Merge pull request #178 from kujaku11/patches

Patches

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.3.2
+current_version = 0.3.3
 files = setup.py mt_metadata/__init__.py README.md tests/tf/io/edi/test_no_error_edi.py
 commit = True
 tag = True

README.md

@@ -1,4 +1,4 @@
-# mt_metadata version 0.3.2
+# mt_metadata version 0.3.3
  Standard MT metadata
 
 [![PyPi version](https://img.shields.io/pypi/v/mt_metadata.svg)](https://pypi.python.org/pypi/mt-metadata)
@@ -28,7 +28,7 @@ MT Metadata is a project led by [IRIS-PASSCAL MT Software working group](https:/
 
 Most people will be using the transfer functions, but a lot of that metadata comes from the time series metadata.  This module supports both and has tried to make them more or less seamless to reduce complication.
 
-* **Version**: 0.3.2
+* **Version**: 0.3.3
 * **Free software**: MIT license
 * **Documentation**: https://mt-metadata.readthedocs.io.
 * **Examples**: Click the `Binder` badge above and Jupyter Notebook examples are in **mt_metadata/examples/notebooks** and **docs/source/notebooks**

mt_metadata/__init__.py

@@ -39,7 +39,7 @@
 
 __author__ = """Jared Peacock"""
 __email__ = "[email protected]"
-__version__ = "0.3.2"
+__version__ = "0.3.3"
 
 # =============================================================================
 # Imports

mt_metadata/transfer_functions/processing/aurora/stations.py

@@ -4,6 +4,7 @@
 
 @author: jpeacock
 """
+import pandas as pd
 # =============================================================================
 # Imports
 # =============================================================================
@@ -126,14 +127,14 @@ def to_dataset_dataframe(self):
 
         """
 
-        local_df = self.local.to_dataset_dataframe()
-
+        df = self.local.to_dataset_dataframe()
         for rr in self.remote:
-            local_df = local_df.append(rr.to_dataset_dataframe())
+            remote_df = rr.to_dataset_dataframe()
+            df = pd.concat([df, remote_df]) #, axis=1, ignore_index=True)
 
-        local_df = local_df.reset_index()
+        df.reset_index(inplace=True, drop=True)
 
-        return local_df
+        return df
 
     def get_station(self, station_id):
         """

setup.py

@@ -56,7 +56,7 @@
     test_suite="tests",
     tests_require=test_requirements,
     url="https://github.com/kujaku11/mt_metadata",
-    version="0.3.2",
+    version="0.3.3",
     zip_safe=False,
     package_data={
         "": [

tests/tf/io/edi/test_no_error_edi.py

@@ -43,7 +43,7 @@ def test_header(self):
                 ("longitude", 0.0),
                 ("progdate", "2013-07-03"),
                 ("progname", "mt_metadata"),
-                ("progvers", "0.3.2"),
+                ("progvers", "0.3.3"),
                 ("stdvers", "SEG 1.0"),
                 ("units", "millivolts_per_kilometer_per_nanotesla"),
             ]

tests/tf/processing/aurora/test_processing.py

@@ -0,0 +1,84 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Mar 25 11:46:46 2022
+
+@author: jpeacock
+"""
+
+# =============================================================================
+# Imports
+# =============================================================================
+import pandas as pd
+import unittest
+
+from mt_metadata.transfer_functions.processing.aurora import Processing
+
+# =============================================================================
+
+
+class TestProcessing(unittest.TestCase):
+
+    @classmethod
+    def setUpClass(self):
+        starts = ["2020-01-01T00:00:00", "2020-02-02T00:00:00"]
+        ends = ["2020-01-31T12:00:00", "2020-02-28T12:00:00"]
+
+        data_list = []
+        for ii in range(3):
+            for start, end in zip(starts, ends):
+                entry = {
+                    "station_id": "mt01",
+                    "run_id": f"{ii:03}",
+                    "start": start,
+                    "end": end,
+                    "mth5_path": r"/home/mth5_path.h5",
+                    "sample_rate": 10,
+                    "input_channels": ["hx", "hy"],
+                    "output_channels": ["hz", "ex", "ey"],
+                    "remote": False
+                }
+
+                data_list.append(entry)
+
+                rr_entry_01 = {
+                    "station_id": "rr01",
+                    "run_id": f"{ii:03}",
+                    "start": start,
+                    "end": end,
+                    "mth5_path": r"/home/mth5_path.h5",
+                    "sample_rate": 10,
+                    "input_channels": ["hx", "hy"],
+                    "output_channels": ["hz", "ex", "ey"],
+                    "remote": True
+                }
+                data_list.append(rr_entry_01)
+
+                rr_entry_02 = {
+                    "station_id": "rr02",
+                    "run_id": f"{ii:03}",
+                    "start": start,
+                    "end": end,
+                    "mth5_path": r"/home/mth5_path.h5",
+                    "sample_rate": 10,
+                    "input_channels": ["hx", "hy"],
+                    "output_channels": ["hz", "ex", "ey"],
+                    "remote": True
+                }
+                data_list.append(rr_entry_02)
+        data_list = data_list
+        df = pd.DataFrame(data_list)
+        df.start = pd.to_datetime(df.start)
+        df.end = pd.to_datetime(df.end)
+        self.df = df
+
+
+    def test_stations_to_dataframe(self):
+        """ This could be moved under test_statons.py"""
+        p = Processing()
+        p.stations.from_dataset_dataframe(self.df)
+        df = p.stations.to_dataset_dataframe()
+        assert len(df) == len(self.df)
+
+
+if __name__ == "__main__":
+    unittest.main()