def test_quickgrid():
"""test quick grid."""
dat2 = [[1, 1], [2, 1.3333333333333333]]
x = np.array([1, 2, 1])
y = np.array([1, 1, 2])
z = np.array([1, 1, 2])
dat = dataprep.quickgrid(x, y, z, 1)
np.testing.assert_array_equal(dat, dat2)
def tests():
""" Tests to debug """
app = QtWidgets.QApplication(sys.argv)
ttt = PTime()
aaa = dp.GroupProj('Input Projection')
ttt.since_last_call()
pdb.set_trace()
points = np.random.rand(1000000, 2)
values = dp.func(points[:, 0], points[:, 1])
dat = dp.quickgrid(points[:, 0], points[:, 1], values, .001, numits=-1)
plt.imshow(dat)
plt.colorbar()
plt.show()
def tiltdepth(self, data):
""" Calculate tilt depth """
self.pbar.setValue(0)
self.pbar.setMaximum(4)
# RTP
inc = self.dsb_inc.value()
dec = self.dsb_dec.value()
zout = dataprep.rtp(data, inc, dec)
# Tilt
self.pbar.setValue(1)
nr, nc = zout.data.shape
dy, dx = np.gradient(zout.data)
dxtot = np.sqrt(dx**2 + dy**2)
dz = cooper.vertical(zout.data)
t1 = np.arctan(dz / dxtot)
self.pbar.setValue(2)
# A negative number implies we are straddling 0
# Contour tilt
x = zout.extent[0] + np.arange(nc) * zout.xdim + zout.xdim / 2
y = zout.extent[-1] - np.arange(nr) * zout.ydim - zout.ydim / 2
X, Y = np.meshgrid(x, y)
Z = np.rad2deg(t1)
self.X = X
self.Y = Y
self.Z = Z
cnt0 = self.axes.contour(X, Y, Z, [0])
cnt45 = self.axes.contour(X, Y, Z, [45], alpha=0)
cntm45 = self.axes.contour(X, Y, Z, [-45], alpha=0)
self.pbar.setValue(3)
gx0, gy0, cgrad0, cntid0 = vgrad(cnt0)
gx45, gy45, _, _ = vgrad(cnt45)
gxm45, gym45, _, _ = vgrad(cntm45)
g0 = np.transpose([gx0, gy0])
self.pbar.setValue(4)
dmin1 = []
dmin2 = []
for i, j in self.pbar.iter(g0):
dmin1.append(distpc(gx45, gy45, i, j, 0))
dmin2.append(distpc(gxm45, gym45, i, j, 0))
dx1 = gx45[dmin1] - gx0
dy1 = gy45[dmin1] - gy0
dx2 = gxm45[dmin2] - gx0
dy2 = gym45[dmin2] - gy0
grad = np.arctan2(dy1, dx1) * 180 / pi
grad[grad > 90] -= 180
grad[grad < -90] += 180
gtmp1 = np.abs(90 - np.abs(grad - cgrad0))
grad = np.arctan2(dy2, dx2) * 180 / pi
grad[grad > 90] -= 180
grad[grad < -90] += 180
gtmp2 = np.abs(90 - np.abs(grad - cgrad0))
gtmp = np.logical_and(gtmp1 <= 10, gtmp2 <= 10)
gx0 = gx0[gtmp]
gy0 = gy0[gtmp]
cntid0 = cntid0[gtmp]
dx1 = dx1[gtmp]
dy1 = dy1[gtmp]
dx2 = dx2[gtmp]
dy2 = dy2[gtmp]
dist1 = np.sqrt(dx1**2 + dy1**2)
dist2 = np.sqrt(dx2**2 + dy2**2)
dist = np.min([dist1, dist2], 0)
self.x0 = gx0
self.x1 = dx1 + gx0
self.x2 = dx2 + gx0
self.y0 = gy0
self.y1 = dy1 + gy0
self.y2 = dy2 + gy0
self.depths = np.transpose([gx0, gy0, cntid0.astype(int), dist])
tmp = dataprep.quickgrid(gx0,
gy0,
dist,
data.xdim,
showtext=self.showtext)
mask = np.ma.getmaskarray(tmp)
gdat = tmp.data
dat = Data()
dat.data = np.ma.masked_invalid(gdat[::-1])
dat.data.mask = mask[::-1]
dat.nullvalue = dat.data.fill_value
dat.dataid = data.dataid
dat.xdim = data.xdim
dat.ydim = data.xdim
dat.extent = [gx0.min(), gx0.max(), gy0.min(), gy0.max()]
self.outdata['Raster'] = [dat]
def get_modis(ifile):
"""
Gets MODIS data
Parameters
----------
ifile : str
filename to import
Returns
-------
dat : PyGMI raster Data
dataset imported
"""
dat = []
ifile = ifile[:]
dataset = gdal.Open(ifile, gdal.GA_ReadOnly)
subdata = dataset.GetSubDatasets()
latentry = [i for i in subdata if 'Latitude' in i[1]]
subdata.pop(subdata.index(latentry[0]))
dataset = None
dataset = gdal.Open(latentry[0][0], gdal.GA_ReadOnly)
rtmp = dataset.GetRasterBand(1)
lats = rtmp.ReadAsArray()
latsdim = ((lats.max() - lats.min()) / (lats.shape[0] - 1)) / 2
lonentry = [i for i in subdata if 'Longitude' in i[1]]
subdata.pop(subdata.index(lonentry[0]))
dataset = None
dataset = gdal.Open(lonentry[0][0], gdal.GA_ReadOnly)
rtmp = dataset.GetRasterBand(1)
lons = rtmp.ReadAsArray()
lonsdim = ((lons.max() - lons.min()) / (lons.shape[1] - 1)) / 2
lonsdim = latsdim
tlx = lons.min() - abs(lonsdim / 2)
tly = lats.max() + abs(latsdim / 2)
cols = int((lons.max() - lons.min()) / lonsdim) + 1
rows = int((lats.max() - lats.min()) / latsdim) + 1
newx2, newy2 = np.mgrid[0:rows, 0:cols]
newx2 = newx2 * lonsdim + tlx
newy2 = tlx - newy2 * latsdim
tmp = []
for i in subdata:
if 'HDF4_EOS:EOS_SWATH' in i[0]:
tmp.append(i)
subdata = tmp
i = -1
for ifile2, bandid2 in subdata:
dataset = None
dataset = gdal.Open(ifile2, gdal.GA_ReadOnly)
rtmp2 = dataset.ReadAsArray()
if rtmp2.shape[-1] == min(rtmp2.shape) and rtmp2.ndim == 3:
rtmp2 = np.transpose(rtmp2, (2, 0, 1))
nbands = 1
if rtmp2.ndim == 3:
nbands = rtmp2.shape[0]
for i2 in range(nbands):
rtmp = dataset.GetRasterBand(i2 + 1)
bandid = rtmp.GetDescription()
nval = rtmp.GetNoDataValue()
i += 1
dat.append(Data())
if rtmp2.ndim == 3:
dat[i].data = rtmp2[i2]
else:
dat[i].data = rtmp2
newx = lons[dat[i].data != nval]
newy = lats[dat[i].data != nval]
newz = dat[i].data[dat[i].data != nval]
if newx.size == 0:
dat[i].data = np.zeros((rows, cols)) + nval
else:
tmp = quickgrid(newx, newy, newz, latsdim)
mask = np.ma.getmaskarray(tmp)
gdat = tmp.data
dat[i].data = np.ma.masked_invalid(gdat[::-1])
dat[i].data.mask = mask[::-1]
if dat[i].data.dtype.kind == 'i':
if nval is None:
nval = 999999
nval = int(nval)
elif dat[i].data.dtype.kind == 'u':
if nval is None:
nval = 0
nval = int(nval)
else:
if nval is None:
nval = 1e+20
nval = float(nval)
dat[i].data = np.ma.masked_invalid(dat[i].data)
dat[i].data.mask = (np.ma.getmaskarray(dat[i].data) |
(dat[i].data == nval))
if dat[i].data.mask.size == 1:
dat[i].data.mask = (np.ma.make_mask_none(dat[i].data.shape) +
np.ma.getmaskarray(dat[i].data))
dat[i].dataid = bandid2 + ' ' + bandid
dat[i].nullvalue = nval
dat[i].xdim = abs(lonsdim)
dat[i].ydim = abs(latsdim)
rows, cols = dat[i].data.shape
xmin = tlx
ymax = tly
ymin = ymax - rows * dat[i].ydim
xmax = xmin + cols * dat[i].xdim
dat[i].extent = [xmin, xmax, ymin, ymax]
srs = osr.SpatialReference()
srs.ImportFromWkt(dataset.GetProjection())
srs.AutoIdentifyEPSG()
dat[i].wkt = srs.ExportToWkt()
dataset = None
return dat
def get_modis(ifile):
"""
Gets MODIS data
Parameters
----------
ifile : str
filename to import
Returns
-------
dat : PyGMI raster Data
dataset imported
"""
dat = []
ifile = ifile[:]
dataset = gdal.Open(ifile, gdal.GA_ReadOnly)
subdata = dataset.GetSubDatasets()
latentry = [i for i in subdata if 'Latitude' in i[1]]
subdata.pop(subdata.index(latentry[0]))
dataset = gdal.Open(latentry[0][0], gdal.GA_ReadOnly)
rtmp = dataset.GetRasterBand(1)
lats = rtmp.ReadAsArray()
latsdim = ((lats.max()-lats.min())/(lats.shape[0]-1))/2
lonentry = [i for i in subdata if 'Longitude' in i[1]]
subdata.pop(subdata.index(lonentry[0]))
dataset = gdal.Open(lonentry[0][0], gdal.GA_ReadOnly)
rtmp = dataset.GetRasterBand(1)
lons = rtmp.ReadAsArray()
lonsdim = ((lons.max()-lons.min())/(lons.shape[1]-1))/2
lonsdim = latsdim
tlx = lons.min()-abs(lonsdim/2)
tly = lats.max()+abs(latsdim/2)
cols = int((lons.max()-lons.min())/lonsdim)+1
rows = int((lats.max()-lats.min())/latsdim)+1
newx2, newy2 = np.mgrid[0:rows, 0:cols]
newx2 = newx2*lonsdim + tlx
newy2 = tlx - newy2*latsdim
tmp = []
for i in subdata:
if 'HDF4_EOS:EOS_SWATH' in i[0]:
tmp.append(i)
subdata = tmp
i = -1
for ifile2, bandid2 in subdata:
dataset = gdal.Open(ifile2, gdal.GA_ReadOnly)
gtr = dataset.GetGeoTransform()
rtmp2 = dataset.ReadAsArray()
if rtmp2.shape[-1] == min(rtmp2.shape) and rtmp2.ndim == 3:
rtmp2 = np.transpose(rtmp2, (2, 0, 1))
nbands = 1
if rtmp2.ndim == 3:
nbands = rtmp2.shape[0]
for i2 in range(nbands):
rtmp = dataset.GetRasterBand(i2+1)
bandid = rtmp.GetDescription()
nval = rtmp.GetNoDataValue()
i += 1
dat.append(Data())
if rtmp2.ndim == 3:
dat[i].data = rtmp2[i2]
else:
dat[i].data = rtmp2
newx = lons[dat[i].data != nval]
newy = lats[dat[i].data != nval]
newz = dat[i].data[dat[i].data != nval]
if newx.size == 0:
dat[i].data = np.zeros((rows, cols)) + nval
else:
tmp = quickgrid(newx, newy, newz, latsdim)
mask = np.ma.getmaskarray(tmp)
gdat = tmp.data
dat[i].data = np.ma.masked_invalid(gdat[::-1])
dat[i].data.mask = mask[::-1]
if dat[i].data.dtype.kind == 'i':
if nval is None:
nval = 999999
nval = int(nval)
elif dat[i].data.dtype.kind == 'u':
if nval is None:
nval = 0
nval = int(nval)
else:
if nval is None:
nval = 1e+20
nval = float(nval)
dat[i].data = np.ma.masked_invalid(dat[i].data)
dat[i].data.mask = np.ma.getmaskarray(dat[i].data) | (dat[i].data == nval)
if dat[i].data.mask.size == 1:
dat[i].data.mask = (np.ma.make_mask_none(dat[i].data.shape) +
np.ma.getmaskarray(dat[i].data))
dat[i].nrofbands = dataset.RasterCount
dat[i].tlx = tlx
dat[i].tly = tly
dat[i].dataid = bandid2+' '+bandid
dat[i].nullvalue = nval
dat[i].rows = dat[i].data.shape[0]
dat[i].cols = dat[i].data.shape[1]
dat[i].xdim = abs(lonsdim)
dat[i].ydim = abs(latsdim)
dat[i].gtr = gtr
srs = osr.SpatialReference()
srs.ImportFromWkt(dataset.GetProjection())
srs.AutoIdentifyEPSG()
dat[i].wkt = srs.ExportToWkt()
return dat