Merge branch 'main' into dl3_reader

Author: mstrzys

src/pybkgmodel/camera.py

@@ -1,4 +1,4 @@
-import numpy
+import numpy as np
 import scipy.special
 import scipy.optimize
 
@@ -36,7 +36,7 @@ def solid_angle_lat_lon_rectangle(theta_E, theta_W, phi_N, phi_S):
     phi_S = phi_S.to(u.Unit("rad"))
     theta_E = theta_E.to(u.Unit("rad"))
     theta_W = theta_W.to(u.Unit("rad"))
-    solid_angle = (numpy.sin(phi_N) - numpy.sin(phi_S)) * (theta_E.to_value() - theta_W.to_value()) * u.sr
+    solid_angle = (np.sin(phi_N) - np.sin(phi_S)) * (theta_E.to_value() - theta_W.to_value()) * u.sr
 
     return solid_angle
 
@@ -58,7 +58,7 @@ def cstat(y, model_y):
         2 * log-likelihood value.
 
     """
-    val = -2 * numpy.sum(y * numpy.log(model_y) - model_y - scipy.special.gammaln(y+1))
+    val = -2 * np.sum(y * np.log(model_y) - model_y - scipy.special.gammaln(y+1))
 
     return val
 
@@ -117,16 +117,16 @@ def nodespec_integral(energy_edges, dnde):
     if isinstance(dnde.unit, u.DexUnit):
         dnde = dnde.physical
 
-    energy = numpy.sqrt(energy_edges[1:] * energy_edges[:-1])
-    counts = numpy.zeros(len(energy)) * u.one
+    energy = np.sqrt(energy_edges[1:] * energy_edges[:-1])
+    counts = np.zeros(len(energy)) * u.one
 
     xunit = u.DexUnit(energy_edges.unit)
     yunit = u.DexUnit(dnde.unit)
 
-    dx = numpy.diff(energy.to(xunit).value)
-    dy = numpy.diff(dnde.to(yunit).value)
+    dx = np.diff(energy.to(xunit).value)
+    dy = np.diff(dnde.to(yunit).value)
     indicies = dy / dx
-    indicies = numpy.concatenate(
+    indicies = np.concatenate(
         (indicies[:1], indicies, indicies[-1:])
     )
 
@@ -169,12 +169,12 @@ def __init__(self, counts, xedges, yedges, energy_edges, center=None, mask=None,
         ny = yedges.size - 1
 
         if mask is None:
-            mask = numpy.ones((nx, ny), dtype=bool)
+            mask = np.ones((nx, ny), dtype=np.bool)
 
         if exposure is None:
-            exposure = numpy.ones((nx, ny), dtype=numpy.float) * u.s
+            exposure = np.ones((nx, ny), dtype=np.float) * u.s
         elif exposure.shape == ():
-            exposure = numpy.repeat(exposure, nx * ny).reshape((nx, ny))
+            exposure = np.repeat(exposure, nx * ny).reshape((nx, ny))
 
         self.raw_counts = counts
         self.xedges = xedges
@@ -244,7 +244,7 @@ def differential_rate(self, index=None):
         Parameters
         ----------
         index: float
-            Power law spectral index to assume.
+            Power law spectral index to assume. 
             If none, will be dynamically determined assuming
             a "node function" for the spectral shape.
 
@@ -269,7 +269,7 @@ def differential_rate(self, index=None):
             dnde_unit = u.DexUnit(dnde.unit)
             for xi in range(self.rate.shape[1]):
                 for yi in range(self.rate.shape[2]):
-                    if not numpy.any(dnde[:, xi, yi] == 0):
+                    if not np.any(dnde[:, xi, yi] == 0):
                         opt = scipy.optimize.minimize(
                             lambda x: node_cnt_diff((x*dnde_unit).physical, self.energy_edges, self.counts[:, xi, yi], poisson=True),
                             x0=dnde[:, xi, yi].to(dnde_unit).value
@@ -318,7 +318,7 @@ def mask_region(self, region):
         # Set up an "Airy's zenithal" projection
         # Vector properties may be set with Python lists, or np arrays
         dummy_wcs.wcs.crpix = [-234.75, 8.3393]
-        dummy_wcs.wcs.cdelt = numpy.array([-0.066667, 0.066667])
+        dummy_wcs.wcs.cdelt = np.array([-0.066667, 0.066667])
         dummy_wcs.wcs.crval = [0, -90]
         dummy_wcs.wcs.ctype = ["RA---AIR", "DEC--AIR"]
         dummy_wcs.wcs.set_pv([(2, 1, 45.0)])
@@ -329,7 +329,7 @@ def mask_region(self, region):
     def mask_reset(self):
         """_summary_
         """
-        self.mask = numpy.ones((self.xedges.size - 1, self.yedges.size - 1), dtype=bool)
+        self.mask = np.ones((self.xedges.size - 1, self.yedges.size - 1), dtype=np.bool)
 
 
     def plot(self, energy_bin_id=0, ax_unit='deg', val_unit='1/s', **kwargs):
@@ -394,7 +394,7 @@ def get_pixel_areas(self):
         for i in range(nx):
             for j in range(ny):
                 area[i, j] = solid_angle_lat_lon_rectangle(self.xedges[i], self.xedges[i+1], self.yedges[j], self.yedges[j+1])
-
+        
         return area
 
     def to_hdu(self, name='BACKGROUND'):