Use explicit numpy dtypes

Author: ianthomas23

intake_xarray/tests/test_image.py

@@ -125,7 +125,7 @@ def test_coerce_shape_array_non_int():
     expected = np.append(array[:2, :], [[0], [0]], axis=1)
     actual = _coerce_shape(array, shape)
     assert (expected == actual).all()
-    assert expected.dtype == "float"
+    assert expected.dtype == np.float64
 
 
 def test_read_image():

intake_xarray/tests/test_remote.py

@@ -1,6 +1,7 @@
 # Tests for intake-server, local HTTP file server, local "S3" object server
 import aiohttp
 import intake
+import numpy as np
 import os
 import pytest
 import requests
@@ -122,7 +123,7 @@ def test_http_read_netcdf(data_server):
     url = f'{data_server}/example_1.nc'
     source = intake.open_netcdf(url)
     ds = source.read()
-    assert ds['rh'].isel(lat=0,lon=0,time=0).values.dtype == 'float32'
+    assert ds['rh'].isel(lat=0,lon=0,time=0).values.dtype == np.float32
     assert ds['rh'].isel(lat=0,lon=0,time=0).values == 0.5
 
 
@@ -245,7 +246,7 @@ def test_s3_read_netcdf(s3):
     source = intake.open_netcdf(url,
                                 storage_options=s3options)
     ds = source.read()
-    assert ds['rh'].isel(lat=0,lon=0,time=0).values.dtype == 'float32'
+    assert ds['rh'].isel(lat=0,lon=0,time=0).values.dtype == np.float32
     assert ds['rh'].isel(lat=0,lon=0,time=0).values == 0.5