Updating for version 0.6.3

Fix #47

pyzebra/__init__.py

@@ -5,4 +5,4 @@ from pyzebra.h5 import *
 from pyzebra.utils import *
 from pyzebra.xtal import *
 
-__version__ = "0.6.0"
+__version__ = "0.6.3"

pyzebra/app/panel_param_study.py

@@ -122,11 +122,7 @@ def create():
             file_list.append(os.path.basename(scan["original_filename"]))
 
         scan_table_source.data.update(
-            file=file_list,
-            scan=scan_list,
-            param=param,
-            fit=[0] * len(scan_list),
-            export=export,
+            file=file_list, scan=scan_list, param=param, fit=[0] * len(scan_list), export=export,
         )
         scan_table_source.selected.indices = []
         scan_table_source.selected.indices = [0]
@@ -346,7 +342,7 @@ def create():
             mapper["transform"].high = np.max([np.max(y) for y in ys])
         ov_param_plot_scatter_source.data.update(x=x, y=y, param=par)
 
-        if y:
+        try:
             interp_f = interpolate.interp2d(x, y, par)
             x1, x2 = min(x), max(x)
             y1, y2 = min(y), max(y)
@@ -358,7 +354,7 @@ def create():
             ov_param_plot_image_source.data.update(
                 image=[image], x=[x1], y=[y1], dw=[x2 - x1], dh=[y2 - y1]
             )
-        else:
+        except Exception:
             ov_param_plot_image_source.data.update(image=[], x=[], y=[], dw=[], dh=[])
 
     def _update_param_plot():
@@ -781,7 +777,7 @@ def create():
             export_data = []
             param_data = []
             for scan, param in zip(det_data, scan_table_source.data["param"]):
-                if scan["export"]:
+                if scan["export"] and param:
                     export_data.append(scan)
                     param_data.append(param)
 

pyzebra/ccl_io.py

@@ -170,7 +170,7 @@ def parse_1D(fileobj, data_type):
             while len(counts) < s["n_points"]:
                 counts.extend(map(float, next(fileobj).split()))
             s["counts"] = np.array(counts)
-            s["counts_err"] = np.sqrt(s["counts"])
+            s["counts_err"] = np.sqrt(np.maximum(s["counts"], 1))
 
             if s["h"].is_integer() and s["k"].is_integer() and s["l"].is_integer():
                 s["h"], s["k"], s["l"] = map(int, (s["h"], s["k"], s["l"]))
@@ -208,7 +208,7 @@ def parse_1D(fileobj, data_type):
         for name in col_names:
             s[name] = np.array(s[name])
 
-        s["counts_err"] = np.sqrt(s["counts"])
+        s["counts_err"] = np.sqrt(np.maximum(s["counts"], 1))
 
         s["scan_motors"] = []
         for motor, step in zip(motors, steps):

pyzebra/ccl_process.py

@@ -131,7 +131,7 @@ def merge_scans(scan_into, scan_from):
 
     scan_into[scan_motor] = pos_tmp
     scan_into["counts"] = val_tmp / num_tmp
-    scan_into["counts_err"] = np.sqrt(err_tmp)
+    scan_into["counts_err"] = np.sqrt(err_tmp) / num_tmp
 
     scan_from["export"] = False
 
@@ -220,8 +220,7 @@ def fit_scan(scan, model_dict, fit_from=None, fit_to=None):
         else:
             model += _model
 
-    weights = [1 / y_err if y_err != 0 else 1 for y_err in y_err]
-    scan["fit"] = model.fit(y_fit, x=x_fit, weights=weights)
+    scan["fit"] = model.fit(y_fit, x=x_fit, weights=1 / y_err)
 
 
 def get_area(scan, area_method, lorentz):