numpy 2.0 compatibility

pyproject.toml

@@ -2,8 +2,8 @@
 requires = ["setuptools",
             "wheel",
             "Cython",
-            "numpy==1.23.2; python_version >= '3.10'",
-            "oldest-supported-numpy; python_version >= '3.8' and python_version < '3.10'",
+            "numpy==2.0.0,<2.1.0; python_version >= '3.9'",
+            "oldest-supported-numpy; python_version >= '3.8' and python_version < '3.9'",
             "numpy==1.16.1; python_version <= '3.7' and python_version >= '3'",
             "numpy==1.13.3; python_version=='2.7'",
             "scipy"]

requirements.txt

@@ -1,3 +1,4 @@
-numpy
+numpy>=2.0.0; python_version >= '3.9'
+numpy; python_version < '3.9'
 scipy
 six

src/ms_peak_picker/_c/peak_statistics.pyx

@@ -32,6 +32,12 @@ cdef DTYPE_t minimum_signal_to_noise = 4.0
 
 cdef object np_zeros = np.zeros
 
+cdef object trapz = None
+try:
+    trapz = np.trapz
+except AttributeError:
+    trapz = np.trapezoid
+
 
 @cython.nonecheck(False)
 @cython.cdivision(True)
@@ -651,7 +657,7 @@ cpdef double gaussian_volume(FittedPeak peak):
     cdef:
         np.ndarray[double, ndim=1] x, y
     x, y = gaussian_shape(peak)
-    return np.trapz(y, x, dx=0.0001)
+    return trapz(y, x, dx=0.0001)
 
 
 cdef class PeakShapeModel(object):

src/ms_peak_picker/peak_statistics.py

@@ -3,6 +3,11 @@
 from .utils import range
 from .search import get_nearest
 
+trapz = None
+try:
+    trapz = np.trapz
+except AttributeError:
+    trapz = np.trapezoid
 
 minimum_signal_to_noise = 4.
 
@@ -398,7 +403,7 @@ def gaussian_error(peak, mz, intensity):
 
 def gaussian_volume(peak):
     x, y = gaussian_shape(peak)
-    return np.trapz(y, x, dx=0.0001)
+    return trapz(y, x, dx=0.0001)
 
 
 def lorentzian_predict(peak, mz):
@@ -426,7 +431,7 @@ def lorentzian_error(peak, mz, intensity):
 
 def lorentzian_volume(peak):
     x, y = lorentzian_shape(peak)
-    return np.trapz(y, x, dx=0.0001)
+    return trapz(y, x, dx=0.0001)
 
 
 class PeakShapeModel(object):