script dump

2026-02-17 08:52:57 +01:00
parent a666b31f25
commit 15ea8f8cd5
11 changed files with 2013 additions and 0 deletions
--- a/combine_resultants.py
+++ b/combine_resultants.py
@@ -0,0 +1,126 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+
+def combine_structure_factors(F_A, phi_A,
+                              F_B, phi_B,
+                              a, b,
+                              plot=True):
+    """
+    Combine two resultant structure factors:
+        F_comb = a*F1 + b*F2
+
+    Returns:
+        magnitude, phase_deg, complex_value
+    """
+
+    # Convert to complex SFs
+    SF_A = F_A * np.exp(1j * np.deg2rad(phi_A))
+    SF_B = F_B * np.exp(1j * np.deg2rad(phi_B))
+
+    # Linear combination
+    SF_AB_comb = a * SF_A + b * SF_B
+    F_AB_comb = np.abs(SF_AB_comb)
+    SF_AB_phi_A = F_AB_comb * np.exp(1j * np.deg2rad(phi_A))
+    
+    SF_B_extr = ( SF_AB_comb - a * SF_A ) / b
+    
+    
+    F_AB = a * F_A + b * F_B    
+    SF_AB_x8 = F_AB * np.exp(1j * np.deg2rad(phi_A))
+
+    # x8 combination
+    SF_extr_comb = (SF_AB_comb - SF_A)/b + SF_A
+    
+    F_extr = (F_AB_comb - F_A)/b + F_A
+    SF_extr_x8 = F_extr * np.exp(1j * np.deg2rad(phi_A))
+
+    # Optional Argand plot
+    origin = 0 + 0j
+    if plot:
+        plt.figure(figsize=(6, 6))
+        plt.arrow(origin.real, origin.imag, SF_A.real, SF_A.imag,
+                  color="blue", alpha=0.6,
+                  head_width=0.2, head_length=0.2,
+                  length_includes_head=True, label="SFA")
+        plt.arrow(origin.real, origin.imag, SF_B.real, SF_B.imag,
+                  color="orange", alpha=0.6,
+                  head_width=0.4, head_length=0.4,
+                  length_includes_head=True, label="SFB")
+        plt.arrow(origin.real, origin.imag, SF_AB_comb.real, SF_AB_comb.imag,
+                  color="green", linewidth=3,
+                  head_width=0.2, head_length=0.2,
+                  length_includes_head=True, label="SF_extr")
+        plt.arrow(origin.real, origin.imag, SF_B_extr.real, SF_B_extr.imag,
+                  color="yellow", linewidth=3,
+                  head_width=0.2, head_length=0.2,
+                  length_includes_head=True, label="SF_B_extr")
+        plt.arrow(origin.real, origin.imag, F_extr.real, F_extr.imag,
+                  color="pink", linewidth=3,
+                  head_width=0.2, head_length=0.2,
+                  length_includes_head=True, label="F_extr")
+        plt.axhline(0)
+        plt.axvline(0)
+        plt.axis("equal")
+        plt.xlabel("Re(F)")
+        plt.ylabel("Im(F)")
+        plt.title(f"F_comb = aF1 + bF2  (a={a}, b={b})")
+        plt.legend()
+        plt.grid(True)
+        plt.show()
+        
+    return SF_AB_comb, SF_AB_x8, SF_B_extr, SF_extr_x8
+
+
+# -----------------------------
+# Example usage
+# -----------------------------
+F_A = 100
+#phi_A = 90
+
+F_B = 50
+phi_B = 0
+
+phi_lst = np.arange(0,360,10)
+b_lst = [ 0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1 ]
+df = pd.DataFrame()
+
+for phi_A in phi_lst:
+    
+    for b in b_lst:
+        
+        a = 1 - b
+        SF_AB_comb, SF_AB_x8, SF_extr_comb, SF_extr_x8 = combine_structure_factors(
+            F_A, phi_A,
+            F_B, phi_B,
+            a, b,
+            plot=True
+        )
+        
+        data = [ {  "F_A" : F_A,
+                    "phi" : phi_A,
+                    "F_B" : F_B,
+                    "phi_B" : phi_B,
+                    "b" : b,
+                    "SF_AB_comb_abs": np.abs(SF_AB_comb),
+                    "SF_AB_comb_phi": np.angle(SF_AB_comb, deg=True),
+                    "SF_AB_x8_abs": np.abs(SF_AB_x8),
+                    "SF_AB_x8_phi": np.angle(SF_AB_x8, deg=True),
+                    "SF_B_extr_abs": np.abs(SF_extr_comb),
+                    "SF_B_extr_comb_phi": np.angle(SF_extr_comb, deg=True),
+                    "SF_extr_x8_abs": np.abs(SF_extr_x8),
+                    "SF_extr_x8_phi": np.angle(SF_extr_x8, deg=True),
+                } ]
+        df_1 = pd.DataFrame( data )
+        df = pd.concat( ( df, df_1 ) )
+        
+        df = df.reset_index( drop=True )
+    
+print( df )
+
+df.to_csv( "../results/complete_varied_b_and_phi.csv", sep="," )
+df_mean = pd.DataFrame()
+df_mean[ "b" ] = df.b   
+df_mean[ "SF_extr_x8_abs" ] = ( df.groupby('b')["SF_extr_x8_abs"].transform('mean') / F_B  ) *100
+
+print(df_mean.drop_duplicates())