1 files changed, 37 insertions(+), 9 deletions(-)

M clusterfunc.py

@@ 63,8 63,6 @@ def normalised_N_fixed(Dst, Dmax, ERmax, N, check=True):
     # Number of points for uniform spacing at Dst
     Nunif = np.ceil(1./Dst)
 
-    print(N1a, N1b, N, L1a)
-
     if N > Nunif:
         raise ClusteringException(
         f'Too many points N={N} for a uniform spacing of Dst={Dst}.'


@@ 156,6 154,34 @@ def normalised_N_fixed(Dst, Dmax, ERmax, N, check=True):
 
     return x
 
+def normalised_N_free(Dst, Dmax, ERmax, mult=8, check=True):
+
+    # Find high and low guesses for n, N = mult*n + 1
+    nlow = np.round(1./Dmax/mult).astype(int)
+    nhigh = np.round(1./Dst/mult).astype(int)
+
+    # Loop until converged
+    while nhigh-nlow > 1:
+
+        # Bisect high and low guesses
+        nnew = (nhigh+nlow)//2
+        Nnew = nnew * mult + 1
+
+        # Attempt to cluster
+        try:
+            x = normalised_N_fixed(Dst, Dmax, ERmax, Nnew, check=False)
+            # new n is valid, use as high limiit
+            nhigh = nnew
+        except ClusteringException:
+            # new n is not valid, use as low limiit
+            nlow = nnew
+
+    if check:
+        check_normalised(x, Dst, Dmax, ERmax)
+
+    return x
+
+
 
 def cumsum0(x, axis=None):
     return np.insert(np.cumsum(x, axis=axis), 0, 0.0, axis=axis)


@@ 169,19 195,21 @@ import matplotlib.pyplot as plt
 Dst = 0.001
 Dmax = 0.08
 ER = 1.1
-N = 56
+N = 57
 
-xx = normalised_N_fixed(Dst, Dmax, ER, N)
+x1 = normalised_N_fixed(Dst, Dmax, ER, N)
+x2 = normalised_N_free(Dst, Dmax, ER)
 
 fig, ax = plt.subplots()
-ax.plot(xx,'k-x')
+ax.plot(x1,'-x')
+ax.plot(x2,'-x')
 ax.set_title('x')
 plt.show()
 
-fig, ax = plt.subplots()
-ax.set_title('dx')
-ax.plot(np.diff(xx),'k-x')
-plt.show()
+# fig, ax = plt.subplots()
+# ax.set_title('dx')
+# ax.plot(np.diff(xx),'k-x')
+# plt.show()
 
 # fig, ax = plt.subplots()
 # ax.plot(dx,'k-x')