diff --git a/qpms/lattices.py b/qpms/lattices.py
index 94abed2..aaf2dbe 100644
--- a/qpms/lattices.py
+++ b/qpms/lattices.py
@@ -1,13 +1,16 @@
 '''
 Object oriented approach for the classical multiple scattering problem.
 '''
-
 import numpy as np
+import time
+import scipy
+import sys
 from qpms_c import * # TODO be explicit about what is imported
-from .qpms_p import * # TODO be explicit about what is imported
+from .qpms_p import nelem2lMax # TODO be explicit about what is imported
 
-class Scatterers(object):
+class Scattering(object):
     '''
+
     This is the most general class for a system of scatterers
     in a non-lossy homogeneous background
     to be solved with the multiple_scattering method. The scatterers,
@@ -22,6 +25,50 @@ class Scatterers(object):
     the object can be recycled for many incident field shapes
     at the given frequency.
 
+    Attributes should be perhaps later redefined to be read-only
+    (or make descriptors for them).
+
+    Args:
+        positions: (N,3)-shaped real array
+        TMatrices: (N,2,nelem,2,nelem)-shaped array
+        k_0 (float): Wave number for the space between scatterers.
+
+    Attributes:
+        positions:
+        TMatrices:
+        k_0 (float): Wave number for the space between scatterers.
+        lMax (int): Absolute maximum l for all scatterers. Depending on implementation,
+            lMax can be smaller for some individual scatterers in certain subclasses.
+        prepared (bool): Keeps information whether the interaction matrix has
+            already been built and factorized.
+        
 
     '''
+    def __init__(self, positions, TMatrices, k_0, lMax = None, verbose=False):
+        self.positions = positions
+        self.TMatrices = TMatrices
+        self.k_0 = k_0
+        self.lMax = lMax ? lMax : nelem2lMax(TMatrices.shape[-1])
+        self.prepared = False
+
+    def prepare(self, keep_interaction_matrix = False, verbose=False):
+        if not self.prepared:
+            if not self.interaction_matrix:
+                self.build_interaction_matrix(verbose=verbose)
+            self.lupiv = scipy.linalg_lu_factor(interaction_matrix)
+            if not keep_interaction_matrix:
+                self.interaction_matrix = None
+            self.prepared = True
+
+    def build_interaction_matrix(verbose = False):
+        pass
+
+    def scatter(pq_0_c, verbose = False):
+        self.prepare(verbose=verbose)
+
+
+        pass
+
+
+