Working build (no normalization)

Author: John Halloran

src/diffpy/snmf/main.py

@@ -1,10 +1,10 @@
 import numpy as np
 import snmf_class
 
-X0 = np.loadtxt("inputs/my_X0_4.txt", dtype=float)
-MM = np.loadtxt("inputs/my_MM_4.txt", dtype=float)
-A0 = np.loadtxt("inputs/my_A0_4.txt", dtype=float)
-Y0 = np.loadtxt("inputs/my_W0_4.txt", dtype=float)
+X0 = np.loadtxt("input/X0.txt", dtype=float)
+MM = np.loadtxt("input/MM.txt", dtype=float)
+A0 = np.loadtxt("input/A0.txt", dtype=float)
+Y0 = np.loadtxt("input/W0.txt", dtype=float)
 N, M = MM.shape
 
 # Convert to DataFrames for display
@@ -21,9 +21,10 @@
 print("Initial Guess (Y0):\n", df_Y0, "\n")
 """
 
-my_model = snmf_class.SNMFOptimizer(MM=MM, Y0=Y0, X0=X0, A=A0)
-print(f"My final guess for X: {my_model.X}")
-print(f"My final guess for Y: {my_model.Y}")
+my_model = snmf_class.SNMFOptimizer(MM=MM, Y0=Y0, X0=X0, A=A0, components=2)
+print("Done")
+# print(f"My final guess for X: {my_model.X}")
+# print(f"My final guess for Y: {my_model.Y}")
 # print(f"Compare to true X: {X_norm}")
 # print(f"Compare to true Y: {Y_norm}")
 np.savetxt("my_new_X.txt", my_model.X, fmt="%.6g", delimiter=" ")