Fix some deprecation warnings from tests

extra_data/components.py

@@ -827,7 +827,7 @@ def dask_array(self, *, labelled=False, fill_value=None, astype=None):
         from dask.array import concatenate, from_delayed
 
         entry_size = (self.dtype.itemsize *
-            len(self.modno_to_keydata) * np.product(self._eg_keydata.entry_shape)
+            len(self.modno_to_keydata) * np.prod(self._eg_keydata.entry_shape)
         )
         # Aim for 1GB chunks, with an arbitrary maximum of 256 trains
         split = self.split_trains(frames_per_part=min(1024 ** 3 / entry_size, 256))
@@ -1035,7 +1035,7 @@ def dask_array(self, *, labelled=False, subtrain_index='pulseId',
         from dask.array import concatenate, from_delayed
 
         entry_size = (self.dtype.itemsize *
-            len(self.modno_to_keydata) * np.product(self._eg_keydata.entry_shape)
+            len(self.modno_to_keydata) * np.prod(self._eg_keydata.entry_shape)
         )
         if frames_per_chunk is None:
             # Aim for 2GB chunks, with an arbitrary maximum of 1024 frames

extra_data/keydata.py

@@ -481,7 +481,7 @@ def dask_array(self, labelled=False):
             # affect speed dramatically - but this could depend on many factors.
             # TODO: optional user control of chunking
             limit = 2 * 1024 ** 3
-            while np.product(chunk_shape) * itemsize > limit and chunk_dim0 > 1:
+            while np.prod(chunk_shape) * itemsize > limit and chunk_dim0 > 1:
                 chunk_dim0 //= 2
                 chunk_shape = (chunk_dim0,) + chunk.dataset.shape[1:]
 

extra_data/tests/mockdata/base.py

@@ -162,7 +162,7 @@ def write_metadata(h5file, data_sources, chunksize=16, format_version='0.5'):
 
     if format_version != '0.5':
         h5file['METADATA/dataFormatVersion'] = [format_version.encode('ascii')]
-        now = datetime.utcnow().replace(microsecond=0)
+        now = datetime.now(timezone.utc).replace(microsecond=0)
         updated_time = now + timedelta(minutes=5)
         h5file['METADATA/creationDate'] = [
             now.strftime('%Y%m%dT%H%M%SZ').encode('ascii')

extra_data/tests/mockdata/jungfrau.py

@@ -3,14 +3,23 @@
 class JUNGFRAUModule(DeviceBase):
     output_channels = ('daqOutput/data',)
 
-    instrument_keys = [
-        ('adc', 'u2', (16, 512, 1024)),
-        ('frameNumber', 'u8', (16,)),
-        ('gain', 'u1', (16, 512, 1024)),
-        ('mask', 'u2', (16, 512, 1024)),
-        ('memoryCell', 'u1', (16,)),
-        ('timestamp', 'f8', (16,)),
-    ]
+    def __init__(self, device_id, nsamples=None, raw=False):
+        super().__init__(device_id, nsamples)
+        self.raw = raw
+
+    @property
+    def instrument_keys(self):
+        return [
+            ('frameNumber', 'u8', (16,)),
+            ('gain', 'u1', (16, 512, 1024)),
+            ('memoryCell', 'u1', (16,)),
+            ('timestamp', 'f8', (16,)),
+        ] + ([
+            ('adc', 'u2', (16, 512, 1024)),
+        ] if self.raw else [
+            ('adc', 'f4', (16, 512, 1024)),
+            ('mask', 'u4', (16, 512, 1024)),
+        ])
 
 class JUNGFRAUControl(DeviceBase):
     control_keys = [

extra_data/tests/test_reader_mockdata.py

@@ -1042,7 +1042,7 @@ def test_inspect_key_no_trains(mock_jungfrau_run):
     # INSTRUMENT
     jf_m1_data = sel['SPB_IRDA_JF4M/DET/JNGFR01:daqOutput', 'data.adc']
     assert jf_m1_data.shape == (0, 16, 512, 1024)
-    assert jf_m1_data.dtype == np.dtype(np.uint16)
+    assert jf_m1_data.dtype == np.dtype(np.float32)
 
 
 def test_run_metadata(mock_spb_raw_run):