Merge pull request #1629 from FlorianPfaff/meshgrid

Explicitly specify meshgrid convention (can be different for different backends)

Author: FlorianPfaff

pyrecest/distributions/cart_prod/abstract_hypercylindrical_distribution.py

@@ -351,7 +351,7 @@ def plot(self, *args, **kwargs):
                 m[self.bound_dim] + lin_size * sigma,
                 100,
             )
-            x, theta = meshgrid(x_vals, theta_vals)
+            x, theta = meshgrid(x_vals, theta_vals, indexing="ij")
 
             # Evaluate pdf at the grid points
             points = vstack((x.ravel(), theta.ravel())).T
@@ -398,7 +398,7 @@ def plot_cylinder(self, limits_linear=None):
 
         phi = linspace(0.0, 2 * pi, 100)
         lin = linspace(limits_linear[0], limits_linear[1], 100)
-        Phi, L = meshgrid(phi, lin)
+        Phi, L = meshgrid(phi, lin, indexing="ij")
         points = vstack([Phi.ravel(), L.ravel()]).T
         C = self.pdf(points)
         C = C.reshape(Phi.shape)

pyrecest/distributions/cart_prod/partially_wrapped_normal_distribution.py

@@ -74,7 +74,7 @@ def pdf(self, xs, m: Union[int, int32, int64] = 3):
         multiples = array(range(-m, m + 1)) * 2.0 * pi
 
         # create meshgrid for all combinations of multiples
-        mesh = array(meshgrid(*[multiples] * self.bound_dim)).reshape(
+        mesh = array(meshgrid(*[multiples] * self.bound_dim, indexing="ij")).reshape(
             -1, self.bound_dim
         )
 

pyrecest/distributions/hypersphere_subset/abstract_hyperhemispherical_distribution.py

@@ -182,6 +182,7 @@ def plot_hemisphere(resolution: Union[int, int32, int64] = 150):
             linspace(-1, 1, resolution),
             linspace(-1, 1, resolution),
             linspace(0, 1, resolution // 2),
+            indexing="ij",
         )
         mask = (x**2 + y**2 + z**2 <= 1) & (z >= 0)
         x, y, z = x[mask].reshape(-1, 1), y[mask].reshape(-1, 1), z[mask].reshape(-1, 1)

pyrecest/distributions/hypertorus/abstract_hypertoroidal_distribution.py

@@ -203,7 +203,7 @@ def plot(self, resolution=128, **kwargs):
         elif self.dim == 2:
             step = 2 * pi / resolution
             alpha, beta = meshgrid(
-                arange(0.0, 2.0 * pi, step), arange(0.0, 2.0 * pi, step)
+                arange(0.0, 2.0 * pi, step), arange(0.0, 2.0 * pi, step), indexing="ij"
             )
             f = self.pdf(column_stack((alpha.ravel(), beta.ravel())))
             f = f.reshape(alpha.shape)

pyrecest/distributions/nonperiodic/abstract_linear_distribution.py

@@ -314,7 +314,7 @@ def plot(self, *args, plot_range=None, **kwargs):
         elif self.dim == 2:
             x = linspace(plot_range[0], plot_range[1], 100)
             y = linspace(plot_range[2], plot_range[3], 100)
-            x_grid, y_grid = meshgrid(x, y)
+            x_grid, y_grid = meshgrid(x, y, indexing="ij")
             z_grid = self.pdf(column_stack((x_grid.ravel(), y_grid.ravel())))
 
             ax = plt.axes(projection="3d")