def plvar( varname, value ):
"""Emulating PLearn's $DEFINE statement.
An old .plearn script (included with include()) may depend on some
variables to be defined externally. If one wants to define that
variable within a PyPLearn script, he must use this function with two
arguments::
plvar( 'DATASET',
pl.AutoVMatrix( specification = "somefile.pmat",
inputsize = 10,
targetsize = 1
)
)
which is strictly equivalent to the old::
$DEFINE{DATASET}{ AutoVMatrix( specification = "somefile.pmat";
inputsize = 10;
targetsize = 1 ) }
If, on the other hand, a variable is defined within the PLearn script
and must be referenced within PyPLearn, the simple C{plvar('DATASET')}
will refer to the variable just as C{${DATASET}} would have.
"""
if value is None:
snippet = '${%s}' % varname
else:
snippet = '$DEFINE{%s}{ %s }' % (
varname, plearn_repr( value, indent_level+1 )
)
return PLearnSnippet( snippet )
print sub2.__class__.__name__, id(sub2.__class__)
print sub2
print
sub3 = pl.Subclass()
print sub3.__class__.__name__, id(sub3.__class__)
print sub3
print
if __name__ == "__main__":
print TMat(2, 2, ["allo", "mon", "petit", "coco"]).plearn_repr()
print
print "Simple list:\n"
a = [1, 2, 3]
print plearn_repr(a)
print plearn_repr(a)
print "---"
print
print "TVec( list ):\n"
b = TVec(a)
print plearn_repr(b)
print plearn_repr(b)
print "---"
print
print "copy.deepcopy( tvec ):\n"
c = copy.deepcopy(b)
print plearn_repr(c)
print plearn_repr(c)
def elemFormat(e):
if isinstance(e, str):
return e # Not quoted...
elif isinstance(e, float):
return "%.2f" % e
return plearn_repr(e)
def write_typed(self, x):
spec = plearn_repr(x) + ' '
self.write(spec)
def elemFormat(e):
if isinstance(e, str):
return e # Not quoted...
elif isinstance(e, float):
return "%.2f"%e
return plearn_repr(e)
def __str__( self ):
"""Calls plearn_repr global function over itself."""
# It is most important no to call this instance's plearn_repr
# method!!! Indeed, if we did so, we'd neglect to add the current
# instance in the representations map...
return plearn_repr( self, indent_level = 0 )
def write_typed(self, x):
spec = plearn_repr(x)+' '
self.write(spec)
def __str__( self ):
return plearn_repr(self, indent_level=0)
def __str__(self):
"""Calls plearn_repr global function over itself."""
# It is most important no to call this instance's plearn_repr
# method!!! Indeed, if we did so, we'd neglect to add the current
# instance in the representations map...
return plearn_repr(self, indent_level=0)