diff --git a/droplets/droplets.py b/droplets/droplets.py
index 4edc126..9dc58da 100644
--- a/droplets/droplets.py
+++ b/droplets/droplets.py
@@ -280,7 +280,8 @@ def get_dtype(cls, **kwargs) -> DTypeList:
             :class:`numpy.dtype`: the (structured) dtype associated with this class
         """
         position = np.atleast_1d(kwargs.pop("position"))
-        assert not kwargs  # no more keyword arguments
+        if kwargs:
+            raise ValueError(f"Leftover keyword arguments: {kwargs}")
         dim = len(position)
         return [("position", float, (dim,)), ("radius", float)]
 
@@ -789,7 +790,8 @@ def amplitudes(self) -> np.ndarray:
     @amplitudes.setter
     def amplitudes(self, value: np.ndarray | None = None) -> None:
         if value is None:
-            assert self.modes == 0
+            if self.modes != 0:
+                raise ValueError("Require values for amplitudes")
             self.data["amplitudes"] = np.broadcast_to(0.0, (0,))
         else:
             self.data["amplitudes"] = np.broadcast_to(value, (self.modes,))
diff --git a/droplets/emulsions.py b/droplets/emulsions.py
index ee71f3e..69aa397 100644
--- a/droplets/emulsions.py
+++ b/droplets/emulsions.py
@@ -153,7 +153,8 @@ def get_position():
 
         else:
             bnds = np.atleast_2d(grid_or_bounds)
-            assert bnds.ndim == 2 and bnds.shape[0] > 0 and bnds.shape[1] == 2
+            if bnds.ndim != 2 or bnds.shape[0] == 0 or bnds.shape[1] != 2:
+                raise ValueError(f"Bounds must be array of shape (n, 2), got {bnds}")
 
             def get_position():
                 return rng.uniform(bnds[:, 0], bnds[:, 1])
diff --git a/droplets/image_analysis.py b/droplets/image_analysis.py
index 82e7911..f5f4b16 100644
--- a/droplets/image_analysis.py
+++ b/droplets/image_analysis.py
@@ -417,7 +417,8 @@ def locate_droplets(
     Returns:
         :class:`~droplets.emulsions.Emulsion`: All detected droplets
     """
-    assert isinstance(phase_field, ScalarField)
+    if not isinstance(phase_field, ScalarField):
+        raise TypeError("`phase_field` must be ScalarField")
     dim = phase_field.grid.dim  # dimensionality of the space
 
     if modes > 0 and dim not in [2, 3]:
@@ -581,7 +582,8 @@ def refine_droplet(
         :class:`~droplets.droplets.DiffuseDroplet`:
             The refined droplet as an instance of the argument `droplet`
     """
-    assert isinstance(phase_field, ScalarField)
+    if not isinstance(phase_field, ScalarField):
+        raise TypeError("`phase_field` must be ScalarField")
     if least_squares_params is None:
         least_squares_params = {}
     if tolerance is not None:
diff --git a/droplets/tools/spherical.py b/droplets/tools/spherical.py
index 263d6f5..c485617 100644
--- a/droplets/tools/spherical.py
+++ b/droplets/tools/spherical.py
@@ -320,7 +320,8 @@ def points_cartesian_to_spherical(points: np.ndarray) -> np.ndarray:
         :class:`~numpy.ndarray`: Points (r, θ, φ) in spherical coordinates
     """
     points = np.atleast_1d(points)
-    assert points.shape[-1] == 3, "Points must have 3 coordinates"
+    if points.shape[-1] != 3:
+        raise DimensionError("Points must have 3 coordinates")
 
     ps_spherical = np.empty(points.shape)
     # calculate radius in [0, infinity]
@@ -343,7 +344,8 @@ def points_spherical_to_cartesian(points: np.ndarray) -> np.ndarray:
         :class:`~numpy.ndarray`: Points in Cartesian coordinates
     """
     points = np.atleast_1d(points)
-    assert points.shape[-1] == 3, "Points must have 3 coordinates"
+    if points.shape[-1] != 3:
+        raise DimensionError("Points must have 3 coordinates")
 
     sin_θ = np.sin(points[..., 1])
     ps_cartesian = np.empty(points.shape)