def testReal(self):
m1 = _getMapping()
m2 = resample(m1, pxPerDeg=15, method='mean')
m2.checkPlateCarree()
m3 = resample(m2, arcsecPerPx=100, method='nearest')
m3.checkPlateCarree()
assert_array_approx_equal(_bbToArray(m2.boundingBox), _bbToArray(m1.boundingBox), 1)
assert_array_approx_equal(_bbToArray(m3.boundingBox), _bbToArray(m1.boundingBox), 1)
def _testReal(self):
m1 = _getMapping()
m2 = resample(m1, pxPerDeg=15, method='mean')
m2.checkPlateCarree()
m3 = resample(m2, arcsecPerPx=100, method='nearest')
m3.checkPlateCarree()
assert_array_approx_equal(_bbToArray(m2.boundingBox),
_bbToArray(m1.boundingBox), 1)
assert_array_approx_equal(_bbToArray(m3.boundingBox),
_bbToArray(m1.boundingBox), 1)
def testMiracleMapping(self):
m = _getMiracleMapping()
m.checkGuarantees()
m = m.maskedByElevation(10)
m.checkGuarantees()
m = resample(m, arcsecPerPx=100, method='mean')
m.checkGuarantees()
def test(self):
lats, lons, latsCenter, lonsCenter = testCoordsDiscontinuity()
altitude = 110
rgb = ma.masked_array(
(np.random.rand(lats.shape[0] - 1, lats.shape[1] - 1, 3) *
255).astype(np.uint8))
elevation = np.zeros((rgb.shape[0], rgb.shape[1]))
date = datetime.datetime.now()
mapping = GenericMapping(lats,
lons,
latsCenter,
lonsCenter,
elevation,
altitude,
rgb,
cameraPosGCRS=np.array([0, 0, 0]),
photoTime=date,
identifier=None)
m = resample(mapping, pxPerDeg=1, method='mean')
m.checkPlateCarree()
mapping = resampleMLatMLT(mapping, arcsecPerPx=100, method='nearest')
assert not mapping.isPlateCarree
mlat, mlt = mapping.mLatMlt
mlat, mlt = mlat.data, mlt.data
smlon = mltToSmLon(mlt)
checkPlateCarree(mlat, smlon)
def testSpacecraftMappingSouth(self):
m = _getMappingSouth()
m.checkGuarantees()
m = m.maskedByElevation(10)
m.checkGuarantees()
m = resample(m, arcsecPerPx=100, method='mean')
m.checkGuarantees()
def _testColors(self):
m = _getMappingNorth()
m = resample(m, arcsecPerPx=100, method='mean')
saveFig('test_white.png', drawStereographic(m, bottomTitle='foo'), bgcolor='white')
saveFig('test_black.png', drawStereographic(m, bottomTitle='foo'), bgcolor='black')
saveFig('test_polar_white.png', drawMLatMLTPolar(m), bgcolor='white')
saveFig('test_polar_black.png', drawMLatMLTPolar(m), bgcolor='black')
def testMiracleMapping(self):
m = _getMiracleMapping()
m.checkGuarantees()
m = m.maskedByElevation(10)
m.checkGuarantees()
m = resample(m, arcsecPerPx=100, method='mean')
m.checkGuarantees()
def testSpacecraftMappingSouth(self):
m = _getMappingSouth()
m.checkGuarantees()
m = m.maskedByElevation(10)
m.checkGuarantees()
m = resample(m, arcsecPerPx=100, method='mean')
m.checkGuarantees()
def _testMLatMLTPolarMapNorthPole(self):
m = _getMappingNorth()
m.checkGuarantees()
#m = m.maskedByElevation(10)
#m.checkGuarantees()
m = resample(m, arcsecPerPx=100, method='mean')
m.checkGuarantees()
saveFig('test_mlatmlt_polar_north.png', drawMLatMLTPolar(m))
def _testMLatMLTPolarMapBothHemispheres(self):
m = _getMappingSouth()
m.checkGuarantees()
#m = m.maskedByElevation(10)
#m.checkGuarantees()
m = resample(m, arcsecPerPx=100, method='mean')
m.checkGuarantees()
seqbb = BoundingBox(latSouth=-61.150846231, lonWest=142.622725698, latNorth=6.84984918353, lonEast=-116.820615123)
saveFig('test_mlatmlt_polar_seqbb.png', drawMLatMLTPolar(m, boundingBox=seqbb))
def _testMiracle(self):
m = _getMiracleMapping()
saveFig('heat_intersection.png', drawHeatmap(m.intersectionInflatedCorner[...,0]))
drawHeatmaps(m)
m.checkGuarantees()
m = m.maskedByElevation(10)
m.checkGuarantees()
m = resample(m, arcsecPerPx=100, method='mean')
m.checkGuarantees()
saveFig('test_stereo.png', drawStereographic(m))
def testSpacecraftMappingNorth(self):
m = _getMappingNorth()
m.checkGuarantees()
m2 = m.maskedByElevation(10)
m2.checkGuarantees()
assert np.any(~(m.latsCenter.mask == m2.latsCenter.mask))
assert np.any(~(m.lats.mask == m2.lats.mask))
m3 = resample(m, arcsecPerPx=100, method='mean')
m3.checkGuarantees()
def testSpacecraftMappingNorth(self):
m = _getMappingNorth()
m.checkGuarantees()
m2 = m.maskedByElevation(10)
m2.checkGuarantees()
assert np.any(~(m.latsCenter.mask == m2.latsCenter.mask))
assert np.any(~(m.lats.mask == m2.lats.mask))
m3 = resample(m, arcsecPerPx=100, method='mean')
m3.checkGuarantees()
def _testHoleBug(self):
"""
Triggers a (now fixed) bug that occured when 'mean' resampling led to
single-polygon holes where surrounding polygons were well-defined.
A hole is a polygon such that all corners are defined and just the polygon
center data was missing (color etc.). The issue was that those holes were
not filtered and led to subsequent errors. The fix was to filter not by whether
all corners are defined but whether the color is defined as this also guarantees
that the corners are defined.
"""
m = _getMappingNorth()
m = resample(m, arcsecPerPx=200, method='mean')
# saving as svg without rasterization will lead to errors when trying to use
# polygons with NaN colors; saving as png only leads to black areas!
saveFig('test_stereo.svg', drawStereographic(m, rasterized=False))
def testPlateCarreeNetCDFExport(self):
imagePath = getResourcePath('ISS030-E-102170_dc.jpg')
wcsPath = getResourcePath('ISS030-E-102170_dc.wcs')
mapping = getMapping(imagePath, wcsPath, fastCenterCalculation=True)
mapping = resample(mapping, arcsecPerPx=200)
path = tempfile.mktemp(suffix='.nc')
try:
auromat.export.netcdf.write(path, mapping)
cdfmapping = NetCDFMapping(path)
cdfmapping.checkGuarantees()
cdfmapping.checkPlateCarree()
check_equal(cdfmapping, mapping)
finally:
if os.path.exists(path):
os.remove(path)
def testPlateCarreeNetCDFExport(self):
imagePath = getResourcePath('ISS030-E-102170_dc.jpg')
wcsPath = getResourcePath('ISS030-E-102170_dc.wcs')
mapping = getMapping(imagePath, wcsPath, fastCenterCalculation=True)
mapping = resample(mapping, arcsecPerPx=200)
path = tempfile.mktemp(suffix='.nc')
try:
auromat.export.netcdf.write(path, mapping)
cdfmapping = NetCDFMapping(path)
cdfmapping.checkGuarantees()
cdfmapping.checkPlateCarree()
check_equal(cdfmapping, mapping)
finally:
if os.path.exists(path):
os.remove(path)
def test(self):
np.set_printoptions(precision=1)
lats, lons, latsCenter, lonsCenter = testCoordsDiscontinuity()
altitude = 110
rgb = ma.masked_array((np.random.rand(lats.shape[0]-1,lats.shape[1]-1,3) * 255).astype(np.uint8))
elevation = np.zeros((rgb.shape[0], rgb.shape[1]))
mapping = GenericMapping(lats, lons, latsCenter, lonsCenter, elevation, altitude, rgb,
cameraPosGCRS=np.array([0,0,0]), photoTime=datetime.datetime.now(), identifier=None)
m = resample(mapping, pxPerDeg=1, method='mean')
m.checkPlateCarree()
mapping = resampleMLatMLT(mapping, arcsecPerPx=100, method='nearest')
assert not mapping.isPlateCarree
mlat, mlt = mapping.mLatMlt
smlon = mltToSmLon(mlt)
checkPlateCarree(mlat, smlon)
import numpy as np
import cv2
import base64
import math
import matplotlib.pyplot as plt
for i in range(64757, 64758):
dcfolder = '/home/lianqiang/data/iss_imgs_dc'
wcsfolder = '/home/lianqiang/data/iss_wcs'
print("Calculating...")
provider = SpacecraftMappingProvider(dcfolder, wcsfolder)
number = str(i)
mapping = provider.getById(number) # id = any unique part of the filename
resampled = resample(mapping, arcsecPerPx=100)
masked = resampled.maskedByElevation(10)
# h = mapping.img.shape[0]
# w = mapping.img.shape[1]
# img = list(np.array(masked.img).flatten())
# lats = list(np.array(masked.lats).flatten())
# lons = list(np.array(masked.lons).flatten())
img = masked.img
lats = masked.lats
lons = masked.lons
# plt.scatter(lats, lons, np.array(masked.img).flatten())
# plt.show()
# for i in range(0, len(lats)):
def _testPoleBug(self):
m1 = _getMapping()
m2 = resample(m1, arcsecPerPx=100, method='mean')
assert_array_approx_equal(_bbToArray(m2.boundingBox),
_bbToArray(m1.boundingBox), 1)
def _profileMeanResampling(m):
print('profiling mean resampling')
resample(m, method='mean')
def _testStereographicMap(self):
m = _getMappingSouth()
m = m.maskedByElevation(10)
m = resample(m, arcsecPerPx=100, method='mean')
saveFig('test_stereo.svg', drawStereographic(m), dpi=200)
def _testBBPole2(self):
bb = BoundingBox(latSouth=35.3446724767, lonWest=-180.0, latNorth=90.0, lonEast=180.0)
m = _getMappingNorth()
m = resample(m, arcsecPerPx=100, method='mean')
saveFig('test_bb.png', drawStereographic(m, boundingBox=bb))
import numpy as np
import cv2
import base64
import math
import matplotlib.pyplot as plt
for i in range(64757, 64758):
dcfolder = '/home/lianqiang/data/iss_imgs_dc'
wcsfolder = '/home/lianqiang/data/iss_wcs'
print("Calculating...")
provider = SpacecraftMappingProvider(dcfolder, wcsfolder)
number = str(i)
mapping = provider.getById(number) # id = any unique part of the filename
resampled = resample(mapping, arcsecPerPx=100)
masked = resampled.maskedByElevation(10)
# h = mapping.img.shape[0]
# w = mapping.img.shape[1]
# img = list(np.array(masked.img).flatten())
# lats = list(np.array(masked.lats).flatten())
# lons = list(np.array(masked.lons).flatten())
img = masked.img
lats = masked.lats
lons = masked.lons
# plt.scatter(lats, lons, np.array(masked.img).flatten())
# plt.show()
# for i in range(0, len(lats)):
def _testSingle(self):
provider = ISSMappingProvider(url, cacheFolder, altitude=110)
mapping = provider.get(datetime(2012,1,25,9,26,57))
mapping = resample(mapping, arcsecPerPx=100)
saveFig('test.png', drawStereographicMLatMLT(mapping))
def _profileMeanResampling(m):
print('profiling mean resampling')
resample(m, method='mean')
def testPoleBug(self):
m1 = _getMapping()
m2 = resample(m1, arcsecPerPx=100, method='mean')
assert_array_approx_equal(_bbToArray(m2.boundingBox), _bbToArray(m1.boundingBox), 1)
