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Brian Jones
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attempt to fix changes. failing locally on dataframe compare because of issues how pandas versions set types
1 parent f2cb1ab commit 20becc2

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Lines changed: 30 additions & 21 deletions

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‎README‎

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@@ -9,7 +9,7 @@ extracts from OTN.
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Abacus Plot
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-----------
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The abacus plot is a way to plot annimal along time. The function uses Plotly to place your points on a scatter plot. ``ycolumn`` is used as the y axis and ``datecollected`` is used as the x axis. ``color_column`` is used to group detections together and assign them a color.
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The abacus plot is a way to plot annimal along time. The function uses Plotly to place your points on a scatter plot. ``ycolumn`` is used as the y axis and ``datecollected`` (or `dateCollectedUTC` ~ for the new extract format) is used as the x axis. ``color_column`` is used to group detections together and assign them a color.
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‎resonate/determine_format.py‎

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@@ -31,12 +31,22 @@ def detect(dataframe: pd.DataFrame) -> dict:
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"col_longitude": "decimalLongitude",
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"col_latitude": "decimalLatitude",
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"col_station": "station",
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"col_catalognumber": "catalogNumber"},
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"col_catalognumber": "catalogNumber",
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"col_unique_id": "unqDetecID"},
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{ "col_datecollected": "datecollected",
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"col_longitude": "longitude",
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"col_latitude": "latitude",
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"col_station": "station",
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"col_catalognumber": "catalognumber"}
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"col_catalognumber": "catalognumber",
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"col_unique_id": "unqdetecid",},
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{"col_datecollected": 'datecollected',
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"col_fieldnumber": 'fieldnumber',
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"col_scientificname": "scientificname",
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"col_station":"station",
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'col_latitude' :'latitude',
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'col_longitude': 'longitude'},
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{"col_catalognumber":"catalognumber",
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"col_station":"station"}
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]
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columns = dataframe.columns

‎resonate/interval_data_tool.py‎

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@@ -3,7 +3,7 @@
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def interval_data(compressed_df: pd.DataFrame, dist_matrix_df: pd.DataFrame, station_radius_df: pd.DataFrame=None, col_catalognumber:str='catalogNumber',
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col_station:str='station'):
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col_station:str='station', **kwargs):
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"""Creates a detection interval file from a compressed detection, distance matrix and station detection radius DataFrames
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Args:

‎resonate/residence_index.py‎

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Original file line numberDiff line numberDiff line change
@@ -178,9 +178,8 @@ def get_days(dets: pd.DataFrame, calculation_method='kessel'):
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return days
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def get_station_location(station: str, detections: pd.DataFrame, col_catalognumber:str='catalogNumber',
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col_station:str='station', col_latitude:str='decimalLatitude', col_longitude:str='decimalLongitude',
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col_datecollected:str='dateCollectedUTC', col_unique_id:str='unqDetecID'):
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def get_station_location(station: str, detections: pd.DataFrame,
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col_station:str='station', col_latitude:str='decimalLatitude', col_longitude:str='decimalLongitude'):
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"""Returns the longitude and latitude of a station/receiver given the station
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and the table name.
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@@ -366,7 +365,7 @@ def residency_index(detections: pd.DataFrame, calculation_method='kessel', col_c
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for station in dets[col_station].unique():
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st_dets = pd.DataFrame(dets[dets[col_station] == station])
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total = get_days(st_dets.copy(), calculation_method)
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location = get_station_location(station, detections)
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location = get_station_location(station, detections, col_longitude=col_longitude, col_station=col_station, col_latitude=col_latitude)
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# Determine the RI and add the station to the list
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station_dict = {
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'days_detected': total,

‎tests/rei_test.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,7 +5,7 @@
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import pandas.testing as pt
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from colorama import Fore as c
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from resonate.receiver_efficiency import REI
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from resonate.determine_format import detect
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class REITest(unittest.TestCase):
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@@ -15,7 +15,7 @@ def test_rei(self):
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detections = pd.read_csv('tests/assertion_files/hfx_detections.csv')
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deployments = pd.read_csv('tests/assertion_files/hfx_deployments.csv')
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dfa = REI(detections, deployments)
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dfa = REI(detections, deployments, **detect(detections))
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dfb = pd.read_csv('tests/assertion_files/hfx_rei.csv')
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pt.assert_frame_equal(dfa, dfb)
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print(c.GREEN + 'OK!\n' + c.RESET)

‎tests/residence_index_test.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,14 +5,14 @@
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import pandas.testing as pt
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import resonate.residence_index as ri
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from colorama import Fore as c
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from resonate.determine_format import detect
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class ResidenceIndexTest(unittest.TestCase):
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def test_kessel(self):
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print(c.YELLOW + 'Testing Kessel RI...' + c.RESET)
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dfa = ri.residency_index(pd.read_csv(
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'tests/assertion_files/nsbs.csv'), calculation_method='kessel')
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input_file = pd.read_csv('tests/assertion_files/nsbs.csv')
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dfa = ri.residency_index(input_file, calculation_method='kessel', **detect(input_file))
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dfb = pd.read_csv('tests/assertion_files/nsbs_kessel_ri.csv')
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dfa.sort_values(['station', 'days_detected'], inplace=True)
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dfb.sort_values(['station', 'days_detected'], inplace=True)
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def test_timedelta(self):
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print(c.YELLOW + 'Testing Timedelta RI...' + c.RESET)
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dfa = ri.residency_index(pd.read_csv(
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'tests/assertion_files/nsbs.csv'), calculation_method='timedelta')
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input_file = pd.read_csv('tests/assertion_files/nsbs.csv')
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dfa = ri.residency_index(input_file, calculation_method='timedelta', **detect(input_file))
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dfb = pd.read_csv('tests/assertion_files/nsbs_timedelta_ri.csv')
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dfa.sort_values(['station', 'days_detected'], inplace=True)
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dfb.sort_values(['station', 'days_detected'], inplace=True)
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def test_aggregate_with_overlap(self):
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print(c.YELLOW + 'Testing Aggregate With Overlap RI...' + c.RESET)
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dfa = ri.residency_index(pd.read_csv(
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'tests/assertion_files/nsbs.csv'), calculation_method='aggregate_with_overlap')
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input_file = pd.read_csv('tests/assertion_files/nsbs.csv')
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dfa = ri.residency_index(input_file, calculation_method='aggregate_with_overlap',**detect(input_file))
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dfb = pd.read_csv(
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'tests/assertion_files/nsbs_aggregate_with_overlap_ri.csv')
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dfa.sort_values(['station', 'days_detected'], inplace=True)
@@ -48,8 +48,8 @@ def test_aggregate_with_overlap(self):
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def test_aggregate_no_overlap(self):
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print(c.YELLOW + 'Testing Aggregate No Overlap RI...' + c.RESET)
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dfa = ri.residency_index(pd.read_csv(
52-
'tests/assertion_files/nsbs.csv'), calculation_method='aggregate_no_overlap')
51+
input_file = pd.read_csv('tests/assertion_files/nsbs.csv')
52+
dfa = ri.residency_index(input_file, calculation_method='aggregate_no_overlap',**detect(input_file))
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dfb = pd.read_csv(
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'tests/assertion_files/nsbs_aggregate_no_overlap_ri.csv')
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dfa.sort_values(['station', 'days_detected'], inplace=True)

‎tests/unqid_test.py‎

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Original file line numberDiff line numberDiff line change
@@ -10,14 +10,14 @@ class UniqueDetectionIdTest(unittest.TestCase):
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def test_add_unqdetecid_file(self):
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print(c.YELLOW+'Testing Unique ID file...'+c.RESET)
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dfa = add_unqdetecid('tests/assertion_files/nsbs_nounq.csv')
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dfa = add_unqdetecid('tests/assertion_files/nsbs_nounq.csv', column_name="unqdetecid")
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dfb = pd.read_csv('tests/assertion_files/nsbs_unqid.csv')
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pt.assert_frame_equal(dfa, dfb, check_like=True)
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print( c.GREEN+'OK!\n'+c.RESET)
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def test_add_unqdetecid_file(self):
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print( c.YELLOW+'Testing Unique ID DataFrame...'+c.RESET)
20-
dfa = add_unqdetecid(pd.read_csv('tests/assertion_files/nsbs_nounq.csv'))
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dfa = add_unqdetecid(pd.read_csv('tests/assertion_files/nsbs_nounq.csv'), column_name="unqdetecid")
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dfb =pd.read_csv('tests/assertion_files/nsbs_unqid.csv')
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pt.assert_frame_equal(dfa, dfb, check_like=True)
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print( c.GREEN+'OK!\n'+c.RESET)

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