general clean up

geomagio/ImagCDFFactory.py

@@ -31,6 +31,8 @@ from . import TimeseriesUtility
 from . import Util
 
 import cdflib
+from cdflib.cdfwrite import CDF as CDFWriter
+from cdflib.cdfread import CDF as CDFReader
 import tempfile
 
 
@@ -48,7 +50,7 @@ class IMCDFPublicationLevel:
         4: Definitive data with no further changes expected.
 
     Reference:
-    - ImagCDF Documentation Section 4.2: Attributes that Uniquely Identify the Data
+    - ImagCDF Technical Documentation: Attributes that Uniquely Identify the Data
     """
 
     class PublicationLevel:
@@ -137,13 +139,13 @@ class ImagCDFFactory(TimeseriesFactory):
             # Initialize the CDF writer
             cdf_spec = {
                 'Compressed': 9,          # Enable compression (0-9)
-                # 'Majority': 'row_major',        # Data layout - gets set automatically
-                # 'Encoding': 'ibmpc',      # Corrupts CDF - gets set automatically
+                'Majority': CDFWriter.ROW_MAJOR,        # Data layout - gets set automatically
+                'Encoding': CDFWriter.IBMPC_ENCODING, #  gets set automatically
                 'Checksum': True,        # Disable checksum for faster writes (optional)
                 'rDim_sizes': [],         # Applicable only if using rVariables - CDF protocol recommends only using zVariables. 
             }
 
-            cdf_writer = cdflib.cdfwrite.CDF(path=tmp_file_path, cdf_spec=cdf_spec, delete=True)
+            cdf_writer = CDFWriter(path=tmp_file_path, cdf_spec=cdf_spec, delete=True)
 
             # Write global attributes
             global_attrs = self._create_global_attributes(timeseries, channels)
@@ -155,13 +157,13 @@ class ImagCDFFactory(TimeseriesFactory):
                 # Define time variable specification
                 var_spec = {
                     'Variable': ts_name,
-                    'Data_Type': 33,  # CDF_TIME_TT2000
+                    'Data_Type': CDFWriter.CDF_TIME_TT2000,  # CDF_TIME_TT2000
                     'Num_Elements': 1,
                     'Rec_Vary': True,
                     'Var_Type': 'zVariable',
                     'Dim_Sizes': [],
                     'Sparse': 'no_sparse',
-                    'Compress': 6,
+                    'Compress': 9,
                     'Pad': None,
                 }
                 # Define time variable attributes
@@ -182,9 +184,7 @@ class ImagCDFFactory(TimeseriesFactory):
                     var_name = f"GeomagneticField{channel}"
                 data_type = self._get_cdf_data_type(trace)
                 num_elements = 1
-                CDF_CHAR = 51
-                CDF_UCHAR = 52
-                if data_type in [CDF_CHAR, CDF_UCHAR]:  # Handle string types
+                if data_type in [CDFWriter.CDF_CHAR, CDFWriter.CDF_UCHAR]:  # Handle string types
                     num_elements = len(trace.data[0]) if len(trace.data) > 0 else 1
             
                 var_spec = {
@@ -195,7 +195,7 @@ class ImagCDFFactory(TimeseriesFactory):
                     'Var_Type': 'zVariable',
                     'Dim_Sizes': [],
                     'Sparse': 'no_sparse',
-                    'Compress': 6,
+                    'Compress': 9,
                     'Pad': None,
                 }
                 var_attrs = self._create_var_attrs(trace, temperature_index, self.isUniqueTimes)
@@ -294,7 +294,7 @@ class ImagCDFFactory(TimeseriesFactory):
                 if os.path.isfile(url_file):
                     try:
                         # Read existing data to merge with new data
-                        existing_cdf = cdflib.cdfread.CDF(url_file)
+                        existing_cdf = CDFReader(url_file)
                         existing_stream = self._read_cdf(existing_cdf)
                         # existing_cdf.close() #no close method?
                         existing_data = existing_stream
@@ -371,7 +371,7 @@ class ImagCDFFactory(TimeseriesFactory):
 
             try:
                 # Read CDF data and merge
-                cdf = cdflib.cdfread.CDF(url_file)
+                cdf = CDFReader(url_file)
                 file_stream = self._read_cdf(cdf)
                 # Attempt to select only requested channels
                 selected = Stream()
@@ -418,7 +418,7 @@ class ImagCDFFactory(TimeseriesFactory):
         descriptions.
 
         References:
-        - ImagCDF Documentation Section 4: ImagCDF Global Attributes
+        - ImagCDF Technical Documentation: ImagCDF Global Attributes
         """
         stats = timeseries[0].stats if len(timeseries) > 0 else None
 
@@ -458,10 +458,10 @@ class ImagCDFFactory(TimeseriesFactory):
             # 'UniqueIdentifier': {0: ''},
             # 'ParentIdentifiers': {0: ''},
             # 'ReferenceLinks': {0: ''}, #links to /ws, plots, USGS.gov 
-            'SensorSamplingRate': {0: sensor_sampling_rate},            
-            'DataType': {0: data_type},
-            'Comments': {0: comments},
-            'DeclinationBase': {0: declination_base},
+            'SensorSamplingRate': {0: sensor_sampling_rate}, #Optional            
+            'DataType': {0: data_type},#Optional
+            'Comments': {0: comments}, #Optional
+            'DeclinationBase': {0: declination_base}, #Optional
         }
         return global_attrs
 
@@ -470,7 +470,6 @@ class ImagCDFFactory(TimeseriesFactory):
         scalar_times = None
         temperature_times = {}
         temperature_index = 1
-        print(timeseries[0].stats)
 
         for trace in timeseries:
             channel = trace.stats.channel
@@ -615,9 +614,9 @@ class ImagCDFFactory(TimeseriesFactory):
         Create a dictionary of time variable attributes.
 
         These attributes provide metadata for time variables.
-        Note: None of these attributes are required for the time stamp variables GeomagneticVectorTimes and GeomagneticScalarTimes.
+        Note: None of these attributes are required for the time stamp variables.
         Reference:
-        - ImagCDF Documentation Section 3: ImagCDF Data
+        - ImagCDF Technical Documentation: ImagCDF Data
         """
         # var_attrs = {
             # 'UNITS': 'TT2000',
@@ -639,21 +638,18 @@ class ImagCDFFactory(TimeseriesFactory):
         - CDF_INT4 (41) for integer data.
 
         Reference:
-        - CDF Data Types: http://cdf.gsfc.nasa.gov/html/cdfdatatypes.html
+        - See CDF for more data types
         """
-        # CDF data type constants
-        CDF_DOUBLE = 45  # CDF_DOUBLE corresponds to 64-bit float
-        CDF_INT4 = 41    # CDF_INT4 corresponds to 32-bit int
 
         if trace.data.dtype in [np.float32, np.float64]:
-            return CDF_DOUBLE
+            return CDFWriter.CDF_DOUBLE
         elif trace.data.dtype in [np.int32, np.int64]:
-            return CDF_INT4
+            return CDFWriter.CDF_INT4
         else:
             # Default to double precision float
-            return CDF_DOUBLE
+            return CDFWriter.CDF_DOUBLE
 
-    def _read_cdf(self, cdf: cdflib.cdfread.CDF) -> Stream:
+    def _read_cdf(self, cdf: CDFReader) -> Stream:
         """
         Read CDF data into an ObsPy Stream.
 
@@ -677,7 +673,7 @@ class ImagCDFFactory(TimeseriesFactory):
         institution = global_attrs.get('Institution', [''])[0]
         latitude = global_attrs.get('Latitude', [0.0])[0]
         longitude = global_attrs.get('Longitude', [0.0])[0]
-        elevation = global_attrs.get('Elevation', [99_999.0])[0]
+        elevation = global_attrs.get('Elevation', [99_999.0])[0] #default to 99_999 per technical documents.
         sensor_sampling_rate = global_attrs.get('SensorSamplingRate', [0.0])[0]
         sensor_orientation = global_attrs.get('VectorSensOrient', [''])[0]
         data_type = global_attrs.get('DataType', ['variation'])[0]
@@ -816,7 +812,7 @@ class ImagCDFFactory(TimeseriesFactory):
         - The formatted file URL or path.
 
         Reference:
-        - ImagCDF Documentation Section 5: ImagCDF File Names
+        - ImagCDF Technical Documentation: ImagCDF File Names
         """
         # Get the publication level for the type
         publication_level = IMCDFPublicationLevel(data_type=type).to_string()