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# coding=utf-8
"""Tests QGIS plugin init."""
import os
import unittest
import example
from osgeo import gdal, ogr, osr
from eotimeseriesviewer.utils import file_search
from eotimeseriesviewer.tests import TestObjects
from eotimeseriesviewer.timeseries import *
from eotimeseriesviewer.tests import initQgisApplication
class TestInit(unittest.TestCase):
def createTestDatasets(self):
vsiDir = '/vsimem/tmp'
from eotimeseriesviewer.temporalprofiles2d import date2num
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ns = 50
nl = 100
r1 = np.arange('2000-01-01', '2005-06-14', step=np.timedelta64(16, 'D'), dtype=np.datetime64)
r2 = np.arange('2000-01-01', '2005-06-14', step=np.timedelta64(8, 'D'), dtype=np.datetime64)
drv = gdal.GetDriverByName('ENVI')
crs = osr.SpatialReference()
crs.ImportFromEPSG(32633)
assert isinstance(drv, gdal.Driver)
datasets = []
for i, r in enumerate([r1, r2]):
p = '{}tmpstack{}.bsq'.format(vsiDir, i+1)
ds = drv.Create(p, ns, nl, len(r), eType=gdal.GDT_Float32)
assert isinstance(ds, gdal.Dataset)
ds.SetProjection(crs.ExportToWkt())
dateString = ','.join([str(d) for d in r])
dateString = '{{{}}}'.format(dateString)
ds.SetMetadataItem('wavelength', dateString, 'ENVI')
for b, date in enumerate(r):
decimalYear = date2num(date)
band = ds.GetRasterBand(b+1)
assert isinstance(band, gdal.Band)
band.Fill(decimalYear)
ds.FlushCache()
datasets.append(p)
return datasets
def createTimeSeries(self)->TimeSeries:
files = list(file_search(os.path.dirname(example.__file__), '*.tif', recursive=True))
TS = TimeSeries()
self.assertIsInstance(TS, TimeSeries)
TS.addSources(files)
self.assertTrue(len(TS) > 0)
return TS
configs = [(6, 30, 30, gdal.GDT_Byte, [1, 2, 3, 4, 5, 6], None),
(6, 10, 20, gdal.GDT_CFloat32, [1, 2, 3, 4, 5, 6], 'index'),
(6, 30, 30, gdal.GDT_UInt32, [1, 2, 3, 323, 23., 3.4], 'Micrometers'),
(6, 30, 30, gdal.GDT_Int32, None, None),
#nb:int, px_size_x:float, px_size_y:float, dt:int, wl:list, wlu:str
print(conf)
self.assertIsInstance(sensorID(*conf), str, msg='Unable to create sensorID from "{}"'.format(str(conf)))
def test_TimeSeriesTableModel(self):
TS = self.createTimeSeries()
TM = TimeSeriesTableModel(TS)
self.assertTrue(len(TS) > 0)
self.assertIsInstance(TM, TimeSeriesTableModel)
self.assertIsInstance(TM, QAbstractTableModel)
self.assertTrue(TM.rowCount(None) == len(TS))
tsd = TS[2]
idx = TM.getIndexFromDate(tsd)
self.assertIsInstance(idx, QModelIndex)
def test_timeseriesdatum(self):
file = example.Images.Img_2014_03_20_LC82270652014079LGN00_BOA
tss = TimeSeriesSource.create(file)
sensor = SensorInstrument(tss.sid())
tsd = TimeSeriesDatum(None, tss.date(), sensor)
self.assertIsInstance(tsd, TimeSeriesDatum)
self.assertEqual(tsd.sensor(), sensor)
self.assertEqual(len(tsd), 0)
tsd.addSource(tss)
self.assertEqual(len(tsd), 1)
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self.assertTrue(tsd.year() == 2014)
self.assertTrue(tsd.doy() == 79)
self.assertIsInstance(tsd.decimalYear(), float)
self.assertTrue(tsd.decimalYear() >= 2014 and tsd.decimalYear() < 2015)
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def test_timeseriessource(self):
wcs = r'dpiMode=7&identifier=BGS_EMODNET_CentralMed-MCol&url=http://194.66.252.155/cgi-bin/BGS_EMODnet_bathymetry/ows?VERSION%3D1.1.0%26coverage%3DBGS_EMODNET_CentralMed-MCol'
if False:
webSources = [QgsRasterLayer(wcs, 'test', 'wcs')]
for src in webSources:
tss = TimeSeriesSource.create(src)
self.assertIsInstance(tss, TimeSeriesSource)
sources = [example.Images.Img_2014_03_20_LC82270652014079LGN00_BOA,
gdal.Open(example.Images.Img_2014_03_20_LC82270652014079LGN00_BOA),
QgsRasterLayer(example.Images.Img_2014_03_20_LC82270652014079LGN00_BOA)
]
ref = None
for src in sources:
tss = TimeSeriesSource.create(src)
self.assertIsInstance(tss.spatialExtent(), SpatialExtent)
self.assertIsInstance(tss, TimeSeriesSource)
if not isinstance(ref, TimeSeriesSource):
ref = tss
else:
self.assertTrue(ref == tss)
self.assertTrue(ref.sid() == tss.sid())
mdui = tss.qgsMimeDataUtilsUri()
self.assertIsInstance(mdui, QgsMimeDataUtils.Uri)
lyr, b = mdui.rasterLayer('')
self.assertTrue(b)
self.assertIsInstance(lyr, QgsRasterLayer)
self.assertTrue(lyr.isValid())
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def test_datetimeprecision(self):
img1 = TestObjects.inMemoryImage()
img2 = TestObjects.inMemoryImage()
self.assertIsInstance(img1, gdal.Dataset)
self.assertIsInstance(img2, gdal.Dataset)
t0 = np.datetime64('now')
pairs = [('2018-12-23T14:40:48', '2018-12-23T14:40:47', DateTimePrecision.Minute),
('2018-12-23T14:40', '2018-12-23T14:39', DateTimePrecision.Hour),
('2018-12-23T14:40:48', '2018-12-23T14:40:47', DateTimePrecision.Day),
('2018-12-23', '2018-12-22', DateTimePrecision.Week),
('2018-12-23', '2018-12-01', DateTimePrecision.Month),
('2018-12-23', '2018-11-01', DateTimePrecision.Year),
]
for p in pairs:
t1, t2, precision = p
img1.SetMetadataItem('acquisition time', t1)
img2.SetMetadataItem('acquisition time', t2)
TS = TimeSeries()
self.assertIsInstance(TS, TimeSeries)
self.assertTrue(TS.mDateTimePrecision == DateTimePrecision.Original)
TS.addSources([img1, img2])
self.assertTrue(len(TS) == 2)
TS = TimeSeries()
TS.setDateTimePrecision(precision)
TS.addSources([img1, img2])
self.assertTrue(len(TS) == 1)
p1 = TestObjects.inMemoryImage()
p2 = TestObjects.inMemoryImage()
sources = [p1, p2]
for p in sources:
p.SetMetadataItem('acquisition_date', '2014-04-01')
s = ""
tssList = [TimeSeriesSource.create(p) for p in sources]
TS = TimeSeries()
self.assertTrue(len(TS) == 0)
TS.addSources(tssList)
self.assertTrue(len(TS) == 1)
tsd = TS[0]
self.assertIsInstance(tsd, TimeSeriesDatum)
self.assertTrue(len(tsd.sources()) == 2)
paths = TestObjects.createMultiSourceTimeSeries()
TS = TimeSeries()
TS.addSources(paths)
srcUris = TS.sourceUris()
self.assertTrue(len(srcUris) == len(paths))
self.assertTrue(len(TS) == 0.5 * len(paths))
self.assertTrue(len(TS) == 0.5 * len(srcUris))
def test_timeseries(self):
files = list(file_search(os.path.dirname(example.__file__), '*.tif', recursive=True))
removedDates = []
addedSensors = []
removedSensors = []
sourcesChanged = []
TS = TimeSeries()
self.assertIsInstance(TS, TimeSeries)
TS.sigTimeSeriesDatesAdded.connect(lambda dates: addedDates.extend(dates))
TS.sigTimeSeriesDatesRemoved.connect(lambda dates: removedDates.extend(dates))
TS.sigSourcesChanged.connect(lambda tsd: sourcesChanged.append(tsd))
TS.sigSensorAdded.connect(lambda sensor: addedSensors.append(sensor))
TS.sigSensorRemoved.connect(lambda sensor:removedSensors.append(sensor))
TS.addSources(files)
counts = dict()
self.assertIsInstance(tsd, TimeSeriesDatum)
sensor = tsd.sensor()
if sensor not in counts.keys():
counts[sensor] = 0
counts[sensor] = counts[sensor] + 1
self.assertEqual(len(files), len(TS))
self.assertEqual(len(removedDates), 0)
self.assertTrue(len(addedSensors) == 2)
self.assertIsInstance(TS.maxSpatialExtent(), SpatialExtent)
sensor = TS.sensors()[0]
self.assertIsInstance(sensor, SensorInstrument)
self.assertTrue(sensor == TS.sensor(sensor.id()))
TS.removeSensor(sensor)
self.assertEqual(counts[sensor], len(removedDates))
extent = TS.maxSpatialExtent()
self.assertIsInstance(extent, SpatialExtent)
def test_sensors(self):
tss = TimeSeriesSource.create(example.Images.Img_2014_01_15_LC82270652014015LGN00_BOA)
self.assertIsInstance(tss, TimeSeriesSource)
sensor = SensorInstrument(tss.sid())
sensor2 = SensorInstrument(tss.sid())
self.assertIsInstance(sensor, SensorInstrument)
self.assertTrue(sensor == sensor2)
sensor2.setName('foobar')
self.assertTrue(sensor == sensor2)
self.assertIsInstance(sensor2.id(), str)
lyr = sensor.proxyLayer()
def test_datematching(self):
pass
if __name__ == '__main__':
unittest.main()