Merge branch 'fix_blackrock_numpy2' of github.com:samuelgarcia/python…

…-neo into final-2.0-fixes

.github/workflows/io-test.yml

@@ -18,7 +18,7 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python-version: ['3.9', '3.12']
+        python-version: ['3.9', '3.12', '3.13']
     defaults:
       # by default run in bash mode (required for conda usage)
       run:

environment_testing.yml

@@ -4,6 +4,3 @@ channels:
 dependencies:
   - datalad
   - pip
-  # temporary have this here for IO testing while we decide how to deal with
-  # external packages not 2.0 ready
-  - numpy=1.26.4

neo/rawio/blackrockrawio.py

@@ -1357,7 +1357,7 @@ def __match_nsx_and_nev_segment_ids(self, nsx_nb):
 
                     # Show warning if spikes do not fit any segment (+- 1 sampling 'tick')
                     # Spike should belong to segment before
-                    mask_outside = (ev_ids == i) & (data["timestamp"] < int(seg["timestamp"]) - nsx_offset - nsx_period)
+                    mask_outside = (ev_ids == i) & (data["timestamp"] < int(seg["timestamp"]) - int(nsx_offset) - int(nsx_period))
 
                     if len(data[mask_outside]) > 0:
                         warnings.warn(f"Spikes outside any segment. Detected on segment #{i}")
@@ -1987,6 +1987,7 @@ def __get_nsx_param_variant_a(self, nsx_nb):
         else:
             units = "uV"
 
+
         nsx_parameters = {
             "nb_data_points": int(
                 (self.__get_file_size(filename) - bytes_in_headers)
@@ -1995,8 +1996,8 @@ def __get_nsx_param_variant_a(self, nsx_nb):
             ),
             "labels": labels,
             "units": np.array([units] * self.__nsx_basic_header[nsx_nb]["channel_count"]),
-            "min_analog_val": -1 * np.array(dig_factor),
-            "max_analog_val": np.array(dig_factor),
+            "min_analog_val": -1 * np.array(dig_factor, dtype="float"),
+            "max_analog_val": np.array(dig_factor, dtype="float"),
             "min_digital_val": np.array([-1000] * self.__nsx_basic_header[nsx_nb]["channel_count"]),
             "max_digital_val": np.array([1000] * self.__nsx_basic_header[nsx_nb]["channel_count"]),
             "timestamp_resolution": 30000,