Merge based on variable parameter range overlap

pyzebra/app/panel_ccl_integrate.py

@@ -172,7 +172,7 @@ def create():
         peak_pos_textinput_lock = True
 
         y = scan["Counts"]
-        x = scan["om"]
+        x = scan["omega"]
 
         plot_scatter_source.data.update(x=x, y=y, y_upper=y + np.sqrt(y), y_lower=y - np.sqrt(y))
 
@@ -180,11 +180,11 @@ def create():
         if num_of_peaks is not None and num_of_peaks > 0:
             peak_indexes = scan["peak_indexes"]
             if len(peak_indexes) == 1:
-                peak_pos_textinput.value = str(scan["om"][peak_indexes[0]])
+                peak_pos_textinput.value = str(scan["omega"][peak_indexes[0]])
             else:
-                peak_pos_textinput.value = str([scan["om"][ind] for ind in peak_indexes])
+                peak_pos_textinput.value = str([scan["omega"][ind] for ind in peak_indexes])
 
-            plot_peak_source.data.update(x=scan["om"][peak_indexes], y=scan["peak_heights"])
+            plot_peak_source.data.update(x=scan["omega"][peak_indexes], y=scan["peak_heights"])
             plot_line_smooth_source.data.update(x=x, y=scan["smooth_peaks"])
         else:
             peak_pos_textinput.value = None
@@ -314,7 +314,7 @@ def create():
         if new is not None and not peak_pos_textinput_lock:
             scan = _get_selected_scan()
 
-            peak_ind = (np.abs(scan["om"] - float(new))).argmin()
+            peak_ind = (np.abs(scan["omega"] - float(new))).argmin()
             scan["peak_indexes"] = np.array([peak_ind], dtype=np.int64)
             scan["peak_heights"] = np.array([scan["smooth_peaks"][peak_ind]])
             _update_table()

pyzebra/app/panel_param_study.py

@@ -194,7 +194,7 @@ def create():
         peak_pos_textinput_lock = True
 
         y = scan["Counts"]
-        x = scan["om"]
+        x = scan["omega"]
 
         plot_scatter_source.data.update(x=x, y=y, y_upper=y + np.sqrt(y), y_lower=y - np.sqrt(y))
 
@@ -267,10 +267,10 @@ def create():
         par = []
         for s, p in enumerate(scan_table_source.data["param"]):
             if p:
-                xs.append(np.array(det_data[s]["om"]))
+                xs.append(np.array(det_data[s]["omega"]))
-                x.extend(det_data[s]["om"])
+                x.extend(det_data[s]["omega"])
                 ys.append(np.array(det_data[s]["Counts"]))
-                y.extend([float(p)] * len(det_data[s]["om"]))
+                y.extend([float(p)] * len(det_data[s]["omega"]))
                 param.append(float(p))
                 par.extend(det_data[s]["Counts"])
 
@@ -412,7 +412,7 @@ def create():
         if new is not None and not peak_pos_textinput_lock:
             scan = _get_selected_scan()
 
-            peak_ind = (np.abs(scan["om"] - float(new))).argmin()
+            peak_ind = (np.abs(scan["omega"] - float(new))).argmin()
             scan["peak_indexes"] = np.array([peak_ind], dtype=np.int64)
             scan["peak_heights"] = np.array([scan["smooth_peaks"][peak_ind]])
             _update_table()

pyzebra/ccl_findpeaks.py

@@ -11,7 +11,7 @@ def ccl_findpeaks(
     smooth=False,
     window_size=7,
     poly_order=3,
-    variable="om",
+    variable="omega",
 ):
 
     """function iterates through the dictionary created by load_cclv2 and locates peaks for each scan

pyzebra/ccl_io.py

@@ -144,11 +144,18 @@ def parse_1D(fileobj, data_type):
             for param, (param_name, param_type) in zip(next_line.split(), ccl_second_line):
                 s[param_name] = param_type(param)
 
-            s["om"] = np.linspace(
+            if s["variable_name"] != "om":
+                raise Exception("Unsupported variable name in ccl file.")
+
+            # "om" -> "omega"
+            s["variable_name"] = "omega"
+            s["variable"] = np.linspace(
                 s["omega"] - (s["n_points"] / 2) * s["angle_step"],
                 s["omega"] + (s["n_points"] / 2) * s["angle_step"],
                 s["n_points"],
             )
+            # overwrite metadata, because it only refers to the scan center
+            s["omega"] = s["variable"]
 
             # subsequent lines with counts
             counts = []
@@ -182,6 +189,15 @@ def parse_1D(fileobj, data_type):
         for name in col_names:
             s[name] = np.array(s[name])
 
+        # "om" -> "omega"
+        if s["variable_name"] == "om":
+            s["variable_name"] = "omega"
+            s["variable"] = s["om"]
+            s["omega"] = s["om"]
+            del s["om"]
+        else:
+            s["variable"] = s[s["variable_name"]]
+
         s["h"] = s["k"] = s["l"] = float("nan")
 
         for param in ("mf", "temp"):

pyzebra/ccl_process.py

@@ -9,7 +9,7 @@ PARAM_PRECISIONS = {
     "chi": 0.1,
     "nu": 0.1,
     "phi": 0.05,
-    "omega": 5,
+    "omega": 0.05,
     "gamma": 0.05,
     "temp": 1,
     "mf": 0.001,
@@ -36,7 +36,14 @@ def _parameters_match(scan1, scan2):
         return False
 
     for param in ("ub", "temp", "mf", *(vars[0] for vars in CCL_ANGLES[zebra_mode])):
-        if np.max(np.abs(scan1[param] - scan2[param])) > PARAM_PRECISIONS[param]:
+        if param == scan1["variable_name"] == scan2["variable_name"]:
+            # check if ranges of variable parameter overlap
+            range1 = scan1["variable"]
+            range2 = scan2["variable"]
+            if range1[0] > range2[-1] or range2[0] > range1[-1]:
+                return False
+
+        elif np.max(np.abs(scan1[param] - scan2[param])) > PARAM_PRECISIONS[param]:
             return False
 
     return True
@@ -53,12 +60,12 @@ def merge_datasets(dataset1, dataset2):
 
 
 def _merge_scans(scan1, scan2):
-    om = np.concatenate((scan1["om"], scan2["om"]))
+    omega = np.concatenate((scan1["omega"], scan2["omega"]))
     counts = np.concatenate((scan1["Counts"], scan2["Counts"]))
 
-    index = np.argsort(om)
+    index = np.argsort(omega)
 
-    scan1["om"] = om[index]
+    scan1["omega"] = omega[index]
     scan1["Counts"] = counts[index]
 
     print(f'Scan {scan2["idx"]} merged into {scan1["idx"]}')

pyzebra/fit2.py

@@ -67,7 +67,7 @@ def fitccl(
         return
 
     if binning is None or binning == 0 or binning == 1:
-        x = list(scan["om"])
+        x = list(scan["omega"])
         y = list(scan["Counts"])
         y_err = list(np.sqrt(y)) if scan.get("sigma", None) is None else list(scan["sigma"])
         if not scan["peak_indexes"]:
@@ -75,7 +75,7 @@ def fitccl(
         else:
             centre = x[int(scan["peak_indexes"])]
     else:
-        x = list(scan["om"])
+        x = list(scan["omega"])
         if not scan["peak_indexes"]:
             centre = np.mean(x)
         else:

pyzebra/fitvol3.py

@@ -39,13 +39,13 @@ def find_nearest(array, value):
 # peaks = [6.2,  8.1, 9.9, 11.5]
 peaks = [23.5, 24.5]
 # peaks = [24]
-def fitccl(scan, variable="om", peak_type="gauss", binning=None):
+def fitccl(scan, variable="omega", peak_type="gauss", binning=None):
 
     x = list(scan[variable])
     y = list(scan["Counts"])
     peak_centre = np.mean(x)
     if binning is None or binning == 0 or binning == 1:
-        x = list(scan["om"])
+        x = list(scan[variable])
         y = list(scan["Counts"])
         y_err = list(np.sqrt(y)) if scan.get("sigma", None) is None else list(scan["sigma"])
         print(scan["peak_indexes"])
@@ -54,7 +54,7 @@ def fitccl(scan, variable="om", peak_type="gauss", binning=None):
         else:
             centre = x[int(scan["peak_indexes"])]
     else:
-        x = list(scan["om"])
+        x = list(scan[variable])
         if not scan["peak_indexes"]:
             peak_centre = np.mean(x)
         else: