bugs fixing

Analyser/FitAnalyser.py

@@ -559,7 +559,8 @@ class FitAnalyser():
                 }
             )
 
-            return xr.apply_ufunc(self._eval_1D, fitResultArray, kwargs={"x":x}, **kwargs)
+            res = xr.apply_ufunc(self._eval_1D, fitResultArray, kwargs={"x":x}, **kwargs)
+            return res.assign_coords({prefix+'x':np.array(x)})
 
         if self.fitDim == 2:
             if output_core_dims is None:
@@ -586,7 +587,8 @@ class FitAnalyser():
             _x = _x.flatten()
             _y = _y.flatten()
 
-            return xr.apply_ufunc(self._eval_2D, fitResultArray, kwargs={"x":_x, "y":_y, "shape":(len(x), len(y))}, **kwargs)
+            res = xr.apply_ufunc(self._eval_2D, fitResultArray, kwargs={"x":_x, "y":_y, "shape":(len(x), len(y))}, **kwargs)
+            return res.assign_coords({prefix+'x':np.array(x), prefix+'y':np.array(y)})
 
     def _get_fit_value_single(self, fitResult, key):
         return fitResult.params[key].value

DataContainer/ReadData.py

@@ -113,7 +113,7 @@ def update_hdf5_file():
     pass
  
 
-def read_hdf5_file(filePath, group=None, datesetOfGlobal=None, preprocess=None, join="outer", parallel=True, engine="h5netcdf", phony_dims="access", **kwargs):
+def read_hdf5_file(filePath, group=None, datesetOfGlobal=None, preprocess=None, join="outer", parallel=True, engine="h5netcdf", phony_dims="access", excludeAxis=[], **kwargs):
 
     filePath = np.sort(np.atleast_1d(filePath))
 
@@ -152,6 +152,8 @@ def read_hdf5_file(filePath, group=None, datesetOfGlobal=None, preprocess=None,
             combine_attrs=_read_globals_attrs,
             parallel=True, )
     
+    datesetOfGlobal.attrs['scanAxis'] = np.setdiff1d(datesetOfGlobal.attrs['scanAxis'], excludeAxis)
+    
     _assgin_scan_axis = partial(_assign_scan_axis_partial, datesetOfGlobal=datesetOfGlobal, fullFilePath=fullFilePath)
 
     if preprocess is None:

ToolFunction/HomeMadeXarrayFunction.py

@@ -210,8 +210,36 @@ def errorbar(
 
     _ensure_plottable(xplt_val, yplt_val)
     
+    fmt = None
+    if 'fmt' in kwargs and isinstance(kwargs['fmt'], list):
+        fmt = kwargs["fmt"]
+    
+    if len(np.shape(xplt_val)) == len(np.shape(yplt_val)):
+        
         primitive = ax.errorbar(xplt_val, yplt_val, *args, xerr=xerr, yerr=yerr, **kwargs)
     
+    else:
+        primitive = np.empty(np.shape(yplt_val)[1], dtype=object)
+        
+        if not yerr is None:
+            if not fmt is None:
+                for i in range(np.shape(yplt_val)[1]):
+                    kwargs.update({'fmt': fmt[i]})
+                    primitive[i] = ax.errorbar(xplt_val, yplt_val[:, i], *args, xerr=xerr, yerr=yerr[:, i], **kwargs)
+            else:
+                for i in range(np.shape(yplt_val)[1]):
+                    primitive[i] = ax.errorbar(xplt_val, yplt_val[:, i], *args, xerr=xerr, yerr=yerr[:, i], **kwargs)
+        else:
+            if not fmt is None:        
+                for i in range(np.shape(yplt_val)[1]):
+                    kwargs.update({'fmt': fmt[i]})
+                    primitive[i] = ax.errorbar(xplt_val, yplt_val[:, i], *args, xerr=xerr, yerr=yerr, **kwargs)
+            else:
+                for i in range(np.shape(yplt_val)[1]):
+                    primitive[i] = ax.errorbar(xplt_val, yplt_val[:, i], *args, xerr=xerr, yerr=yerr, **kwargs)
+
+        primitive = tuple(primitive)
+
     if _labels:
         if xlabel is not None:
             ax.set_xlabel(xlabel)

ToolFunction/ToolFunction.py

@@ -104,7 +104,7 @@ def print_scanAxis(dataSet):
                 key: scanValue[indices]
             }
         )
-    print("The detected scaning axes and values are: /n")
+    print("The detected scaning axes and values are: \n")
     print(scan)