def test_warpcraters(self):
# Not the real image dimensions, but whatever
imgdim = [250, 300]
ilong = self.craters["Long"].as_matrix()
ilat = self.craters["Lat"].as_matrix()
res = self.oproj.transform_points(x=ilong,
y=ilat,
src_crs=self.geoproj)[:, :2]
# Get output
x, y = mkin.coord2pix(res[:, 0],
res[:, 1],
self.oextent,
imgdim,
origin="upper")
ctr_sub = mkin.WarpCraterLoc(self.craters,
self.geoproj,
self.oproj,
self.oextent,
imgdim,
llbd=None,
origin="upper")
xy_gt = np.r_[x, y]
xy = np.r_[ctr_sub["x"].as_matrix(), ctr_sub["y"].as_matrix()]
self.assertTrue(np.all(np.isclose(xy, xy_gt, rtol=1e-7, atol=1e-10)))
def test_pctoortho(self):
imgo, imgwshp, offset = mkin.WarpImagePad(self.img,
self.iproj,
self.iextent,
self.oproj,
self.oextent,
origin="upper",
rgcoeff=1.2,
fillbg="black")
ctr_xy = mkin.WarpCraterLoc(self.craters,
self.geoproj,
self.oproj,
self.oextent,
imgwshp,
llbd=None,
origin="upper")
ctr_xy.loc[:, "x"] += offset[0]
ctr_xy.loc[:, "y"] += offset[1]
Cd = 1.
pxperkm = mkin.km2pix(imgo.size[1], self.llbd[3] - self.llbd[2], \
dc=Cd, a=1737.4)
ctr_xy["Diameter (pix)"] = ctr_xy["Diameter (km)"] * pxperkm
imgo2, ctr_xy2 = mkin.PlateCarree_to_Orthographic(self.img,
None,
self.llbd,
self.craters,
iglobe=self.iglobe,
ctr_sub=True,
origin="upper",
rgcoeff=1.2,
dontsave=True,
slivercut=0.)
imgo = np.asanyarray(imgo)
imgo2 = np.asanyarray(imgo2)
self.assertTrue(
np.all(
np.isclose(imgo.ravel(), imgo2.ravel(), rtol=1e-6,
atol=1e-10)))
self.assertTrue(ctr_xy.equals(ctr_xy2))
def MakePCOTransform(img, oname, llbd, csvname):
"""Almost identical to make_input_data.PlateCarree_to_Orthographic,
except designed to test relevant loading times when creating large
datasets.
"""
origin = "upper"
rgcoeff = 1.2
ctr_sub = True
iglobe = ccrs.Globe(semimajor_axis=1737400,
semiminor_axis=1737400,
ellipse=None)
craters = pd.read_csv(csvname,
sep=',',
header=0,
engine="c",
encoding="ISO-8859-1")
# Set up Geodetic (long/lat), Plate Carree (usually long/lat, but
# not when globe != WGS84) and Orthographic projections
geoproj = ccrs.Geodetic(globe=iglobe)
iproj = ccrs.PlateCarree(globe=iglobe)
oproj = ccrs.Orthographic(central_longitude=np.mean(llbd[:2]),
central_latitude=np.mean(llbd[2:]),
globe=iglobe)
# Create and transform coordinates of image corners and
# edge midpoints. Due to Plate Carree and Orthographic's symmetries,
# max/min x/y values of these 9 points represent extrema
# of the transformed image.
xll = np.array([llbd[0], np.mean(llbd[:2]), llbd[1]])
yll = np.array([llbd[2], np.mean(llbd[2:]), llbd[3]])
xll, yll = np.meshgrid(xll, yll)
xll = xll.ravel()
yll = yll.ravel()
# [:,:2] becaus we don't need elevation data
res = iproj.transform_points(x=xll, y=yll, src_crs=geoproj)[:, :2]
iextent = [min(res[:, 0]), max(res[:, 0]), min(res[:, 1]), max(res[:, 1])]
res = oproj.transform_points(x=xll, y=yll, src_crs=geoproj)[:, :2]
oextent = [min(res[:, 0]), max(res[:, 0]), min(res[:, 1]), max(res[:, 1])]
imgo, imgwshp, offset = mkin.WarpImagePad(img,
iproj,
iextent,
oproj,
oextent,
origin=origin,
rgcoeff=rgcoeff,
fillbg="white")
# Convert crater x, y position
if ctr_sub:
llbd_in = None
else:
llbd_in = llbd
ctr_xy = mkin.WarpCraterLoc(craters,
geoproj,
oproj,
oextent,
img.size,
llbd=llbd_in)
# Shift crater x, y positions by offset
# (origin doesn't matter for y-shift, since
# padding is symmetric)
ctr_xy.loc[:, "x"] += offset[0]
ctr_xy.loc[:, "y"] += offset[1]
imgo.save(oname)
ctr_xy.to_csv(oname.split(".png")[0] + ".csv", index=False)