def settings(self):
""" This is called when the used double clicks the routine from the
main PyGMI interface"""
if 'Raster' not in self.indata:
return
self.indata['Raster'] = dataprep.merge(self.indata['Raster'])
data = self.indata['Raster']
blist = []
for i in data:
blist.append(i.dataid)
self.cbox_band1.clear()
self.cbox_band1.addItems(blist)
self.show()
QtWidgets.QApplication.processEvents()
return True
def settings(self):
""" This is called when the used double clicks the routine from the
main PyGMI interface"""
if 'Raster' not in self.indata:
return
self.indata['Raster'] = dataprep.merge(self.indata['Raster'])
data = self.indata['Raster']
blist = []
for i in data:
blist.append(i.dataid)
self.cbox_band1.clear()
self.cbox_band1.addItems(blist)
self.show()
QtWidgets.QApplication.processEvents()
return True
def settings(self, test=False):
"""
Entry point.
This is called when the used double clicks the routine from the
main PyGMI interface.
Parameters
----------
test : bool, optional
Parameter indicating testing. The default is False.
Returns
-------
bool
True if successful, False otherwise.
"""
if 'Raster' not in self.indata:
return False
self.indata['Raster'] = dataprep.merge(self.indata['Raster'])
data = self.indata['Raster']
blist = []
for i in data:
blist.append(i.dataid)
self.cbox_band1.clear()
self.cbox_band1.addItems(blist)
if test is False:
self.show()
QtWidgets.QApplication.processEvents()
return True
def settings(self, test=None):
"""
Settings Dialog. This is the main entrypoint into this routine. It also
contains the main IGRF code.
"""
# Variable declaration
# Control variables
self.proj.set_current(self.indata['Raster'][0].wkt)
data = dp.merge(self.indata['Raster'])
self.combobox_dtm.clear()
self.combobox_mag.clear()
for i in data:
self.combobox_dtm.addItem(i.dataid)
self.combobox_mag.addItem(i.dataid)
if len(data) > 1:
self.combobox_dtm.setCurrentIndex(1)
if test is None:
tmp = self.exec_()
if tmp == 0:
return False
self.acceptall()
with open(os.path.join(os.path.dirname(__file__),
'IGRF12.cof')) as mdf:
modbuff = mdf.readlines()
fileline = -1 # First line will be 1
model = []
epoch = []
max1 = []
max2 = []
max3 = []
yrmin = []
yrmax = []
altmin = []
altmax = []
irec_pos = []
# First model will be 0
for i in modbuff:
fileline += 1 # On new line
if i[:3] == ' ':
i2 = i.split()
model.append(i2[0])
epoch.append(float(i2[1]))
max1.append(int(i2[2]))
max2.append(int(i2[3]))
max3.append(int(i2[4]))
yrmin.append(float(i2[5]))
yrmax.append(float(i2[6]))
altmin.append(float(i2[7]))
altmax.append(float(i2[8]))
irec_pos.append(fileline)
i = self.combobox_mag.currentIndex()
maggrid = data[i]
i = self.combobox_dtm.currentIndex()
data = data[i]
altgrid = data.data.flatten() * 0.001 # in km
maxyr = max(yrmax)
sdate = self.dateedit.date()
sdate = sdate.year()+sdate.dayOfYear()/sdate.daysInYear()
alt = self.dsb_alt.value()
drows, dcols = data.data.shape
dtlx = data.extent[0]
dtly = data.extent[-1]
xrange = dtlx+data.xdim/2.+np.arange(dcols)*data.xdim
yrange = dtly-data.ydim/2.-np.arange(drows)*data.ydim
xdat, ydat = np.meshgrid(xrange, yrange)
xdat = xdat.flatten()
ydat = ydat.flatten()
igrf_F = altgrid * 0
igrf_I = altgrid * 0
igrf_D = altgrid * 0
# Pick model
yrmax = np.array(yrmax)
modelI = sum(yrmax < sdate)
igdgc = 1
if maxyr < sdate < maxyr+1:
self.reportback('Warning: The date ' + str(sdate) +
' is out of range,')
self.reportback('but still within one year of model expiration'
' date.')
self.reportback('An updated model file is available before 1.1.' +
str(maxyr))
if max2[modelI] == 0:
self.getshc(modbuff, 1, irec_pos[modelI], max1[modelI], 0)
self.getshc(modbuff, 1, irec_pos[modelI+1], max1[modelI+1], 1)
nmax = self.interpsh(sdate, yrmin[modelI], max1[modelI],
yrmin[modelI+1], max1[modelI+1], 2)
nmax = self.interpsh(sdate+1, yrmin[modelI], max1[modelI],
yrmin[modelI+1], max1[modelI+1], 3)
else:
self.getshc(modbuff, 1, irec_pos[modelI], max1[modelI], 0)
self.getshc(modbuff, 0, irec_pos[modelI], max2[modelI], 1)
nmax = self.extrapsh(sdate, epoch[modelI], max1[modelI],
max2[modelI], 2)
nmax = self.extrapsh(sdate+1, epoch[modelI], max1[modelI],
max2[modelI], 3)
progress = 0
maxlen = xdat.size
alli = []
alld = []
allf = []
for i in self.piter(range(maxlen)):
if igrf_F.mask[i]:
continue
tmp = int(i*100/maxlen)
if tmp > progress:
progress = tmp
longitude, latitude, _ = self.ctrans.TransformPoint(xdat[i],
ydat[i])
alt = altgrid[i]
# Do the first calculations
self.shval3(igdgc, latitude, longitude, alt, nmax, 3)
self.dihf(3)
igrf_F[i] = self.f
igrf_I[i] = np.rad2deg(self.i)
igrf_D[i] = np.rad2deg(self.d)
alli.append(self.i)
alld.append(self.d)
allf.append(self.f)
fmean = np.mean(allf)
imean = np.rad2deg(np.mean(alli))
dmean = np.rad2deg(np.mean(alld))
bname = 'Magnetic Data: IGRF Corrected '
bname = bname + 'F:{0:.2f} I:{1:.2f} D:{2:.2f}'
bname = bname.format(fmean, imean, dmean)
self.outdata['Raster'] = copy.deepcopy(self.indata['Raster'])
igrf_F = np.ma.array(igrf_F)
igrf_F.shape = data.data.shape
igrf_F.mask = np.ma.getmaskarray(data.data)
igrf_I = np.ma.array(igrf_I)
igrf_I.shape = data.data.shape
igrf_I.mask = np.ma.getmaskarray(data.data)
igrf_D = np.ma.array(igrf_D)
igrf_D.shape = data.data.shape
igrf_D.mask = np.ma.getmaskarray(data.data)
self.outdata['Raster'].append(copy.deepcopy(data))
self.outdata['Raster'][-1].data = igrf_F
self.outdata['Raster'][-1].dataid = 'IGRF'
self.outdata['Raster'].append(copy.deepcopy(data))
self.outdata['Raster'][-1].data = igrf_I
self.outdata['Raster'][-1].dataid = 'Inclinations'
self.outdata['Raster'].append(copy.deepcopy(data))
self.outdata['Raster'][-1].data = igrf_D
self.outdata['Raster'][-1].dataid = 'Declinations'
self.outdata['Raster'].append(copy.deepcopy(maggrid))
self.outdata['Raster'][-1].data -= igrf_F
self.outdata['Raster'][-1].dataid = bname
self.reportback('')
self.reportback('Mean Values in Calculation')
self.reportback('=============================')
self.reportback('Total Intensity: {0:.2f}'.format(fmean))
self.reportback('Inclination: {0:.2f}'.format(imean))
self.reportback('Declination: {0:.2f}'.format(dmean))
self.reportback('')
self.reportback('Calculation: Completed', True)
return True
def export_gdal(self, dat, drv):
"""
Export to GDAL format
Parameters
----------
dat : PyGMI raster Data
dataset to export
drv : str
name of the GDAL driver to use
Returns
-------
None.
"""
data = merge(dat)
driver = gdal.GetDriverByName(drv)
dtype = data[0].data.dtype
if dtype == np.uint8:
fmt = gdal.GDT_Byte
elif dtype == np.int32:
fmt = gdal.GDT_Int32
elif dtype == np.float64:
fmt = gdal.GDT_Float64
else:
fmt = gdal.GDT_Float32
tmp = self.ifile.rpartition('.')
if drv == 'GTiff':
tmpfile = tmp[0] + '.tif'
elif drv == 'EHdr':
fmt = gdal.GDT_Float32
dtype = np.float32
tmpfile = tmp[0] + '.bil'
elif drv == 'GSBG':
tmpfile = tmp[0] + '.grd'
fmt = gdal.GDT_Float32
dtype = np.float32
elif drv == 'SAGA':
tmpfile = tmp[0] + '.sdat'
elif drv == 'HFA':
tmpfile = tmp[0] + '.img'
else: # ENVI and ER Mapper
tmpfile = tmp[0]
drows, dcols = data[0].data.shape
if drv == 'GTiff' and dtype == np.uint8:
out = driver.Create(tmpfile,
int(dcols),
int(drows),
len(data),
fmt,
options=['COMPRESS=NONE', 'TFW=YES'])
elif drv == 'ERS' and 'Cape / TM' in data[0].wkt:
tmp = data[0].wkt.split('TM')[1][:2]
out = driver.Create(
tmpfile,
int(dcols),
int(drows),
len(data),
fmt,
options=['PROJ=STMLO' + tmp, 'DATUM=CAPE', 'UNITS=METERS'])
elif drv == 'ERS' and 'Hartebeesthoek94 / TM' in data[0].wkt:
tmp = data[0].wkt.split('TM')[1][:2]
out = driver.Create(
tmpfile,
int(dcols),
int(drows),
len(data),
fmt,
options=['PROJ=STMLO' + tmp, 'DATUM=WGS84', 'UNITS=METERS'])
else:
out = driver.Create(tmpfile, int(dcols), int(drows), len(data),
fmt)
out.SetGeoTransform(data[0].get_gtr())
out.SetProjection(data[0].wkt)
for i, datai in enumerate(data):
rtmp = out.GetRasterBand(i + 1)
rtmp.SetDescription(datai.dataid)
dtmp = np.ma.array(datai.data).astype(dtype)
dtmp.set_fill_value(datai.nullvalue)
dtmp = dtmp.filled()
if dtype == np.uint8:
datai.nullvalue = int(datai.nullvalue)
rtmp.SetNoDataValue(datai.nullvalue)
rtmp.WriteArray(dtmp)
rtmp.GetStatistics(False, True)
out = None # Close File
if drv == 'ENVI':
with open(tmpfile + '.hdr', 'a') as myfile:
myfile.write('data ignore value = ' + str(data[0].nullvalue))
def settings(self):
""" Settings """
localdict = {}
bandsall = []
self.bands = {}
self.bands['all data'] = 'iall'
self.combobox.clear()
self.combobox.addItem('all data')
if 'Cluster' in self.indata:
intype = 'Cluster'
elif 'Raster' in self.indata:
intype = 'Raster'
else:
self.parent.showprocesslog('No raster data')
return
indata = dataprep.merge(self.indata[intype])
for j, i in enumerate(indata):
self.combobox.addItem(i.dataid)
self.bands[i.dataid] = 'i' + str(j)
bandsall.append(i.data)
localdict['i' + str(j)] = i.data
localdict['iall'] = np.ma.array(bandsall)
temp = self.exec_()
if temp == 0:
return
equation = self.textbrowser.toPlainText()
if equation == '':
return
neweq = self.eq_fix(indata, equation)
try:
findat = ne.evaluate(neweq, localdict)
except Exception:
QtWidgets.QMessageBox.warning(
self.parent, 'Error',
' Nothing processed! Your equation most likely had an error.',
QtWidgets.QMessageBox.Ok, QtWidgets.QMessageBox.Ok)
return
outdata = []
if np.size(findat) == 1:
QtWidgets.QMessageBox.warning(
self.parent, 'Warning',
' Nothing processed! Your equation outputs a single ' +
'value instead of a minimum of one band.',
QtWidgets.QMessageBox.Ok, QtWidgets.QMessageBox.Ok)
return
elif len(findat.shape) == 2:
findat.shape = (1, findat.shape[0], findat.shape[1])
for i, findati in enumerate(findat):
mask = np.ma.getmaskarray(indata[i].data)
findati[mask] = indata[i].nullvalue
outdata.append(copy.copy(indata[i]))
outdata[-1].data = np.ma.masked_equal(findati, indata[i].nullvalue)
# This is needed to get rid of bad, unmasked values etc.
for i, outdatai in enumerate(outdata):
outdatai.data.set_fill_value(indata[i].nullvalue)
outdatai.data = np.ma.fix_invalid(outdatai.data)
if len(outdata) == 1:
outdata[0].dataid = equation
self.outdata[intype] = outdata
return True
def settings(self, equation=None):
"""
Entry point into item.
Parameters
----------
equation : str, optional
Equation submitted (for testing). The default is None.
Returns
-------
bool
True if successful, False otherwise.
"""
localdict = {}
bandsall = []
self.bands = {}
self.bands['all data'] = 'iall'
self.combobox.clear()
self.combobox.addItem('all data')
if 'Cluster' in self.indata:
intype = 'Cluster'
elif 'Raster' in self.indata:
intype = 'Raster'
else:
print('No raster data')
return False
indata = dataprep.merge(self.indata[intype])
for j, i in enumerate(indata):
self.combobox.addItem(i.dataid)
self.bands[i.dataid] = 'i' + str(j)
bandsall.append(i.data)
localdict['i' + str(j)] = i.data
localdict_list = list(localdict.keys())
localdict['iall'] = np.ma.array(bandsall)
if equation is None:
temp = self.exec_()
if temp == 0:
return False
equation = self.textbrowser.toPlainText()
if equation == '':
return False
usedbands = []
for i in localdict_list:
if i in equation:
usedbands.append(i)
mask = None
for i in usedbands:
if mask is None:
mask = localdict[i].mask
else:
mask = np.logical_or(mask, localdict[i].mask)
neweq = self.eq_fix(indata, equation)
try:
findat = ne.evaluate(neweq, localdict)
except Exception:
QtWidgets.QMessageBox.warning(
self.parent, 'Error',
' Nothing processed! Your equation most likely had an error.',
QtWidgets.QMessageBox.Ok)
return False
outdata = []
if np.size(findat) == 1:
QtWidgets.QMessageBox.warning(
self.parent, 'Warning',
' Nothing processed! Your equation outputs a single ' +
'value instead of a minimum of one band.',
QtWidgets.QMessageBox.Ok)
return False
if len(findat.shape) == 2:
findat.shape = (1, findat.shape[0], findat.shape[1])
for i, findati in enumerate(findat):
findati[mask] = indata[i].nullvalue
outdata.append(copy.copy(indata[i]))
outdata[-1].data = np.ma.masked_equal(findati, indata[i].nullvalue)
outdata[-1].nullvalue = indata[i].nullvalue
# This is needed to get rid of bad, unmasked values etc.
for i, outdatai in enumerate(outdata):
outdatai.data.set_fill_value(indata[i].nullvalue)
outdatai.data = np.ma.fix_invalid(outdatai.data)
if len(outdata) == 1:
outdata[0].dataid = equation
self.outdata[intype] = outdata
# breakpoint()
return True
def settings(self):
"""
Settings Dialog. This is the main entrypoint into this routine. It also
contains the main IGRF code.
"""
# Variable declaration
# Control variables
self.proj.set_current(self.indata['Raster'][0].wkt)
data = dp.merge(self.indata['Raster'])
self.combobox_dtm.clear()
self.combobox_mag.clear()
for i in data:
self.combobox_dtm.addItem(i.dataid)
self.combobox_mag.addItem(i.dataid)
tmp = self.exec_()
if tmp == 1:
self.acceptall()
tmp = True
else:
return False
mdf = open(__file__.rpartition('\\')[0] + '\\IGRF11.cof')
modbuff = mdf.readlines()
fileline = -1 # First line will be 1
model = []
epoch = []
max1 = []
max2 = []
max3 = []
yrmin = []
yrmax = []
altmin = []
altmax = []
irec_pos = []
# First model will be 0
for i in modbuff:
fileline += 1 # On new line
if i[:3] == ' ':
i2 = i.split()
model.append(i2[0])
epoch.append(float(i2[1]))
max1.append(int(i2[2]))
max2.append(int(i2[3]))
max3.append(int(i2[4]))
yrmin.append(float(i2[5]))
yrmax.append(float(i2[6]))
altmin.append(float(i2[7]))
altmax.append(float(i2[8]))
irec_pos.append(fileline)
i = self.combobox_mag.currentIndex()
maggrid = data[i]
i = self.combobox_dtm.currentIndex()
data = data[i]
altgrid = data.data.flatten() * 0.001 # in km
maxyr = max(yrmax)
sdate = self.dateedit.date()
sdate = sdate.year() + sdate.dayOfYear() / sdate.daysInYear()
alt = self.dsb_alt.value()
xrange = data.tlx + data.xdim / 2. + np.arange(data.cols) * data.xdim
yrange = data.tly - data.ydim / 2. - np.arange(data.rows) * data.ydim
xdat, ydat = np.meshgrid(xrange, yrange)
xdat = xdat.flatten()
ydat = ydat.flatten()
igrf_F = altgrid * 0
# Pick model
yrmax = np.array(yrmax)
modelI = sum(yrmax < sdate)
igdgc = 1
if (sdate > maxyr) and (sdate < maxyr + 1):
self.reportback("Warning: The date " + str(sdate) +
" is out of range,")
self.reportback("but still within one year of model expiration"
" date.")
self.reportback("An updated model file is available before 1.1." +
str(maxyr))
if max2[modelI] == 0:
self.getshc(modbuff, 1, irec_pos[modelI], max1[modelI], 0)
self.getshc(modbuff, 1, irec_pos[modelI + 1], max1[modelI + 1], 1)
nmax = self.interpsh(sdate, yrmin[modelI], max1[modelI],
yrmin[modelI + 1], max1[modelI + 1], 2)
nmax = self.interpsh(sdate + 1, yrmin[modelI], max1[modelI],
yrmin[modelI + 1], max1[modelI + 1], 3)
else:
self.getshc(modbuff, 1, irec_pos[modelI], max1[modelI], 0)
self.getshc(modbuff, 0, irec_pos[modelI], max2[modelI], 1)
nmax = self.extrapsh(sdate, epoch[modelI], max1[modelI],
max2[modelI], 2)
nmax = self.extrapsh(sdate + 1, epoch[modelI], max1[modelI],
max2[modelI], 3)
progress = 0
maxlen = xdat.size
for i in self.pbar.iter(range(maxlen)):
if igrf_F.mask[i] == True:
continue
tmp = int(i * 100 / maxlen)
if tmp > progress:
progress = tmp
longitude, latitude, _ = self.ctrans.TransformPoint(
xdat[i], ydat[i])
alt = altgrid[i]
# Do the first calculations
self.shval3(igdgc, latitude, longitude, alt, nmax, 3)
self.dihf(3)
igrf_F[i] = self.f
self.outdata['Raster'] = copy.deepcopy(self.indata['Raster'])
igrf_F = np.ma.array(igrf_F)
igrf_F.shape = data.data.shape
igrf_F.mask = np.ma.getmaskarray(data.data)
self.outdata['Raster'].append(copy.deepcopy(data))
self.outdata['Raster'][-1].data = igrf_F
self.outdata['Raster'][-1].dataid = 'IGRF'
self.outdata['Raster'].append(copy.deepcopy(maggrid))
self.outdata['Raster'][-1].data -= igrf_F
self.outdata['Raster'][-1].dataid = 'Magnetic Data: IGRF Corrected'
self.reportback('')
self.reportback('Latest Values in Calculation')
self.reportback('=============================')
self.reportback('Total Intensity: ' + str(self.f))
self.reportback('Inclination: ' + str(np.rad2deg(self.i)))
self.reportback('Declination: ' + str(np.rad2deg(self.d)))
self.reportback('')
self.reportback('Calculation: Completed', True)
return True
def settings(self):
"""
Settings Dialog. This is the main entrypoint into this routine. It also
contains the main IGRF code.
"""
# Variable declaration
# Control variables
self.proj.set_current(self.indata['Raster'][0].wkt)
data = dp.merge(self.indata['Raster'])
self.combobox_dtm.clear()
self.combobox_mag.clear()
for i in data:
self.combobox_dtm.addItem(i.dataid)
self.combobox_mag.addItem(i.dataid)
tmp = self.exec_()
if tmp == 1:
self.acceptall()
tmp = True
else:
return False
mdf = open(os.path.join(os.path.dirname(__file__), 'IGRF12.cof'))
modbuff = mdf.readlines()
fileline = -1 # First line will be 1
model = []
epoch = []
max1 = []
max2 = []
max3 = []
yrmin = []
yrmax = []
altmin = []
altmax = []
irec_pos = []
# First model will be 0
for i in modbuff:
fileline += 1 # On new line
if i[:3] == ' ':
i2 = i.split()
model.append(i2[0])
epoch.append(float(i2[1]))
max1.append(int(i2[2]))
max2.append(int(i2[3]))
max3.append(int(i2[4]))
yrmin.append(float(i2[5]))
yrmax.append(float(i2[6]))
altmin.append(float(i2[7]))
altmax.append(float(i2[8]))
irec_pos.append(fileline)
i = self.combobox_mag.currentIndex()
maggrid = data[i]
i = self.combobox_dtm.currentIndex()
data = data[i]
altgrid = data.data.flatten() * 0.001 # in km
maxyr = max(yrmax)
sdate = self.dateedit.date()
sdate = sdate.year()+sdate.dayOfYear()/sdate.daysInYear()
alt = self.dsb_alt.value()
xrange = data.tlx+data.xdim/2.+np.arange(data.cols)*data.xdim
yrange = data.tly-data.ydim/2.-np.arange(data.rows)*data.ydim
xdat, ydat = np.meshgrid(xrange, yrange)
xdat = xdat.flatten()
ydat = ydat.flatten()
igrf_F = altgrid * 0
# Pick model
yrmax = np.array(yrmax)
modelI = sum(yrmax < sdate)
igdgc = 1
if (sdate > maxyr) and (sdate < maxyr+1):
self.reportback("Warning: The date " + str(sdate) +
" is out of range,")
self.reportback("but still within one year of model expiration"
" date.")
self.reportback("An updated model file is available before 1.1." +
str(maxyr))
if max2[modelI] == 0:
self.getshc(modbuff, 1, irec_pos[modelI], max1[modelI], 0)
self.getshc(modbuff, 1, irec_pos[modelI+1], max1[modelI+1], 1)
nmax = self.interpsh(sdate, yrmin[modelI], max1[modelI],
yrmin[modelI+1], max1[modelI+1], 2)
nmax = self.interpsh(sdate+1, yrmin[modelI], max1[modelI],
yrmin[modelI+1], max1[modelI+1], 3)
else:
self.getshc(modbuff, 1, irec_pos[modelI], max1[modelI], 0)
self.getshc(modbuff, 0, irec_pos[modelI], max2[modelI], 1)
nmax = self.extrapsh(sdate, epoch[modelI], max1[modelI],
max2[modelI], 2)
nmax = self.extrapsh(sdate+1, epoch[modelI], max1[modelI],
max2[modelI], 3)
progress = 0
maxlen = xdat.size
for i in self.pbar.iter(range(maxlen)):
if igrf_F.mask[i] == True:
continue
tmp = int(i*100/maxlen)
if tmp > progress:
progress = tmp
longitude, latitude, _ = self.ctrans.TransformPoint(xdat[i],
ydat[i])
alt = altgrid[i]
# Do the first calculations
self.shval3(igdgc, latitude, longitude, alt, nmax, 3)
self.dihf(3)
igrf_F[i] = self.f
self.outdata['Raster'] = copy.deepcopy(self.indata['Raster'])
igrf_F = np.ma.array(igrf_F)
igrf_F.shape = data.data.shape
igrf_F.mask = np.ma.getmaskarray(data.data)
self.outdata['Raster'].append(copy.deepcopy(data))
self.outdata['Raster'][-1].data = igrf_F
self.outdata['Raster'][-1].dataid = 'IGRF'
self.outdata['Raster'].append(copy.deepcopy(maggrid))
self.outdata['Raster'][-1].data -= igrf_F
self.outdata['Raster'][-1].dataid = 'Magnetic Data: IGRF Corrected'
self.reportback('')
self.reportback('Latest Values in Calculation')
self.reportback('=============================')
self.reportback('Total Intensity: '+str(self.f))
self.reportback('Inclination: '+str(np.rad2deg(self.i)))
self.reportback('Declination: '+str(np.rad2deg(self.d)))
self.reportback('')
self.reportback('Calculation: Completed', True)
return True
def export_gdal(self, dat, drv):
"""
Export to GDAL format
Parameters
----------
dat : PyGMI raster Data
dataset to export
drv : str
name of the GDAL driver to use
"""
data = merge(dat)
xmin = data[0].tlx
ymax = data[0].tly
driver = gdal.GetDriverByName(drv)
dtype = data[0].data.dtype
if dtype == np.uint8:
fmt = gdal.GDT_Byte
elif dtype == np.int32:
fmt = gdal.GDT_Int32
elif dtype == np.float64:
fmt = gdal.GDT_Float64
else:
fmt = gdal.GDT_Float32
tmp = self.ifile.rpartition('.')
if drv == 'GTiff':
tmpfile = tmp[0] + '.tif'
elif drv == 'EHdr':
fmt = gdal.GDT_Float32
dtype = np.float32
tmpfile = tmp[0] + '.bil'
else:
tmpfile = tmp[0]
if drv == 'GTiff' and dtype == np.uint8:
out = driver.Create(tmpfile, int(data[0].cols), int(data[0].rows),
len(data), fmt, options=['COMPRESS=NONE',
'TFW=YES'])
elif drv == 'ERS' and 'Cape / TM' in data[0].wkt:
tmp = data[0].wkt.split('TM')[1][:2]
out = driver.Create(tmpfile, int(data[0].cols), int(data[0].rows),
len(data), fmt,
options=['PROJ=STMLO'+tmp, 'DATUM=CAPE',
'UNITS=METERS'])
elif drv == 'ERS' and 'Hartebeesthoek94 / TM' in data[0].wkt:
tmp = data[0].wkt.split('TM')[1][:2]
out = driver.Create(tmpfile, int(data[0].cols), int(data[0].rows),
len(data), fmt,
options=['PROJ=STMLO'+tmp, 'DATUM=WGS84',
'UNITS=METERS'])
else:
out = driver.Create(tmpfile, int(data[0].cols), int(data[0].rows),
len(data), fmt)
out.SetGeoTransform([xmin, data[0].xdim, 0, ymax, 0, -data[0].ydim])
out.SetProjection(data[0].wkt)
for i, datai in enumerate(data):
rtmp = out.GetRasterBand(i+1)
rtmp.SetDescription(datai.dataid)
dtmp = np.ma.array(datai.data).astype(dtype)
# This section tries to overcome null values with round off error
# in 32-bit numbers.
if dtype == np.float32:
datai.nullvalue = np.float64(np.float32(datai.nullvalue))
if datai.data.min() > -1e+10:
datai.nullvalue = np.float64(np.float32(-1e+10))
elif datai.data.max() < 1e+10:
datai.nullvalue = np.float64(np.float32(1e+10))
elif dtype == np.float or dtype == np.float64:
datai.nullvalue = np.float64(dtmp.fill_value)
elif dtype == np.uint8:
datai.nullvalue = 0 # specify 0, since fill value is 999999
elif dtype == np.int32:
datai.nullvalue = np.uint32(dtmp.fill_value)
dtmp.set_fill_value(datai.nullvalue)
dtmp = dtmp.filled()
if dtype == np.uint8:
datai.nullvalue = int(datai.nullvalue)
if drv != 'GTiff':
rtmp.SetNoDataValue(datai.nullvalue)
elif len(data) == 1:
rtmp.SetNoDataValue(datai.nullvalue)
rtmp.WriteArray(dtmp)
out = None # Close File
if drv == 'ENVI':
with open(tmpfile+'.hdr', 'a') as myfile:
myfile.write('data ignore value = ' + str(data[0].nullvalue))
def settings(self):
""" Settings """
localdict = {}
bandsall = []
self.bands = {}
self.bands['all data'] = 'iall'
self.combobox.clear()
self.combobox.addItem('all data')
if 'Cluster' in self.indata:
intype = 'Cluster'
elif 'Raster' in self.indata:
intype = 'Raster'
else:
self.parent.showprocesslog('No raster data')
return
indata = dataprep.merge(self.indata[intype])
for j, i in enumerate(indata):
self.combobox.addItem(i.dataid)
self.bands[i.dataid] = 'i'+str(j)
bandsall.append(i.data)
localdict['i'+str(j)] = i.data
localdict['iall'] = np.ma.array(bandsall)
temp = self.exec_()
if temp == 0:
return
equation = self.textbrowser.toPlainText()
if equation == '':
return
neweq = self.eq_fix(indata, equation)
try:
findat = ne.evaluate(neweq, localdict)
except Exception:
QtWidgets.QMessageBox.warning(
self.parent, 'Error',
' Nothing processed! Your equation most likely had an error.',
QtWidgets.QMessageBox.Ok, QtWidgets.QMessageBox.Ok)
return
outdata = []
if np.size(findat) == 1:
QtWidgets.QMessageBox.warning(
self.parent, 'Warning',
' Nothing processed! Your equation outputs a single ' +
'value instead of a minimum of one band.',
QtWidgets.QMessageBox.Ok, QtWidgets.QMessageBox.Ok)
return
elif len(findat.shape) == 2:
findat.shape = (1, findat.shape[0], findat.shape[1])
for i, findati in enumerate(findat):
mask = np.ma.getmaskarray(indata[i].data)
findati[mask] = indata[i].nullvalue
outdata.append(copy.copy(indata[i]))
outdata[-1].data = np.ma.masked_equal(findati, indata[i].nullvalue)
# This is needed to get rid of bad, unmasked values etc.
for i, outdatai in enumerate(outdata):
outdatai.data.set_fill_value(indata[i].nullvalue)
outdatai.data = np.ma.fix_invalid(outdatai.data)
if len(outdata) == 1:
outdata[0].dataid = equation
self.outdata[intype] = outdata
return True
def export_gdal(self, dat, drv):
"""
Export to GDAL format
Parameters
----------
dat : PyGMI raster Data
dataset to export
drv : str
name of the GDAL driver to use
"""
data = merge(dat)
xmin = data[0].tlx
ymax = data[0].tly
driver = gdal.GetDriverByName(drv)
dtype = data[0].data.dtype
if dtype == np.uint8:
fmt = gdal.GDT_Byte
elif dtype == np.int32:
fmt = gdal.GDT_Int32
elif dtype == np.float64:
fmt = gdal.GDT_Float64
else:
fmt = gdal.GDT_Float32
tmp = self.ifile.rpartition('.')
if drv == 'GTiff':
tmpfile = tmp[0] + '.tif'
elif drv == 'EHdr':
fmt = gdal.GDT_Float32
dtype = np.float32
tmpfile = tmp[0] + '.bil'
else:
tmpfile = tmp[0]
if drv == 'GTiff' and dtype == np.uint8:
out = driver.Create(tmpfile,
int(data[0].cols),
int(data[0].rows),
len(data),
fmt,
options=['COMPRESS=NONE', 'TFW=YES'])
elif drv == 'ERS' and 'Cape / TM' in data[0].wkt:
tmp = data[0].wkt.split('TM')[1][:2]
out = driver.Create(
tmpfile,
int(data[0].cols),
int(data[0].rows),
len(data),
fmt,
options=['PROJ=STMLO' + tmp, 'DATUM=CAPE', 'UNITS=METERS'])
elif drv == 'ERS' and 'Hartebeesthoek94 / TM' in data[0].wkt:
tmp = data[0].wkt.split('TM')[1][:2]
out = driver.Create(
tmpfile,
int(data[0].cols),
int(data[0].rows),
len(data),
fmt,
options=['PROJ=STMLO' + tmp, 'DATUM=WGS84', 'UNITS=METERS'])
else:
out = driver.Create(tmpfile, int(data[0].cols), int(data[0].rows),
len(data), fmt)
out.SetGeoTransform([xmin, data[0].xdim, 0, ymax, 0, -data[0].ydim])
out.SetProjection(data[0].wkt)
for i, datai in enumerate(data):
rtmp = out.GetRasterBand(i + 1)
rtmp.SetDescription(datai.dataid)
dtmp = np.ma.array(datai.data).astype(dtype)
# This section tries to overcome null values with round off error
# in 32-bit numbers.
if dtype == np.float32:
datai.nullvalue = np.float64(np.float32(datai.nullvalue))
if datai.data.min() > -1e+10:
datai.nullvalue = np.float64(np.float32(-1e+10))
elif datai.data.max() < 1e+10:
datai.nullvalue = np.float64(np.float32(1e+10))
elif dtype == np.float or dtype == np.float64:
datai.nullvalue = np.float64(dtmp.fill_value)
elif dtype == np.uint8:
datai.nullvalue = 0 # specify 0, since fill value is 999999
elif dtype == np.int32:
datai.nullvalue = np.uint32(dtmp.fill_value)
dtmp.set_fill_value(datai.nullvalue)
dtmp = dtmp.filled()
if dtype == np.uint8:
datai.nullvalue = int(datai.nullvalue)
if drv != 'GTiff':
rtmp.SetNoDataValue(datai.nullvalue)
elif len(data) == 1:
rtmp.SetNoDataValue(datai.nullvalue)
rtmp.WriteArray(dtmp)
out = None # Close File
if drv == 'ENVI':
with open(tmpfile + '.hdr', 'a') as myfile:
myfile.write('data ignore value = ' + str(data[0].nullvalue))
