added code for p22760 experiment

src/cristallina/p22760/__init__.py

@@ -0,0 +1,69 @@
+import os
+import json
+from pathlib import Path
+from collections import defaultdict, deque
+from copy import copy
+import time
+
+import scipy
+import numpy as np
+import pandas as pd
+from tqdm.notebook import tqdm
+import re
+
+from pathlib import Path
+
+import warnings
+
+from matplotlib import pyplot as plt
+import matplotlib as mpl
+
+import cristallina.utils as cu
+import cristallina as cr
+
+from loguru import logger
+
+from cristallina.uscan import UnfinishedScan
+
+from joblib import Parallel, delayed, Memory
+import sfdata
+from sfdata import SFProcFile, SFDataFile, SFDataFiles, SFScanInfo
+
+memory = Memory(location="/sf/cristallina/data/p22760/work/joblib", compress=2, verbose=2)
+pgroup = "p22760"
+
+print(f"p22760 module imported.")
+
+
+def get_theta_prediction(B_field):
+    """Get predicted theta angle from B field using linear interpolation.
+
+    Args:
+        B_field (float): Magnetic field value.
+    """
+
+    B = np.array([0.    , 0.    , 0.05  , 0.1   , 0.15  , 0.2   , 0.25  , 0.3   ,
+        0.35  , 0.4   , 0.5   , 0.525 , 0.53  , 0.55  , 0.555 , 0.56  ,
+        0.565 , 0.5675, 0.57  , 0.5725, 0.575 , 0.6   ])
+
+    left = np.array([-16.72402197, -16.72592595, -16.72266943, -16.71780642,
+        -16.70710748, -16.68879129, -16.67129814, -16.64430405,
+        -16.61258093, -16.57162955, -16.43958512, -16.36767873,
+        -16.35235521, -16.20000072, -16.14585335, -16.14986136,
+        -16.14953497, -16.15033841, -16.14907281, -16.14883662,
+        -16.14936827, -16.14544489])
+
+    right = np.array([-15.82641889, -15.82810495, -15.82810142, -15.83362565,
+        -15.84191596, -15.85030174, -15.86875095, -15.88716295,
+        -15.91257856, -15.94358668, -16.0436225 , -16.07455302,
+        -16.08374928, -16.13199655, -16.14585335, -16.14986136,
+        -16.14953497, -16.15033841, -16.14907281, -16.14883662,
+        -16.14936827, -16.14544489])
+
+    interpolation_right = scipy.interpolate.interp1d(B, right, kind='linear')
+    interpolation_left = scipy.interpolate.interp1d(B, left, kind='linear')
+
+    theta_right = interpolation_right(B_field)
+    theta_left = interpolation_left(B_field)
+
+    return theta_left, theta_right