Hi,
I've been using matplotlib for a little while and am finding it very
useful. Yesterday, though, I hit a problem:
Because I didn't read the docs properly, I tried to use
matplotlib.transforms.scale_transform
like this:
t = scale_transform(1.0, 2.0)
but then I got a core-dump when trying to use it:
from matplotlib.transforms import scale_transform
t = scale_transform(1.0, 2.0)
print t.xy_tup((1.0, 0.2))
What I should have done was this, which works:
from matplotlib.transforms import scale_transform, Value
t = scale_transform(Value(1.0), Value(2.0))
print t.xy_tup((1.0, 0.2))
The function _transforms_module::new_affine() in _transforms.cpp does
contain checks that its args are LazyValue objects, but it seems to
ignore the results. The following patch (against 0.90.1) makes the
constructor throw a TypeError if it doesn't get what it wants. (It also
fixes a small typo in a separate error string.)
--- ORIG/_transforms.cpp 2007-07-17 10:10:37.443202000 +0100
+++ NEW/_transforms.cpp 2007-07-17 10:11:00.257365000 +0100
@@ -42,7 +42,7 @@
int
LazyValue::compare(const Py::Object &other) {
if (!check(other))
- throw Py::TypeError("Can on compare LazyValues with LazyValues");
+ throw Py::TypeError("Can only compare LazyValues with LazyValues");
LazyValue* pother = static_cast<LazyValue*>(other.ptr());
double valself = val();
double valother = pother->val();
@@ -2116,12 +2116,13 @@
args.verify_length(6);
- LazyValue::check(args[0]);
- LazyValue::check(args[1]);
- LazyValue::check(args[2]);
- LazyValue::check(args[3]);
- LazyValue::check(args[4]);
- LazyValue::check(args[5]);
+ if (!LazyValue::check(args[0])
+ || !LazyValue::check(args[1])
+ || !LazyValue::check(args[2])
+ || !LazyValue::check(args[3])
+ || !LazyValue::check(args[4])
+ || !LazyValue::check(args[5]))
+ throw Py::TypeError("Affine(a, b, c, d, tx, ty) expected 6 LazyValue
args");
LazyValue* a = static_cast<LazyValue*>(args[0].ptr());
LazyValue* b = static_cast<LazyValue*>(args[1].ptr());
Would this be worth applying? By the look of the code in transform.py,
translation_transform() and possibly others might be affected by this
too. Maybe a better solution might be to automatically construct Value
objects from Python floats where required, but that might need a bit
more thought.
Ben.
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