Merge branch 'main' into developer

python/CMakeLists.txt

@@ -49,6 +49,7 @@ set(PYTHON_EXAMPLES
     examples/fits.py
 )
 
+
 # Copy the python examples to the build directory
 foreach(FILE ${PYTHON_EXAMPLES})
     configure_file(${FILE} ${CMAKE_BINARY_DIR}/${FILE}  )

python/examples/play.py

@@ -8,6 +8,7 @@ import numpy as np
 import boost_histogram as bh
 import time
 
+
 import aare
 
 data = np.random.normal(10, 1, 1000)
@@ -19,4 +20,31 @@ hist.fill(data)
 x = hist.axes[0].centers
 y = hist.values()
 y_err = np.sqrt(y)+1
-res = aare.fit_gaus(x, y, y_err, chi2 = True)
+res = aare.fit_gaus(x, y, y_err, chi2 = True)
+
+
+        
+t_elapsed = time.perf_counter()-t0
+print(f'Histogram filling took: {t_elapsed:.3f}s {total_clusters/t_elapsed/1e6:.3f}M clusters/s')
+
+histogram_data = hist3d.counts()
+x = hist3d.axes[2].edges[:-1]
+
+y = histogram_data[100,100,:]
+xx = np.linspace(x[0], x[-1])
+# fig, ax = plt.subplots()
+# ax.step(x, y, where = 'post')
+
+y_err = np.sqrt(y)
+y_err = np.zeros(y.size)
+y_err += 1
+
+# par = fit_gaus2(y,x, y_err)
+# ax.plot(xx, gaus(xx,par))
+# print(par)
+
+res = fit_gaus(y,x)
+res2 = fit_gaus(y,x, y_err)
+print(res)
+print(res2)
+

python/src/fit.hpp

@@ -9,6 +9,7 @@
 namespace py = pybind11;
 using namespace pybind11::literals;
 
+
 void define_fit_bindings(py::module &m) {
 
     // TODO! Evaluate without converting to double
@@ -54,6 +55,7 @@ void define_fit_bindings(py::module &m) {
         )",
         py::arg("x"), py::arg("par"));
 
+
     m.def(
         "fit_gaus",
         [](py::array_t<double, py::array::c_style | py::array::forcecast> x,
@@ -76,6 +78,7 @@ void define_fit_bindings(py::module &m) {
             }
         },
         R"(
+
 Fit a 1D Gaussian to data.
 
 Parameters
@@ -95,6 +98,7 @@ n_threads : int, optional
            py::array_t<double, py::array::c_style | py::array::forcecast> y,
            py::array_t<double, py::array::c_style | py::array::forcecast> y_err,
            int n_threads) {
+
             if (y.ndim() == 3) {
                 // Allocate memory for the output
                 // Need to have pointers to allow python to manage
@@ -142,6 +146,7 @@ n_threads : int, optional
             }
         },
         R"(
+
 Fit a 1D Gaussian to data with error estimates.
 
 Parameters
@@ -189,6 +194,7 @@ n_threads : int, optional
            int n_threads) {
             if (y.ndim() == 3) {
                 auto par = new NDArray<double, 3>({y.shape(0), y.shape(1), 2});
+
                 auto par_err =
                     new NDArray<double, 3>({y.shape(0), y.shape(1), 2});
 
@@ -221,6 +227,7 @@ n_threads : int, optional
                 return py::dict("par"_a = return_image_data(par),
                                 "par_err"_a = return_image_data(par_err),
                                 "chi2"_a = chi2, "Ndf"_a = y.size() - 2);
+
             } else {
                 throw std::runtime_error("Data must be 1D or 3D");
             }