FIX: loading of corrupt files at TES

.flake8

@@ -8,5 +8,5 @@ exclude =
     pyxrf/_version.py,
     docs/conf.py
 # There are some errors produced by 'black', therefore unavoidable
-ignore = E203, W503
+ignore = E203, W503, E701, E704
 max-line-length = 115

pyxrf/core/tests/test_quant_analysis.py

@@ -41,7 +41,7 @@
         "name": "Test Micromatter 411640",
         "serial": "411640",
         "description": "CeF3 21.1 / Au 20.6",
-        "compounds": {"CeF3": 21.1, "Au": 20.6}
+        "compounds": {"CeF3": 21.1, "Au": 20.6},
         # Missing optional 'density' field
     },
 ]

pyxrf/gui_module/wnd_detailed_fitting_params.py

@@ -393,8 +393,7 @@ def _validate_all(self):
         self.pb_cancel.setEnabled(self._data_changed and not self._auto_update)
         self.cb_auto_update.setChecked(Qt.Checked if self._auto_update else Qt.Unchecked)
 
-    def _load_dialog_data(self):
-        ...
+    def _load_dialog_data(self): ...
 
     def _save_dialog_data_function(self):
         raise NotImplementedError()

pyxrf/model/catalog_management.py

@@ -16,10 +16,11 @@ def set_name(self, name):
 def get_catalog(catalog_name):
     from packaging import version
     import databroker
+
     db_version_major = version.parse(databroker.__version__).major == 1
     if db_version_major == 1:
         raise ValueError("Non-tiled version of Databroker is installed")
-    
+
     from tiled.client import from_uri
 
     c = from_uri("https://tiled.nsls2.bnl.gov")

pyxrf/model/load_data_from_db.py

@@ -2804,7 +2804,10 @@ def _get_row_len(row_data):
     filler = Filler(db.reg.handler_reg, inplace=True)
     docs_primary = hdr.documents("primary", fill=False)
 
-    m, n_pt_max, missing_rows = 0, -1, []  # m - index
+    # Assume that the number of positions reflect the size of the row
+    n_pt_max = pos_data.shape[2]
+
+    m, missing_rows = 0, []  # m - index
     try:
         while True:
             try:
@@ -2823,10 +2826,6 @@ def _get_row_len(row_data):
             if is_filled:
                 data = doc["data"][detector_field]
                 data_det1 = np.array(data[:, 0, :], dtype=np.float32)
-
-                # The following is the fix for the case when data has corrupt row (smaller number of data points).
-                # It will not work if the first row is corrupt.
-                n_pt_max = max(data_det1.shape[0], n_pt_max)
                 data_det1_adjusted = np.zeros([n_pt_max, data_det1.shape[1]])
                 data_det1_adjusted[: data_det1.shape[0], :] = data_det1