0.2]
},
'indepvardict': {
't': [10, 11, 12]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
0: {
'a_different': {
'bif': 'H'
}
},
2: 'd'
}
})
def test_three(self):
assert type(self.wp.coordarray) == type(array([1, 2], float64))
def test_four(self):
vw = Pointset({
'coorddict': {
'x0': [0.1, 0.15],
'x1': [100., 102],
'x2': [0.2, 0.1]
},
'indepvardict': {
't': [4.5, 5.0]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
1: 'c'
}
})
self.wp.append(vw)
self.wp.append(
Point(
{'coorddict': {
't': 6.5,
'x0': 2,
'x1': -300,
'x2': -0.9997
}}))
assert type(self.wp.coordarray) == type(array([1, 2], float64))
def test_five(self):
self.wp.toarray()
self.wp.labels[3] = ('a', {'bif': 'SN'})
self.wp.insert(self.wp_ins)
wp_part = self.wp[3:5]
assert wp_part.labels[0] == self.wp.labels[3]
def test_six(self):
self.wp.labels[3] = ('a', {'bif': 'SN'})
wpt = self.wp(3.)
assert wpt.labels == {'a': {'bif': 'SN'}}
def test_seven(self):
self.pointlist = []
self.wp.insert(self.wp_ins)
for t in self.wp['t']:
self.pointlist.append(self.wp(t))
w_reconstructed = pointsToPointset(self.pointlist, 't', self.wp['t'])
with pytest.raises(ValueError):
w_double = w_reconstructed.append(w_reconstructed)
def test_eight(self):
# wnp = pointsToPointset(self.pointlist)
# wnp.labels[0] = ('b', {})
# wnp.addlabel(4, 'c', {'bif': 'H'}) # preferred syntax
vw = Pointset({
'coorddict': {
'x0': [0.1, 0.15],
'x1': [100., 102],
'x2': [0.2, 0.1]
},
'indepvardict': {
't': [4.5, 5.0]
},
'coordtype': float64,
'indepvartype': float64,
'labels': {
1: 'c'
}
})
self.wp.append(vw)
self.wp.append(
Point(
{'coorddict': {
't': 6.5,
'x0': 2,
'x1': -300,
'x2': -0.9997
}}))
self.wp.insert(self.wp_ins)
self.wp.append(self.wp2, skipMatchingIndepvar=True)
assert len(self.wp) == 13
def test_nine(self):
self.wp.insert(self.wp_ins)
assert self.wp.bylabel('b')['t'][0] == 9.0
def test_ten(self):
self.wp.labels[3] = ('a', {'bif': 'SN'})
self.wp.insert(self.wp_ins)
assert all(self.wp.bylabel('a')['t'] == array([3., 10.]))
def test_eleven(self):
self.wp.append(self.wp2, skipMatchingIndepvar=True)
assert self.wp.bylabel('d')['t'][0] == 12.0
def test_twelve(self):
self.wp.append(self.wp2, skipMatchingIndepvar=True)
assert all(self.wp.bylabel('a_different')['t'] == array([10.]))
def test_thirteen(self):
self.wp.insert(self.wp_ins)
self.wp.append(self.wp2, skipMatchingIndepvar=True)
z = self.wp[-5:]
assert z.labels.getIndices() == [1, 2, 4]
class TestPointSet(object):
def setup(self):
# self.y = Point({'y': 4})
# self.v = Pointset({'coorddict': {'x0': 0.2, 'x1': -1.2},
# 'indepvardict': {'t': 0.01},
# 'coordtype': float64,
# 'indepvartype': float64})
# self.u = Pointset(
# {'coordarray': array([10., 20., 30., 40.])})
# self.w_x0 = self.wp['x0']
# self.w_at_1 = self.wp(1.).toarray()
self.wp = Pointset(
{'coordarray': array([ [4.456, 2.34634, 7.3431, 5.443],
[-10.0336, -5.2235, -3.23221, -0.01],
[3e5, 3.1e5, 3.3e5, 2.8e5]], float64),
'coordnames': ['x0', 'x1', 'x2'],
'indepvarname': 't',
'indepvararray': array([0.0, 1.0, 2.0, 3.0], float64)})
self.wp_ins = Pointset(
{'coorddict': {'x0': [-2.1, -4., -5., -4.5], 'x1': [50., 51., 52., 54.], 'x2': [0.01, 0.02, 0.4, 0.9]},
'indepvardict': {'t': [1.5, 5.2, 9., 10.]},
'coordtype': float64,
'indepvartype': float64,
'labels': {2: 'b', 3: {'a': {'bif': 'H'}}}
})
self.wp2 = Pointset(
{'coorddict': {'x0': [-4.5, 2, 3], 'x1': [54, 62, 64], 'x2': [0.9, 0.8, 0.2]},
'indepvardict': {'t': [10, 11, 12]},
'coordtype': float64,
'indepvartype': float64,
'labels': {0: {'a_different': {'bif': 'H'}}, 2: 'd'}
})
def test_three(self):
assert type(self.wp.coordarray) == type(array([1, 2], float64))
def test_four(self):
vw = Pointset(
{'coorddict': {'x0': [0.1, 0.15], 'x1': [100., 102], 'x2': [0.2, 0.1]},
'indepvardict': {'t': [4.5, 5.0]},
'coordtype': float64,
'indepvartype': float64,
'labels': {1: 'c'}})
self.wp.append(vw)
self.wp.append(Point({'coorddict': {'t': 6.5, 'x0': 2, 'x1': -300, 'x2': -0.9997}}))
assert type(self.wp.coordarray) == type(array([1, 2], float64))
def test_five(self):
self.wp.toarray()
self.wp.labels[3] = ('a', {'bif': 'SN'})
self.wp.insert(self.wp_ins)
wp_part = self.wp[3:5]
assert wp_part.labels[0] == self.wp.labels[3]
def test_six(self):
self.wp.labels[3] = ('a', {'bif': 'SN'})
wpt = self.wp(3.)
assert wpt.labels == {'a': {'bif': 'SN'}}
def test_seven(self):
self.pointlist = []
self.wp.insert(self.wp_ins)
for t in self.wp['t']:
self.pointlist.append(self.wp(t))
w_reconstructed = pointsToPointset(
self.pointlist, 't', self.wp['t'])
with pytest.raises(ValueError):
w_double = w_reconstructed.append(w_reconstructed)
def test_eight(self):
# wnp = pointsToPointset(self.pointlist)
# wnp.labels[0] = ('b', {})
# wnp.addlabel(4, 'c', {'bif': 'H'}) # preferred syntax
vw = Pointset(
{'coorddict': {'x0': [0.1, 0.15], 'x1': [100., 102], 'x2': [0.2, 0.1]},
'indepvardict': {'t': [4.5, 5.0]},
'coordtype': float64,
'indepvartype': float64,
'labels': {1: 'c'}})
self.wp.append(vw)
self.wp.append(Point({'coorddict': {'t': 6.5, 'x0': 2, 'x1': -300, 'x2': -0.9997}}))
self.wp.insert(self.wp_ins)
self.wp.append(self.wp2, skipMatchingIndepvar=True)
assert len(self.wp) == 13
def test_nine(self):
self.wp.insert(self.wp_ins)
assert self.wp.bylabel('b')['t'][0] == 9.0
def test_ten(self):
self.wp.labels[3] = ('a', {'bif': 'SN'})
self.wp.insert(self.wp_ins)
assert all(self.wp.bylabel('a')['t'] == array([3., 10.]))
def test_eleven(self):
self.wp.append(self.wp2, skipMatchingIndepvar=True)
assert self.wp.bylabel('d')['t'][0] == 12.0
def test_twelve(self):
self.wp.append(self.wp2, skipMatchingIndepvar=True)
assert all(self.wp.bylabel('a_different')['t'] == array([10.]))
def test_thirteen(self):
self.wp.insert(self.wp_ins)
self.wp.append(self.wp2, skipMatchingIndepvar=True)
z = self.wp[-5:]
assert z.labels.getIndices() == [1, 2, 4]
