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early allocator support and support for boost multiprecision cpp_int

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This commit is contained in:
Hans Dembinski
2017-01-26 23:07:37 +01:00
parent 6d2e969697
commit d09830e272
5 changed files with 121 additions and 91 deletions
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21
src/python/histogram.cpp
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@@ -229,23 +229,28 @@ histogram_variance(python::tuple args, python::dict kwargs) {
return object(self.variance(idx + 0, idx + self.dim()));
}
class histogram_access {
public:
struct python_access {
static
python::dict
histogram_array_interface(dynamic_histogram<>& self) {
array_interface(dynamic_histogram<>& self) {
const auto& b = self.storage_.buffer_;
if (b.type_.id_ == 5) {
PyErr_SetString(PyExc_RuntimeError, "cannot convert multiprecision storage to numpy array");
boost::python::throw_error_already_set();
}
python::dict d;
python::list shapes;
python::list strides;
std::size_t stride = 1;
if (self.depth() == sizeof(detail::weight_t)) {
if (b.type_.id_ == -1) {
stride *= sizeof(double);
d["typestr"] = python::str("|f") + python::str(stride);
strides.append(stride);
stride *= 2;
shapes.append(2);
} else {
stride *= self.depth();
stride *= b.type_.depth_;
d["typestr"] = python::str("|u") + python::str(stride);
}
for (unsigned i = 0; i < self.dim(); ++i) {
@@ -254,7 +259,7 @@ public:
stride *= shape(self.axis(i));
}
d["shape"] = python::tuple(shapes);
d["data"] = python::make_tuple(reinterpret_cast<uintptr_t>(self.data()), false);
d["data"] = python::make_tuple(reinterpret_cast<uintptr_t>(b.ptr_), false);
d["strides"] = python::tuple(strides);
return d;
}
@@ -279,9 +284,9 @@ void register_histogram()
// shadowed C++ ctors
.def(init<const dynamic_histogram<>::axes_t&>())
.add_property("__array_interface__",
&histogram_access::histogram_array_interface)
&python_access::array_interface)
.add_property("dim", &dynamic_histogram<>::dim,
"dimensions of the histogram (number of axes)")
"dimensions of the histogram (number of axes)")
.def("axis", histogram_axis,
":param int i: index of the axis\n"
":returns: axis object for axis i",