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import datetime
import numpy as np
wd = pathlib.Path(__file__).parent
fns_pass = (wd / "example_data").glob("*.ict")
fns_fail = (wd / "example_data" / "will_fail").glob("*.ict")
def compareFiles(fn, strIn, strOut, skiplines=0, nlines=-1): # pragma: no cover
content_in = strIn.readlines()
content_out = strOut.readlines()
content_in = content_in[skiplines : (skiplines + nlines)]
content_out = content_out[skiplines : (skiplines + nlines)]
for inline, outline in zip(content_in, content_out):
valid_data_line = False
# maybe this is a data line in which we only have different number formatting?
# compare as floats
# try:
insteps = [float(x) for x in inline.split(",")]
outsteps = [float(x) for x in outline.split(",")]
if len(insteps) == len(outsteps):
valid_data_line = True
for i in range(len(insteps)):
valid_data_line = valid_data_line and insteps[i] == outsteps[i]
# except:
# pass
# try:
insteps = [x.strip() for x in inline.split(",")]
outsteps = [x.strip() for x in outline.split(",")]
if len(insteps) == 2 and len(outsteps) == 3:
valid_var_line = (
insteps[0] == outsteps[0]
and insteps[1] == outsteps[1]
and insteps[1] == outsteps[2]
)
# except:
# pass
print(f"{str(fn)}: line {i:d} differs:")
print(f" input: {inline}")
print(f" output: {outline}")
self.fn = wd / "example_data" / "NOx_RHBrown_20040830_R0.ict"
ict = icartt.Dataset(self.fn, loadData=False)
self.assertEqual(type(ict), icartt.Dataset)
ict = icartt.Dataset(self.fn, loadData=False)
self.assertEqual(ict.format, icartt.Formats.FFI1001)
ict = icartt.Dataset(self.fn, loadData=False)
self.assertEqual(ict.nHeader, self.nHeader)
self.assertEqual(len(ict.dependentVariables), 9)
self.assertEqual(len(ict.normalComments), 18)
self.assertEqual(len(ict.specialComments), 0)
ict = icartt.Dataset(self.fn, loadData=False)
self.assertEqual(ict.independentVariable.shortname, "Start_UTC")
self.assertEqual(ict.independentVariable.units, "seconds")
self.assertEqual(
ict.independentVariable.standardname, "number_of_seconds_from_0000_UTC"
)
self.assertEqual(ict.independentVariable.longname, None)
self.assertEqual(ict.independentVariable.scale, 1.0)
self.assertEqual(ict.independentVariable.miss, -99999.0)
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ict = icartt.Dataset(self.fn, loadData=False)
self.assertEqual(
[DVAR.shortname for DVAR in ict.dependentVariables.values()],
[
"Stop_UTC",
"Mid_UTC",
"DLat",
"DLon",
"Elev",
"NO_ppbv",
"NO_1sig",
"NO2_ppbv",
"NO2_1sig",
],
)
self.assertEqual(
[DVAR.units for DVAR in ict.dependentVariables.values()],
[
"seconds",
"seconds",
"deg_N",
"deg_E",
"meters",
"ppbv",
"ppbv",
"ppbv",
"ppbv",
],
)
self.assertEqual(
[DVAR.standardname for DVAR in ict.dependentVariables.values()],
[None, None, None, None, None, None, None, None, None],
)
self.assertEqual(
[DVAR.longname for DVAR in ict.dependentVariables.values()],
[None, None, None, None, None, None, None, None, None],
)
self.assertEqual(
[DVAR.scale for DVAR in ict.dependentVariables.values()],
["1", "1", "1", "1", "1", "1", "1", "1", "1"],
)
self.assertEqual(
[DVAR.miss for DVAR in ict.dependentVariables.values()],
[
"-9999",
"-9999",
"-9999",
"-9999",
"-9999",
"-9999",
"-9999",
"-9999",
"-9999",
],
)
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ict = icartt.Dataset(self.fn, loadData=False)
self.assertEqual(
ict.normalComments.keywords["PI_CONTACT_INFO"].data,
[
"325 Broadway, Boulder, CO 80305; 303-497-3226; email:eric.j.williams@noaa.gov"
],
)
self.assertEqual(
ict.normalComments.keywords["PLATFORM"].data,
["NOAA research vessel Ronald H. Brown"],
)
self.assertEqual(
ict.normalComments.keywords["LOCATION"].data,
["Latitude, longitude and elevation data are included in the data records"],
)
self.assertEqual(ict.normalComments.keywords["ASSOCIATED_DATA"].data, ["N/A"])
self.assertEqual(
ict.normalComments.keywords["INSTRUMENT_INFO"].data,
["NO: chemiluminescence; NO2: narrow-band photolysis/chemiluminescence"],
)
self.assertEqual(
ict.normalComments.keywords["DATA_INFO"].data,
[
"All data with the exception of the location data are in ppbv. All oneminute averages contain at least 35 seconds of data, otherwise missing."
],
)
self.assertEqual(
ict.normalComments.keywords["UNCERTAINTY"].data,
["included in the data records as variables with a _1sig suffix"],
)
self.assertEqual(ict.normalComments.keywords["ULOD_FLAG"].data, ["-7777"])
self.assertEqual(ict.normalComments.keywords["ULOD_VALUE"].data, ["N/A"])
self.assertEqual(ict.normalComments.keywords["LLOD_FLAG"].data, ["-8888"])
self.assertEqual(
ict.normalComments.keywords["LLOD_VALUE"].data,
["N/A, N/A, N/A, N/A, N/A, 0.005, N/A, 0.025, N/A"],
)
self.assertEqual(ict.normalComments.keywords["DM_CONTACT_INFO"].data, ["N/A"])
self.assertEqual(
ict.normalComments.keywords["PROJECT_INFO"].data,
[
"ICARTT study; 1 July-15 August 2004; Gulf of Maine and North Atlantic Ocean"
],
)
self.assertEqual(
ict.normalComments.keywords["STIPULATIONS_ON_USE"].data,
["Use of these data requires PRIOR OK from the PI"],
)
self.assertEqual(ict.normalComments.keywords["OTHER_COMMENTS"].data, ["N/A"])
ict = icartt.Dataset(self.fn, loadData=True)
self.assertEqual(type(ict), icartt.Dataset)
ict = icartt.Dataset(self.fn, loadData=False)
self.assertTrue(compareFiles(self.fn, strIn, strOut, nlines=self.nHeader))
ict = icartt.Dataset(self.fn, loadData=True)
self.assertTrue(compareFiles(self.fn, strIn, strOut, skiplines=self.nHeader))
ict = icartt.Dataset(self.fn, loadData=True)
self.assertTrue(compareFiles(self.fn, strIn, strOut))
class Create1001TestCase(unittest.TestCase):
def testCreateDs(self):
ict = icartt.Dataset(format=icartt.Formats.FFI1001)
ict.PIName = "Knote, Christoph"
ict.PIAffiliation = "Faculty of Medicine, University Augsburg, Germany"
ict.dataSourceDescription = "Example data"
ict.missionName = "MBEES"
ict.dateOfCollection = now.timetuple()[:3]
ict.dateOfRevision = now.timetuple()[:3]
ict.dataIntervalCode = [0]
ict.independentVariable = icartt.Variable(
"Time_Start",
"seconds_from_0_hours_on_valid_date",
"Time_Start",
"Time_Start",
vartype=icartt.VariableType.IndependentVariable,
scale=1.0,
miss=-9999999,
)
ict.dependentVariables["Time_Stop"] = icartt.Variable(
"Time_Stop",
"seconds_from_0_hours_on_valid_date",
"Time_Stop",
"Time_Stop",
scale=1.0,
miss=-9999999,
)
ict.dependentVariables["Payload"] = icartt.Variable(
"Payload", "some_units", "Payload", "Payload", scale=1.0, miss=-9999999
)
ict.specialComments.append("Some comments on this dataset:")
ict.specialComments.append("They are just examples!")
ict.specialComments.append("Adapt as needed.")
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# we can just use len of the list to check number of comments
self.assertEqual(len(ict.specialComments), 3)
# let's define some normal comments... 21 lines
ncom = {
"PI_CONTACT_INFO": "PI1 pi-email@mail.com\nPI2 more-email@what.com",
"PLATFORM": "a platform",
"LOCATION": "somewhere",
"ASSOCIATED_DATA": "met sensor data",
"INSTRUMENT_INFO": "super cool instrument",
"DATA_INFO": f"icartt Python package version: {icartt.__version__}",
"UNCERTAINTY": "not much",
"ULOD_FLAG": "-7777",
"ULOD_VALUE": "N/A",
"LLOD_FLAG": "-8888",
"LLOD_VALUE": "N/A",
"DM_CONTACT_INFO": "datamanager@mail.edu",
"PROJECT_INFO": "the campaign",
"STIPULATIONS_ON_USE": "no",
"OTHER_COMMENTS": "a lot more info\non multiple lines",
"REVISION": (
"R1\n"
"R1: revised time synchronization.\n"
"R0: initial, preliminary version."
),
}
for k, v in ncom.items():
ict.normalComments.keywords[k].append(v)
# we can check if nlines method of normalComments class works
self.assertEqual(ict.normalComments.nlines, 21)
ict.normalComments.freeform = ["free comment line"]
self.assertEqual(ict.normalComments.nlines, 22)
# we have not added data yet, so data must be None
self.assertIsNone(ict.data[:])
# and times must be NaT
self.assertTrue(np.isnat(ict.times))
ict.data.add(Time_Start=12.3, Time_Stop=12.5, Payload=23789423.2e5)
mydict = {"Time_Start": 12.6, "Time_Stop": 13.1, "Payload": 324235644.1e5}
ict.data.add(**mydict)
data = np.array([(13.4, 14.0, 2348925e5), (14.1, 14.9, 23425634e5)])
ict.data.addBulk(data)
# elements of the time array must be equal to our input
t0 = np.datetime64(datetime.datetime(*now.timetuple()[:3]), "ns")
for have, want in zip(ict.times, (12.3, 12.6, 13.4, 14.1)):
if __name__ == "__main__": # pragma: no cover
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=UserWarning)
unittest.main()