def ifThenElse(condition, val1, val2, *args, **kwargs):
# for future implementation
assert len(args) == 0 and len(kwargs) == 0
Val1 = atleast_oofun(val1)#fixed_oofun(val1) if not isinstance(val1, oofun) else val1
#if np.isscalar(val1): raise 0
Val2 = atleast_oofun(val2)#fixed_oofun(val2) if not isinstance(val2, oofun) else val2
if isinstance(condition, bool):
return Val1 if condition else Val2
elif isinstance(condition, oofun):
f = lambda conditionResult, value1Result, value2Result: value1Result if conditionResult else value2Result
# !!! Don't modify it elseware function will evaluate both expressions despite of condition value
r = oofun(f, [condition, val1, val2])
r.D = lambda point, *args, **kwargs: (Val1.D(point, *args, **kwargs) if isinstance(Val1, oofun) else {}) if condition(point) else \
(Val2.D(point, *args, **kwargs) if isinstance(Val2, oofun) else {})
r._D = lambda point, *args, **kwargs: (Val1._D(point, *args, **kwargs) if isinstance(Val1, oofun) else {}) if condition(point) else \
(Val2._D(point, *args, **kwargs) if isinstance(Val2, oofun) else {})
r.d = errFunc
# TODO: try to set correct value from val1, val2 if condition is fixed
# def getOrder(Vars=None, fixedVars=None, *args, **kwargs):
# dep = condition.getDep()
# if Vars is not None and dep.is
return r
else:
raise FuncDesignerException('ifThenElse requires 1st argument (condition) to be either boolean or oofun, got %s instead' % type(condition))
def integrator(func, domain, **kwargs):
if not scipyInstalled:
raise FuncDesignerException(
'to use scipy_integrate_quad you should have scipy installed, see scipy.org'
)
# if not isinstance(domain, dict) or len(domain) != 1:
# raise FuncDesignerException('currently integration domain must be of type Pythoon dict {integr_var:(val_from, val_to)} only')
#integration_var = domain.keys()[0]
#_from, _to = domain.values()[0]
integration_var, a, b = domain
if not isinstance(integration_var, oovar):
raise FuncDesignerException(
'integration variable must be FuncDesigner oovar')
a, b, func = atleast_oofun(a), atleast_oofun(b), atleast_oofun(func)
def f(point=None):
p2 = point.copy()
#if integration_var not in p2:
#p2[integration_var] = 0.0 # to ajust size, currently only R^1 is implemented
#T = FuncDesignerTranslator(p2)
def vect_func(x):
p2[integration_var] = x
tmp = func(p2)
if np.isscalar(tmp): return tmp
elif tmp.size == 1: return np.asscalar(tmp)
else:
FuncDesignerException(
'incorrect data type, probably bug in uncDesigner kernel')
#vect_func = lambda x: func(T.vector2point(x))
# TODO: better handling of fixed variables
return integrate.quad(vect_func, a(point), b(point), **kwargs)[0]
# def aux_f(point):
# point = oopoint(_point)
# if a(point).size != b(point).size: raise FuncDesignerException('sizes of point-from and point-to must be equal')
# if a(point).size != 1 or b(point).size != 1: raise FuncDesignerException('currently integration is implemented for single variable only')
# dep = a._getDep() | b._getDep() | func._getDep()
# involved_vars = set(point.keys()).add(integration_var)
# if not dep.issubset(involved_vars): raise FuncDesignerException('user-provided point for integration has no information on some variables')
#
# p2 = point.copy()
# if integration_var not in p2:
# p2[integration_var] = 0.0 # to ajust size, currently only R^1 is implemented
# T = FuncDesignerTranslator(p2)
# vect_func = lambda x: func(T.vector2point(x))
# TODO: derivatives
# !!!!!!!!!!!!! TODO: derivatives should not be zeros! Fix it!
r = oofun(f, None)
r.fun = lambda *args: f(point=r._Point)
# TODO : use decorators here
tmp_f = r._getFunc
tmp_D = r._D
def aux_f(*args, **kwargs):
if isinstance(args[0], dict):
r._Point = args[0]
return tmp_f(*args, **kwargs)
def aux_D(*args, **kwargs):
raise FuncDesignerException(
'derivatives from scipy_quad are not implemented yet')
if isinstance(args[0], dict):
r._Point = args[0]
return tmp_D(*args, **kwargs)
r._getFunc = aux_f
r._D = aux_D
return r
def __init__(self, equations, startPoint, *args, **kwargs):
if len(args) > 2:
raise FuncDesignerException('incorrect ode definition, too many args are obtained')
if not isinstance(equations, dict):
raise FuncDesignerException('1st argument of ode constructor should be Python dict')
if not isinstance(startPoint, dict):
raise FuncDesignerException('2nd argument of ode constructor should be Python dict')
if len(args) == 2:
print("""
FuncDesigner warning: you're using obsolete ode() API,
now time should be passed as 3rd argument {timeVariable: times}
or just array of times if equations are time-independend""")
timeVariable, times = args[0], args[1]
else:
if len(args) != 1 or type(args[0]) not in (dict, list, tuple, ndarray):
raise FuncDesignerException('3rd argument of ode constructor must be dict {timeVariable:array_of_times} or just array_of_times')
if type(args[0]) == dict:
if len(args[0]) != 1:
raise FuncDesignerException('in time argument dict has to have exactly 1 entry')
timeVariable, times = list(args[0].items())[0]
if not isinstance(timeVariable, oovar):
raise FuncDesignerException('incorrect time variable, must be FuncDesigner oofun')
else:
times = args[0]
timeVariable = None
self.timeVariable = timeVariable
if timeVariable is not None and timeVariable in equations:
raise FuncDesignerException("ode: differentiation of a variable by itself (time by time) is treated as a potential bug and thus is forbidden")
if not (isinstance(times, (list, tuple)) or (isinstance(times, ndarray) and times.ndim == 1)):
raise FuncDesignerException('incorrect user-defined time argument, must be Python list or numpy array of time values')
self.times = times
self._fd_func, self._startPoint, self._timeVariable, self._times, self._kwargs = equations, startPoint, timeVariable, times, kwargs
startPoint = startPoint.copy()#dict((key, val) for key, val in startPoint.items())
if timeVariable is not None:
startPoint[timeVariable] = times[0]
y0 = []
Funcs = []
# setting oovar.size is risky - it can affect code written after the ode is solved
# thus Point4TranslatorAssignment is used instead
Point4TranslatorAssignment = {}
for v, func in equations.items():
func = atleast_oofun(func)
# if not isinstance(func, oofun):
# func = fixed_oofun(func)
if not isinstance(v, oovar):
raise FuncDesignerException('ode: dict keys must be FuncDesigner oovars, got "%s" instead' % type(v))
startFVal = asarray(func(startPoint))
y0.append(asarray(startPoint[v]))
Funcs.append(func)
Point4TranslatorAssignment[v] = startFVal
if startFVal.size != asarray(startPoint[v]).size or (hasattr(v, 'size') and isscalar(v.size) and startFVal.size != v.size):
raise FuncDesignerException('error in user-defined data: oovar "%s" size is not equal to related function value in start point' % v.name)
self.y0 = hstack(y0)
self.varSizes = [y.size for y in y0]
ooT = FuncDesignerTranslator(Point4TranslatorAssignment)
self.ooT = ooT
def func(y, t):
tmp = dict(ooT.vector2point(y))
if timeVariable is not None:
tmp[timeVariable] = t
r = hstack([func(tmp) for func in Funcs])
return r
self.func = func
_FDVarsID = _getDiffVarsID()
def derivative(y, t):
# print('d')
tmp = dict(ooT.vector2point(y))
if timeVariable is not None:
tmp[timeVariable] = t
r = []
for func in Funcs:
tt = func.D(tmp, fixedVarsScheduleID = _FDVarsID)
if timeVariable is not None:
tt.pop(timeVariable, None)
r.append(ooT.pointDerivative2array(tt))
return vstack(r)
self.derivative = derivative
self.Point4TranslatorAssignment = Point4TranslatorAssignment
def integrator(func, domain, **kwargs):
if not scipyInstalled:
raise FuncDesignerException("to use scipy_integrate_quad you should have scipy installed, see scipy.org")
# if not isinstance(domain, dict) or len(domain) != 1:
# raise FuncDesignerException('currently integration domain must be of type Pythoon dict {integr_var:(val_from, val_to)} only')
# integration_var = domain.keys()[0]
# _from, _to = domain.values()[0]
integration_var, a, b = domain
if not isinstance(integration_var, oovar):
raise FuncDesignerException("integration variable must be FuncDesigner oovar")
a, b, func = atleast_oofun(a), atleast_oofun(b), atleast_oofun(func)
def f(point=None):
p2 = point.copy()
# if integration_var not in p2:
# p2[integration_var] = 0.0 # to ajust size, currently only R^1 is implemented
# T = FuncDesignerTranslator(p2)
def vect_func(x):
p2[integration_var] = x
tmp = func(p2)
if np.isscalar(tmp):
return tmp
elif tmp.size == 1:
return np.asscalar(tmp)
else:
FuncDesignerException("incorrect data type, probably bug in uncDesigner kernel")
# vect_func = lambda x: func(T.vector2point(x))
# TODO: better handling of fixed variables
return integrate.quad(vect_func, a(point), b(point), **kwargs)[0]
# def aux_f(point):
# point = oopoint(_point)
# if a(point).size != b(point).size: raise FuncDesignerException('sizes of point-from and point-to must be equal')
# if a(point).size != 1 or b(point).size != 1: raise FuncDesignerException('currently integration is implemented for single variable only')
# dep = a._getDep() | b._getDep() | func._getDep()
# involved_vars = set(point.keys()).add(integration_var)
# if not dep.issubset(involved_vars): raise FuncDesignerException('user-provided point for integration has no information on some variables')
#
# p2 = point.copy()
# if integration_var not in p2:
# p2[integration_var] = 0.0 # to ajust size, currently only R^1 is implemented
# T = FuncDesignerTranslator(p2)
# vect_func = lambda x: func(T.vector2point(x))
# TODO: derivatives
# !!!!!!!!!!!!! TODO: derivatives should not be zeros! Fix it!
r = oofun(f, None)
r.fun = lambda *args: f(point=r._Point)
# TODO : use decorators here
tmp_f = r._getFunc
tmp_D = r._D
def aux_f(*args, **kwargs):
if isinstance(args[0], dict):
r._Point = args[0]
return tmp_f(*args, **kwargs)
def aux_D(*args, **kwargs):
raise FuncDesignerException("derivatives from scipy_quad are not implemented yet")
if isinstance(args[0], dict):
r._Point = args[0]
return tmp_D(*args, **kwargs)
r._getFunc = aux_f
r._D = aux_D
return r
