def SaveMasiveValues(outfilename,fileLst, pos, band=1):
'''
Recibe:
:outfilename: nombre de archivo csv de salida
:fileLst: lista de archivos a procesar
:pos: dict de puntos de observación del tipo
{"Santo Domingo": [-31.117368, -60.883001],...}
:band: banda donde extraer los valores
Escribe en outfilename (formato csv) los valores extraidos por cada
archivo en fileLst para cada punto en pos
'''
header1 = ['filename'] + pos.keys()
header2 = [''] + [str(pos[k][0])+','+str(pos[k][1]) for k in pos.keys()]
with open(outfilename, 'wb') as csvfile:
spamwriter = csv.writer(csvfile, dialect='excel', delimiter=';',
quotechar='|', quoting=csv.QUOTE_MINIMAL)
spamwriter.writerow(header1)
spamwriter.writerow(header2)
for fn in fileLst:
file = rasterIO.opengdalraster(fn)
driver, Nx, Ny, NBand, proj, geo = rasterIO.readrastermeta(file)
lon0,lat0,dlon,dlat = geo[0],geo[3],geo[1],geo[5]
etrMap = rasterIO.readrasterband(file, band)
csvrow = [fn]
for po in pos.keys():
row,col = getRowCol(pos[po][0],pos[po][1],lat0,lon0,dlat,dlon)
csvrow += [GetValidValue(etrMap,row,col,Nx,Ny)]
spamwriter.writerow(csvrow)
def load_band(self):
file_count = self.ui.listWidget_Layers.count()
if file_count < 1:
sys.stderr.write('Error: No input files, open a raster file first!\n')
else:
if self.ui.comboBands.currentText() == 'Band #':
sys.stderr.write('Select which band number to load.\n')
else:
band_num = int(self.ui.comboBands.currentText())
fname = self.ui.listWidget_Layers.currentItem().text()
fname_Str = str(fname)
basename = os.path.basename(fname_Str)
basename = os.path.splitext(basename)
basename = basename[0]
cleaname_a = string.replace(basename, '.', '_')
cleaname = string.replace(cleaname_a, '-', '_')
newname = cleaname+'_'+str(band_num)
rasterpointer = rasterIO.opengdalraster(fname_Str)
global driver, XSize, YSize, proj, geotrans
global bandname
bandname = newname
globals()[bandname] = rasterIO.readrasterband(rasterpointer, band_num)
driver, XSize, YSize, proj, geotrans = rasterIO.readrastermeta(rasterpointer)
self.ui.textEqEdit.insertPlainText(bandname+" ")
sys.stdout.write("Loaded: ")
sys.stdout.write(str(fname_Str))
sys.stdout.write(", band: ")
sys.stdout.write(str(band_num))
sys.stdout.write("\n")
self.ui.textPyout.insertPlainText('# open a file pointer\n')
self.ui.textPyout.insertPlainText('rasterpointer = rasterIO.opengdalraster("%s")\n' %(fname_Str))
self.ui.textPyout.insertPlainText('# read a raster band\n')
self.ui.textPyout.insertPlainText('%s = rasterIO.readrasterband(rasterpointer, %i)\n' %(bandname, band_num))
self.ui.textPyout.insertPlainText('# get file metadata: format, X, Y, projection, geo-parameters\n')
self.ui.textPyout.insertPlainText('driver, XSize, YSize, proj, geotrans = rasterIO.readrastermeta(rasterpointer)\n\n')
def SaveMasiveValues(outfilename, fileLst, pos, band=1):
'''
Recibe:
:outfilename: nombre de archivo csv de salida
:fileLst: lista de archivos a procesar
:pos: dict de puntos de observación del tipo
{"Santo Domingo": [-31.117368, -60.883001],...}
:band: banda donde extraer los valores
Escribe en outfilename (formato csv) los valores extraidos por cada
archivo en fileLst para cada punto en pos
'''
header1 = ['filename'] + pos.keys()
header2 = [''
] + [str(pos[k][0]) + ',' + str(pos[k][1]) for k in pos.keys()]
with open(outfilename, 'wb') as csvfile:
spamwriter = csv.writer(csvfile,
dialect='excel',
delimiter=';',
quotechar='|',
quoting=csv.QUOTE_MINIMAL)
spamwriter.writerow(header1)
spamwriter.writerow(header2)
for fn in fileLst:
file = rasterIO.opengdalraster(fn)
driver, Nx, Ny, NBand, proj, geo = rasterIO.readrastermeta(file)
lon0, lat0, dlon, dlat = geo[0], geo[3], geo[1], geo[5]
etrMap = rasterIO.readrasterband(file, band)
csvrow = [fn]
for po in pos.keys():
row, col = getRowCol(pos[po][0], pos[po][1], lat0, lon0, dlat,
dlon)
csvrow += [GetValidValue(etrMap, row, col, Nx, Ny)]
spamwriter.writerow(csvrow)
def onBandChanged(self, event):
# Reload the image with the band selected
self.data = rasterIO.readrasterband(self.file_pointer,
int(self.m_cmb_band.GetValue()))
self.data = self.data.astype(np.float32)
eval("self.ax.imshow(self.data, cmap = cm." +
self.m_cmb_colormap.GetValue() + ")")
self.m_canvas.draw()
def onOpenFile(self, event):
# Show in status bar and log
self.filename = self.m_btn_file.GetPath()
self.m_txt_log.AppendText("#### Opened File #### \n" + self.filename)
self.m_statusBar.SetStatusText(self.filename)
# Load image with PyRaster
self.file_pointer = rasterIO.opengdalraster(self.filename)
driver, self.XSize, self.YSize, self.NBand, proj_wkt, geo = rasterIO.readrastermeta(
self.file_pointer)
self.lon0, self.lat0, self.dlon, self.dlat = geo[0], geo[3], geo[
1], geo[5]
# Clean band combobox, and load existing bands (Default band: 1)
self.m_cmb_band.Clear()
bands = [str(b) for b in range(1, self.NBand + 1)]
self.m_cmb_band.AppendItems(bands)
self.m_cmb_band.SetValue('1')
# Get selected band
self.data = rasterIO.readrasterband(self.file_pointer,
int(self.m_cmb_band.GetValue()))
self.data = self.data.astype(np.float32)
# Create figure with the colormap selected
self.m_figure.clear()
self.ax = self.m_figure.add_subplot(111)
eval("self.ax.imshow(self.data, cmap = cm." +
self.m_cmb_colormap.GetValue() + ")")
# Latitude and longitude range
max_lat = self.lat0 + self.YSize * self.dlat
max_lon = self.lon0 + self.XSize * self.dlon
# Show and Log figure metadata
sms = "\n+ Metadata \n " + proj_wkt + "\n"
sms += " - Size = " + str(self.YSize) + "," + str(self.XSize) + "\n"
sms += " - Delta latitude = " + str(
self.dlat) + "\n - Delta longitude = " + str(self.dlon) + "\n"
sms += " - Latitude limits: \n"
sms += " from = " + str(self.lat0) + "\n"
sms += " to = " + str(max_lat) + "\n"
sms += " - Longitude limits: \n"
sms += " from = " + str(self.lon0) + "\n"
sms += " to = " + str(max_lon) + "\n"
self.m_txt_log.AppendText(sms)
self.m_txt_log.ShowPosition(self.m_txt_log.GetLastPosition())
# Set axes labels
self.ax.set_xlabel('Col (Lon)')
self.ax.set_ylabel('Row (Lat)')
# Draw figure
self.ax.grid(True)
self.m_canvas.draw()
def onOpenFile( self, event ):
# Show in status bar and log
self.filename = self.m_btn_file.GetPath()
self.m_txt_log.AppendText("#### Opened File #### \n"+self.filename)
self.m_statusBar.SetStatusText(self.filename)
# Load image with PyRaster
self.file_pointer = rasterIO.opengdalraster(self.filename)
driver, self.XSize, self.YSize, self.NBand, proj_wkt, geo = rasterIO.readrastermeta(self.file_pointer)
self.lon0,self.lat0,self.dlon,self.dlat = geo[0],geo[3],geo[1],geo[5]
# Clean band combobox, and load existing bands (Default band: 1)
self.m_cmb_band.Clear()
bands = [str(b) for b in range(1,self.NBand+1)]
self.m_cmb_band.AppendItems(bands)
self.m_cmb_band.SetValue('1')
# Get selected band
self.data = rasterIO.readrasterband(self.file_pointer, int(self.m_cmb_band.GetValue()))
self.data = self.data.astype(np.float32)
# Create figure with the colormap selected
self.m_figure.clear()
self.ax = self.m_figure.add_subplot(111)
eval("self.ax.imshow(self.data, cmap = cm."+self.m_cmb_colormap.GetValue()+")")
# Latitude and longitude range
max_lat = self.lat0 + self.YSize*self.dlat
max_lon = self.lon0 + self.XSize*self.dlon
# Show and Log figure metadata
sms = "\n+ Metadata \n " + proj_wkt +"\n"
sms += " - Size = " + str(self.YSize) + "," + str(self.XSize) + "\n"
sms += " - Delta latitude = " + str(self.dlat) + "\n - Delta longitude = " + str(self.dlon) + "\n"
sms += " - Latitude limits: \n"
sms += " from = "+ str(self.lat0) + "\n"
sms += " to = "+ str(max_lat) + "\n"
sms += " - Longitude limits: \n"
sms += " from = "+ str(self.lon0) + "\n"
sms += " to = "+ str(max_lon) + "\n"
self.m_txt_log.AppendText(sms)
self.m_txt_log.ShowPosition( self.m_txt_log.GetLastPosition())
# Set axes labels
self.ax.set_xlabel('Col (Lon)')
self.ax.set_ylabel('Row (Lat)')
# Draw figure
self.ax.grid(True)
self.m_canvas.draw()
def load_band(self):
file_count = self.ui.listWidget_Layers.count()
if file_count < 1:
sys.stderr.write(
'Error: No input files, open a raster file first!\n')
else:
if self.ui.comboBands.currentText() == 'Band #':
sys.stderr.write('Select which band number to load.\n')
else:
band_num = int(self.ui.comboBands.currentText())
fname = self.ui.listWidget_Layers.currentItem().text()
fname_Str = str(fname)
basename = os.path.basename(fname_Str)
basename = os.path.splitext(basename)
basename = basename[0]
cleaname_a = string.replace(basename, '.', '_')
cleaname = string.replace(cleaname_a, '-', '_')
newname = cleaname + '_' + str(band_num)
rasterpointer = rasterIO.opengdalraster(fname_Str)
global driver, XSize, YSize, proj, geotrans
global bandname
bandname = newname
globals()[bandname] = rasterIO.readrasterband(
rasterpointer, band_num)
driver, XSize, YSize, proj, geotrans = rasterIO.readrastermeta(
rasterpointer)
self.ui.textEqEdit.insertPlainText(bandname + " ")
sys.stdout.write("Loaded: ")
sys.stdout.write(str(fname_Str))
sys.stdout.write(", band: ")
sys.stdout.write(str(band_num))
sys.stdout.write("\n")
self.ui.textPyout.insertPlainText('# open a file pointer\n')
self.ui.textPyout.insertPlainText(
'rasterpointer = rasterIO.opengdalraster("%s")\n' %
(fname_Str))
self.ui.textPyout.insertPlainText('# read a raster band\n')
self.ui.textPyout.insertPlainText(
'%s = rasterIO.readrasterband(rasterpointer, %i)\n' %
(bandname, band_num))
self.ui.textPyout.insertPlainText(
'# get file metadata: format, X, Y, projection, geo-parameters\n'
)
self.ui.textPyout.insertPlainText(
'driver, XSize, YSize, proj, geotrans = rasterIO.readrastermeta(rasterpointer)\n\n'
)
@author: emiliano """ import rasterIO import numpy as np #from mayavi import mlab import matplotlib.pyplot as plt import matplotlib.cm as cm # ruta de la imagen filename_img = '2000073-et.img' file_pointer = rasterIO.opengdalraster(filename_img) driver, XSize, YSize, proj_wkt, geo_t_params = rasterIO.readrastermeta(file_pointer) # en data tengo la matriz que representa la imagen data = rasterIO.readrasterband(file_pointer, 1) data = data.astype(np.float32) # Podria recortarla #data = data[0:500, 1500:2000] #Algunos Otros mapas de color: Greys_r,Blues, hsv plt.imshow(data, cmap = cm.hot) del data plt.show() #mlab.figure(size=(400, 320), bgcolor=(0.16, 0.28, 0.46)) #mlab.surf(data, colormap='hot')#,warp_scale=0.5) #vmin=1200, vmax=1610) ##mlab.view(-5.9, 83, 570, [5.3, 20, 238])
def processfunction(file_list):
# Create a loop for all files in current directory
for file in file_list:
# Check file type (in this case Geotiff)
if file.endswith('.tif'):
# Open a pointer to the file
pointer = rasterIO.opengdalraster(file)
# Read the raster metadata for the new output file
driver, XSize, YSize, proj_wkt, geo_t_params = rasterIO.readrastermeta(pointer)
# Read the first band to a matrix called band_1
band_1 = rasterIO.readrasterband(pointer, 1)
# Read the second band to a matrix called band_2
band_2 =rasterIO.readrasterband(pointer, 2)
# Perform the NDVI calculation and put the results into a new matrix
new_ndvi_band = ((band_2 - band_1) / (band_2 + band_1))
# Get the input file filename without extension and create a new file name
parts =string.split(file)
newname = './'+parts[0]+'_ndvi.tif' # ./filename_ndvi.tif
# Get the EPSG code from well known text projection
epsg = rasterIO.wkt2epsg(proj_wkt)
# Write the NDVI matrix to a new raster file
rasterIO.writerasterband(new_ndvi_band, newname, XSize, YSize, geo_t_params, epsg)
# loop will now go to next file in input list
# Create a run function to accept jobs from queue
def processRun(q, filename):
q.put(processfunc(filename))
# Create the main function
def main(arg=sys.argv):
# Get a list fo files in the current directory (assumed to contain raster data)
file_list = os.listdir(os.getcwd())
# Get the length of the file list
len_flist = len(file_list)
half_len = len_flist / 2
# Create a queue object
q = Queue()
# Create two processes (add more depending on processor availability)
p1 = Process(target=processRun, args=(q, flist[:half_len]))
p2 = Process(target=processRun, args=(q, flist[half_len:]))
# Start processes
p1.start()
p2.start()
# Standard Python script execution/exit handling
if __name__=='__main__':
sys.exit(main())
# Get a list of files in current directory
# Create a loop for all files in current directory
for file in flist:
# Check file type (in this case Geotiff)
if file.endswith('.tif'):
# Open a pointer to the file
pointer = rasterIO.opengdalraster(file)
# Read the raster metadata for the new output file
driver, XSize, YSize, proj_wkt, geo_t_params = rasterIO.readrastermeta(
pointer)
# Read the first band to a matrix called band_1
band_1 = rasterIO.readrasterband(pointer, 1)
# Read the second band to a matrix called band_2
band_2 = rasterIO.readrasterband(pointer, 2)
# Perform the NDVI calculation and put the results into a new matrix
new_ndvi_band = ((band_2 - band_1) / (band_2 + band_1))
# Get the input file filename without extension and create a new file name
parts = string.split(file)
newname = './' + parts[0] + '_ndvi.tif' # ./filename_ndvi.tif
# Get the EPSG code from well known text projection
epsg = rasterIO.wkt2epsg(proj_wkt)
# Write the NDVI matrix to a new raster file
#Read a raster file
# Import the rasterIO module
import rasterIO
# Open a gdal pointer to a file on disk
file_pointer = rasterIO.opengdalraster(
'/path/surface_temperature_kelvin.tif')
# Get the spatial reference information from the image
drive, XSize, YSize, proj_wkt, geo_t_params =
rasterIO.readrastermeta(pointer)
# Read a band from the file to a new matrix in memory,
#the number indicates which band to read.
kelvin_band = rasterIO.readrasterband(file_pointer, 1)
# Get a list of files in current directory
# Create a loop for all files in current directory
for file in flist:
# Check file type (in this case Geotiff)
if file.endswith('.tif'):
# Open a pointer to the file
pointer = rasterIO.opengdalraster(file)
# Read the raster metadata for the new output file
driver, XSize, YSize, proj_wkt, geo_t_params = rasterIO.readrastermeta(pointer)
# Read the first band to a matrix called band_1
band_1 =rasterIO.readrasterband(pointer, 1)
# Read the second band to a matrix called band_2
band_2 = rasterIO.readrasterband(pointer, 2)
# Perform the NDVI calculation and put the results into a new matrix
new_ndvi_band = ((band_2 - band_1) / (band_2 + band_1))
# Get the input file filename without extension and create a new file name
parts = string.split(file)
newname ='./'+parts[0]+'_ndvi.tif' # ./filename_ndvi.tif
# Get the EPSG code from well known text projection
epsg =rasterIO.wkt2epsg(proj_wkt)
# Write the NDVI matrix to a new raster file
rasterIO.writerasterband(new_ndvi_band, newname, XSize, YSize, geo_t_params, epsg)
def onBandChanged( self, event ):
# Reload the image with the band selected
self.data = rasterIO.readrasterband(self.file_pointer, int(self.m_cmb_band.GetValue()))
self.data = self.data.astype(np.float32)
eval("self.ax.imshow(self.data, cmap = cm."+self.m_cmb_colormap.GetValue()+")")
self.m_canvas.draw()
