diff --git a/EXPtools/basis_builder/makemodel.py b/EXPtools/basis_builder/makemodel.py
index 9d6aa01..cf5f3fc 100644
--- a/EXPtools/basis_builder/makemodel.py
+++ b/EXPtools/basis_builder/makemodel.py
@@ -1,5 +1,6 @@
 import numpy as np
 import scipy 
+from scipy.interpolate import interp1d, BSpline, splrep
 
 def empirical_density_profile(rbins, pos, mass):
     """
@@ -30,13 +31,16 @@ def empirical_density_profile(rbins, pos, mass):
     V_shells = 4/3 * np.pi * (rbins[1:]**3 - rbins[:-1]**3)
 
     # Compute density profile
-    density, _ = np.histogram(r_p, bins=rbins+1, weights=mass)
+    density, _ = np.histogram(r_p, bins=rbins, weights=mass)
     density /= V_shells
 
-    # Compute bin centers and return profile
-    #radius = 0.5 * (rbins[1:] + rbins[:-1])
+    #compute bin centers and return profile
+    radius = 0.5 * (rbins[1:] + rbins[:-1])
 
-    return density
+    tck_s = splrep(radius, np.log10(density), s=0.15)
+    dens2 = BSpline(*tck_s)(radius)
+
+    return radius, 10**dens2
 
 
 
@@ -142,7 +146,10 @@ def makemodel(func, M, funcargs, rvals = 10.**np.linspace(-2.,4.,2000), pfile=''
     R = np.nanmax(rvals)
     
     # query out the density values
-    dvals = func(rvals,*funcargs)
+    if func == empirical_density_profile:
+        rvals, dvals = func(rvals,*funcargs)
+    else:
+        dvals = func(rvals,*funcargs)
 
     # make the mass and potential arrays
     mvals = np.zeros(dvals.size)
diff --git a/EXPtools/utils/coefficients.py b/EXPtools/utils/coefficients.py
index d44ad9d..ee1593d 100644
--- a/EXPtools/utils/coefficients.py
+++ b/EXPtools/utils/coefficients.py
@@ -18,7 +18,7 @@ def remove_terms(original_coefficients, n, l, m):
         for i in range(len(l)):
             lm_idx = int(l[i]*(l[i]+1) / 2) + m[i]
             print(n[i],l[i],m[i], lm_idx)
-            try: coefs_matrix[n[i], lm_idx, t] = np.complex128(0)
+            try: coefs_matrix[lm_idx, n[i], t] = np.complex128(0)
             except IndexError: continue
         copy_coeffcients.setMatrix(mat=coefs_matrix[:,:, t], time=t_snaps[t])