example of plotting radial BB separation for ions

examples/run3_ions/006_radial_bb_sep.py

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+# Example of plotting radial BB separation
+import matplotlib.pyplot as plt
+import xtrack as xt
+import numpy as np
+import pandas as pd
+
+
+collider = xt.Multiline.from_json('./collider_04_tuned_and_leveled_bb_on.json')
+collider.build_trackers()
+
+df_bb = {}
+
+for beam in [1, 2]:
+    bb_names = []
+    bb_idx = []
+
+    for counter, i in enumerate(collider[f"lhcb{beam}"].element_names):
+        if "bb_" in i:
+            bb_names.append(i)
+            bb_idx.append(counter)
+
+    radial_bb_sep = []
+
+    for idx in bb_idx:
+        element = collider[f"lhcb{beam}"].elements[idx]
+        sep_x = element.other_beam_shift_x
+        sep_y = element.other_beam_shift_y
+
+        try:
+            sigma_x = np.sqrt(element.other_beam_Sigma_11)
+            sigma_y = np.sqrt(element.other_beam_Sigma_33)
+        except:
+            sigma_x = np.sqrt(element.slices_other_beam_Sigma_11[0])
+            sigma_y = np.sqrt(element.slices_other_beam_Sigma_33[0])
+
+        sep_x /= sigma_x
+        sep_y /= sigma_y
+        radial_bb_sep.append(np.sqrt(sep_x**2 + sep_y**2))
+
+    df_beam = pd.DataFrame({
+        "radial_bb_sep": radial_bb_sep,
+        "name": bb_names
+    })
+
+    twiss = collider[f"lhcb{beam}"].twiss().to_pandas()
+    df_bb[beam] = pd.merge(df_beam, twiss, on='name')
+
+
+fig, axs = plt.subplots(nrows=2, ncols=2, figsize=(10,8), sharey=True)
+ax = axs.flatten()
+
+twiss_b1 = collider[f"lhcb1"].twiss().to_pandas()
+#twiss_b2 = collider[f"lhcb2"].twiss().to_pandas()
+
+for counter, ip in enumerate([1,2,5,8]):
+
+    plt.sca(ax[counter])
+
+    plt.title(f"IP{ip}")
+
+    ip_s = twiss_b1[twiss_b1.name == f"ip{ip}"]["s"].values[0]
+    plt.axvline(ip_s, c='k', linestyle='--')
+
+    df_bb_temp = df_bb[1][df_bb[1]["name"].str.contains(f".l{ip}") | df_bb[1]["name"].str.contains(f".r{ip}")]
+    plt.plot(df_bb_temp.s, df_bb_temp.radial_bb_sep, marker='o', label='B1', c='b')
+
+    #ip_s = twiss_b2[twiss_b2.name == f"ip{ip}"]["s"].values[0]
+    #df_bb_temp = df_bb[2][df_bb[2]["name"].str.contains(f".l{ip}") | df_bb[2]["name"].str.contains(f".r{ip}")]
+    #plt.plot(df_bb_temp.s, df_bb_temp.radial_bb_sep, marker='o', label='B2', c='r')
+
+    plt.xlabel("s (m)")
+    plt.ylabel("Radial BB separation  (sigma)")
+    plt.grid()
+
+plt.legend()
+fig.tight_layout()
+plt.show()