Add consistency tests for SZ.

tests/test_sz.py

+import numpy as np
+
 from utils import wrapper, TestClass
 
 folders = None
@@ -13,13 +15,93 @@ class TestSZ(TestClass):
             analyze_files(file_paths=input_path, compressor="sz")
 
     def test_compress_sz_pw_rel(self):
-        compression = "lossy,sz,pw_rel,0.1"
+        compression = "lossy,sz,pw_rel,0.001"
         wrapper(self, compression=compression)
 
+    def test_consistency_sz_pw_rel(self):
+        import enstools.compression.api
+        from enstools.encoding.api import VariableEncoding
+        import enstools.io
+        tolerance = 0.001
+        compression = f"lossy,sz,pw_rel,{tolerance}"
+        # Check that the compression without specifying compression parameters works
+
+        datasets = ["dataset_%iD.nc" % dimension for dimension in range(1, 4)]
+        for dataset_name in datasets:
+            input_path = self.input_directory_path / dataset_name
+
+            # Check that the output file can be loaded
+            with enstools.io.read(input_path) as ds:
+                for var in ds.data_vars:
+                    data_array = ds[var]
+                    encoding = VariableEncoding(specification=compression)
+                    compressed_da, _ = enstools.compression.api.emulate_compression_on_data_array(
+                        data_array=data_array,
+                        compression_specification=encoding,
+                        in_place=False,
+                    )
+                    diff = compressed_da - data_array
+                    diff /= data_array
+
+                    assert (np.abs(diff.values) < (data_array.values * tolerance)).all()
+
     def test_compress_sz_abs(self):
         compression = "lossy,sz,abs,0.01"
         wrapper(self, compression=compression)
 
+    def test_consistency_sz_abs(self):
+        import enstools.compression.api
+        from enstools.encoding.api import VariableEncoding
+        import enstools.io
+        tolerance = 0.01
+        compression = f"lossy,sz,abs,{tolerance}"
+        # Check that the compression without specifying compression parameters works
+
+        datasets = ["dataset_%iD.nc" % dimension for dimension in range(1, 4)]
+        for dataset_name in datasets:
+            input_path = self.input_directory_path / dataset_name
+
+            # Check that the output file can be loaded
+            with enstools.io.read(input_path) as ds:
+                for var in ds.data_vars:
+                    data_array = ds[var]
+                    encoding = VariableEncoding(specification=compression)
+                    compressed_da, _ = enstools.compression.api.emulate_compression_on_data_array(
+                        data_array=data_array,
+                        compression_specification=encoding,
+                        in_place=False,
+                    )
+                    diff = compressed_da - data_array
+                    assert (np.abs(diff.values) < tolerance).all()
+
     def test_compress_sz_rel(self):
         compression = "lossy,sz,rel,0.001"
         wrapper(self, compression=compression)
+
+
+    def test_consistency_sz_rel(self):
+        import enstools.compression.api
+        from enstools.encoding.api import VariableEncoding
+        import enstools.io
+        tolerance = 0.01
+        compression = f"lossy,sz,rel,{tolerance}"
+        # Check that the compression without specifying compression parameters works
+
+        datasets = ["dataset_%iD.nc" % dimension for dimension in range(1, 4)]
+        for dataset_name in datasets:
+            input_path = self.input_directory_path / dataset_name
+
+            # Check that the output file can be loaded
+            with enstools.io.read(input_path) as ds:
+                for var in ds.data_vars:
+                    data_array = ds[var]
+                    encoding = VariableEncoding(specification=compression)
+                    compressed_da, _ = enstools.compression.api.emulate_compression_on_data_array(
+                        data_array=data_array,
+                        compression_specification=encoding,
+                        in_place=False,
+                    )
+                    abs_tolerance = float(data_array.max() - data_array.min()) * tolerance
+                    diff = compressed_da - data_array
+                    assert (np.abs(diff.values) < abs_tolerance).all()
+