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Started to work on #1898, are we already done?

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This commit is contained in:
Jorrit Wronski
2020-05-11 08:26:11 +02:00
parent 86b02cd6a1
commit 4780033127
1 changed files with 28 additions and 16 deletions
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44
wrappers/Python/CoolProp/CoolProp.pyx
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@@ -393,10 +393,10 @@ cpdef PropsSI(in1, in2, in3 = None, in4 = None, in5 = None, in6 = None, in7 = No
is_iterable3 = iterable(in3)
is_iterable5 = iterable(in5)
if _numpy_supported and is_iterable3 and isinstance(in3, np.ndarray) and (np.prod(in3.shape) != max(in3.shape)):
raise ValueError("Input 3 is not one-dimensional")
if _numpy_supported and is_iterable5 and isinstance(in5, np.ndarray) and (np.prod(in5.shape) != max(in5.shape)):
raise ValueError("Input 5 is not one-dimensional")
#if _numpy_supported and is_iterable3 and isinstance(in3, np.ndarray) and (np.prod(in3.shape) != max(in3.shape)):
# raise ValueError("Input 3 is not one-dimensional")
#if _numpy_supported and is_iterable5 and isinstance(in5, np.ndarray) and (np.prod(in5.shape) != max(in5.shape)):
# raise ValueError("Input 5 is not one-dimensional")
if is_iterable1 or is_iterable3 or is_iterable5:
# Prepare the output datatype
@@ -405,24 +405,34 @@ cpdef PropsSI(in1, in2, in3 = None, in4 = None, in5 = None, in6 = None, in7 = No
else:
vin1 = in1
target_shape = None # out.reshape(target_shape)
target_size = None
# Resize state variable inputs
if is_iterable3 and is_iterable5:
if len(in3) != len(in5):
raise TypeError("Sizes of Prop1 {n1:d} and Prop2 {n2:d} to PropsSI are not the same".format(n1 = len(in3), n2 = len(in5)))
target_shape = in3.shape
target_size = in3.size
if in3.shape != in5.shape:
raise TypeError("Shapes of Prop1 {n1} and Prop2 {n2} to PropsSI are not the same".format(n1 = in3.shape, n2 = in5.shape))
else:
vval1 = in3
vval2 = in5
vval1 = np.ravel(in3)
vval2 = np.ravel(in5)
elif is_iterable3 and not is_iterable5:
vval1 = in3
vval2.resize(len(in3))
templist = [in5]*len(in3)
target_shape = in3.shape
target_size = in3.size
vval1 = np.ravel(in3)
vval2.resize(target_size)
templist = [in5]*target_size
vval2 = templist
elif is_iterable5 and not is_iterable3:
vval1.resize(len(in5))
templist = [in3]*len(in5)
target_shape = in5.shape
target_size = in5.size
vval1.resize(target_size)
templist = [in3]*target_size
vval1 = templist
vval2 = in5
vval2 = np.ravel(in5)
else:
target_shape = None
target_size = None
vval1.resize(1)
vval1[0] = in3
vval2.resize(1)
@@ -444,8 +454,10 @@ cpdef PropsSI(in1, in2, in3 = None, in4 = None, in5 = None, in6 = None, in7 = No
# Check that we got some output
if outmat.empty():
raise ValueError(_get_global_param_string(b'errstring'))
return ndarray_or_iterable(outmat)
if target_shape is not None:
return ndarray_or_iterable(outmat).reshape(target_shape)
else:
return ndarray_or_iterable(outmat)
else:
# This version takes doubles
val = _PropsSI(in1, in2, in3, in4, in5, in6)