diff --git a/test/algorithm_test/AverageAlgorithm_test.py b/test/algorithm_test/AverageAlgorithm_test.py
index 1600c48da288ff7d2fb860d7745578fb797522c4..7784b41533b663c62a52cee364cd797f75a3ba8f 100644
--- a/test/algorithm_test/AverageAlgorithm_test.py
+++ b/test/algorithm_test/AverageAlgorithm_test.py
@@ -1,4 +1,4 @@
-from geomagio.algorithm import AverageAlgorithm as avg
+from geomagio.algorithm import AverageAlgorithm
from obspy.core.stream import Stream
from ..StreamConverter_test import __create_trace
from obspy.core import UTCDateTime
@@ -14,25 +14,36 @@ def test_process():
different stations.
"""
+ # Make three test data arrays of 1's, 3's, and 5's
+ # the average of the three arrays should be 3
+ test_data1 = np.ones(5)
+ test_data2 = np.ones(5) * 5
+ test_data3 = np.ones(5) * 3
- dat1 = np.array(np.ones(5))
- dat2 = np.ones(5) * 5
- dat3 = np.ones(5) * 3
- final_data = np.ones(5) * 3
+ # Create expected solution array of 3's
+ expected_solution = np.ones(5) * 3
+
+ # Create timeseries with first trace that uses test_data1
timeseries = Stream()
- timeseries += __create_trace('H', dat1)
+ timeseries += __create_trace('H', test_data1)
+ # Set metadata so process can read the array:
+ # station, sample number, data type, and data interval
timeseries[0].stats.station = 'HON'
timeseries[0].stats.samples = 5
timeseries[0].stats.data_type = 'variation'
timeseries[0].stats.data_interval = 'minute'
- timeseries += __create_trace('H', dat2)
+ # Add the next trace with test_data2 and set station name
+ timeseries += __create_trace('H', test_data2)
timeseries[1].stats.station = 'GUA'
- timeseries += __create_trace('H', dat3)
+ # Add final trace with test_data3 and set station name
+ timeseries += __create_trace('H', test_data3)
timeseries[2].stats.station = 'SJG'
- a = avg(('HON', 'GUA', 'SJG'), 'H')
+
+ # initialize the algorithm factory with Observatories and Channel
+ a = AverageAlgorithm(('HON', 'GUA', 'SJG'), 'H')
outstream = a.process(timeseries)
# Ensure the average of two
- np.testing.assert_array_equal(outstream[0].data, final_data)
+ np.testing.assert_array_equal(outstream[0].data, expected_solution)
def test_gaps():
@@ -42,30 +53,35 @@ def test_gaps():
"""
- trace1 = __create_trace('H', [1, 1, np.nan, np.nan, 1, 1])
- # set time of first sample
- trace1.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
- # set sample rate to 1 minute
- trace1.stats.delta = 60
- # set station code
- trace1.stats.station = 'HON'
- trace1.stats.data_type = 'variation'
- trace1.stats.data_interval = 'minute'
-
- trace2 = __create_trace('H', [1, 1, 1, 1, 1, 1])
- # set time of first sample
- trace2.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
- # set sample rate to 1 minute
- trace2.stats.delta = 60
- # set station code
- trace2.stats.station = 'SJG'
+ # Create a trace with data gaps
+ gap_trace = __create_trace('H', [1, 1, np.nan, np.nan, 1, 1])
+
+ # set time of first sample, sample rate (1 minute),
+ # station, data type, and data interval
+ gap_trace.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
+ gap_trace.stats.delta = 60
+ gap_trace.stats.station = 'HON'
+ gap_trace.stats.data_type = 'variation'
+ gap_trace.stats.data_interval = 'minute'
+
+ # Create a trace with no gaps
+ full_trace = __create_trace('H', [1, 1, 1, 1, 1, 1])
+ # set time of first sample, sample rate, station
+ full_trace.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
+ full_trace.stats.delta = 60
+ full_trace.stats.station = 'SJG'
+
+ # Create timeseries that contains the gap_trace and full_trace
timeseries = Stream()
- timeseries += trace1
- timeseries += trace2
- alg = avg(('HON', 'SJG'), 'H')
+ timeseries += gap_trace
+ timeseries += full_trace
+ # Initialize the AverageAlgorithm factory with observatories and channel
+ alg = AverageAlgorithm(('HON', 'SJG'), 'H')
+ # Run timeseries through the average process
outstream = alg.process(timeseries)
+ # The gaps should not be changed and should remain 'nan'
assert_array_equal(outstream[0].data, [1, 1, np.nan, np.nan, 1, 1])
@@ -76,30 +92,33 @@ def test_metadata():
"""
- trace1 = __create_trace('H', [3, 3, 3, 3, 3, 3])
- # set time of first sample
- trace1.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
- # set sample rate to 1 minute
- trace1.stats.delta = 60
- # set station code
- trace1.stats.station = 'HON'
- trace1.stats.data_type = 'variation'
- trace1.stats.data_interval = 'minute'
-
- trace2 = __create_trace('H', [1, 1, 1, 1, 1, 1])
- # set time of first sample
- trace2.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
- # set sample rate to 1 minute
- trace2.stats.delta = 60
- # set station code
- trace2.stats.station = 'SJG'
+ # Create a trace with channel 'H' and any numbers
+ test_trace = __create_trace('H', [3, 3, 3, 3, 3, 3])
+ test_trace2 = __create_trace('H', [1, 1, 1, 1, 1, 1])
+
+ # set start time, sample rate (1 minute), station, data type and interval
+ test_trace.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
+ test_trace.stats.delta = 60
+ test_trace.stats.station = 'HON'
+ test_trace.stats.data_type = 'variation'
+ test_trace.stats.data_interval = 'minute'
+
+ # set start time, sample rate (1 minute), station of second trace
+ test_trace2.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
+ test_trace2.stats.delta = 60
+ test_trace2.stats.station = 'SJG'
+ # Populate timeseries with the 2 traces
timeseries = Stream()
- timeseries += trace1
- timeseries += trace2
+ timeseries += test_trace
+ timeseries += test_trace2
- alg = avg(('HON', 'SJG'), 'Hdt')
+ # Initialize the average algorithm with observatories and
+ # set a new outchannel name
+ alg = AverageAlgorithm(('HON', 'SJG'), 'Hdt')
outstream = alg.process(timeseries)
+ # The station name should be changed to 'USGS'
assert_equals(outstream[0].stats.station, 'USGS')
+ # The channel should be changed to 'Hdt'
assert_equals(outstream[0].stats.channel, 'Hdt')