fix: commenting out osqp

LoopStructural/interpolators/discrete_interpolator.py

@@ -475,29 +475,29 @@ def build_matrix(self, square=True, damp=0.0, ie=False):
     def _solve_osqp(self, P, A, q, l, u):
 
 
-        import osqp
-        m = A.shape[0]
-        n = A.shape[1]
-        Ad = sparse.random(m, n, density=0.7, format='csc')
-        b = np.random.randn(m)
-
-        # OSQP data
-        P = sparse.block_diag([sparse.csc_matrix((n, n)), sparse.eye(m)], format='csc')
-        q = np.zeros(n+m)
-        A = sparse.vstack([
-                sparse.hstack([Ad, -sparse.eye(m)]),
-                sparse.hstack([sparse.eye(n), sparse.csc_matrix((n, m))])], format='csc')
-        l = np.hstack([b, np.zeros(n)])
-        u = np.hstack([b, np.ones(n)])
-
-        # Create an OSQP object
-        prob = osqp.OSQP()
-
-        # Setup workspace
-        prob.setup(P, q, A, l, u)
-
-        # Solve problem
-        res = prob.solve()
+        # import osqp
+        # m = A.shape[0]
+        # n = A.shape[1]
+        # Ad = sparse.random(m, n, density=0.7, format='csc')
+        # b = np.random.randn(m)
+
+        # # OSQP data
+        # P = sparse.block_diag([sparse.csc_matrix((n, n)), sparse.eye(m)], format='csc')
+        # q = np.zeros(n+m)
+        # A = sparse.vstack([
+        #         sparse.hstack([Ad, -sparse.eye(m)]),
+        #         sparse.hstack([sparse.eye(n), sparse.csc_matrix((n, m))])], format='csc')
+        # l = np.hstack([b, np.zeros(n)])
+        # u = np.hstack([b, np.ones(n)])
+
+        # # Create an OSQP object
+        # prob = osqp.OSQP()
+
+        # # Setup workspace
+        # prob.setup(P, q, A, l, u)
+
+        # # Solve problem
+        # res = prob.solve()
 
 
         # Create an OSQP object

LoopStructural/modelling/features/geological_feature.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 
-from LoopStructural.utils import getLogger
+from LoopStructural.utils import getLogger, LoopValueError
 
 logger = getLogger(__name__)
 
@@ -134,6 +134,8 @@ def evaluate_value(self, evaluation_points):
             numpy array containing evaluated values
 
         """
+        if evaluation_points.shape[1] != 3:
+            raise LoopValueError("Need Nx3 array of xyz points to evaluate value")
         # TODO need to add a generic type checker for all methods
         # if evaluation_points is not a numpy array try and convert
         # otherwise error
@@ -171,6 +173,8 @@ def evaluate_gradient(self, evaluation_points):
         -------
 
         """
+        if evaluation_points.shape[1] != 3:
+            raise LoopValueError("Need Nx3 array of xyz points to evaluate gradient")
         self.builder.up_to_date()
         v = np.zeros(evaluation_points.shape)
         v[:] = np.nan

LoopStructural/modelling/features/geological_feature_builder.py

@@ -1,9 +1,6 @@
 """
 Feature builder
 """
-import copy
-import logging
-
 import numpy as np
 import pandas as pd