def __init__(self, address, value):
super(ConstantNode, self).__init__(address)
if isinstance(value, VentureValue):
# Possible for programmatic construction, e.g. builtin.py
# Will also occur for literal atoms, since there's no other way
# to tell them apart from literal numbers.
self.value = value
else: # In eval
self.value = ExpressionType().asVentureValue(value)
def parse_expr(self, expr, command):
special_names = [VentureSymbol(x) for x in ['iter', 'time', 'score']]
if (isinstance(expr, VentureArray) and expr.lookup(VentureInteger(0))
== VentureSymbol('labelled')):
# The first element is the command, the second is the label for
# the command
stack_dict = expr.lookup(VentureInteger(1)).asStackDict()
name = expr.lookup(VentureInteger(2)).symbol
elif command == 'printf' and expr in special_names:
name = expr.getSymbol()
stack_dict = None
else:
# Generate the default name, get the stack dict
stack_dict = expr.asStackDict()
name = self.default_name_for_exp(ExpressionType().asPython(expr))
return name, stack_dict
def unboxExpression(self, exp):
return ExpressionType().asPython(VentureValue.fromStackDict(exp))
def default_names_from_exprs(self, exprs):
return [
self.default_name_for_exp(ExpressionType().asPython(e))
for e in exprs
]
def plotf_to_file(self, basenames, spec, dataset):
filenames = ExpressionType().asPython(basenames)
spec = ExpressionType().asPython(spec)
spec = self._canonicalize_tree(spec)
PlotSpec(spec).plot(dataset.asPandas(), dataset.ind_names,
self._format_filenames(filenames, spec))
def plotf(self, spec, dataset):
spec = ExpressionType().asPython(spec)
spec = self._canonicalize_tree(spec)
PlotSpec(spec).plot(dataset.asPandas(), dataset.ind_names)