PyQGIS

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已于 2022-05-26 08:38:44 修改

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分类专栏： QGIS 文章标签： python 开发语言

于 2020-05-26 22:31:59 首次发布

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本文档详细介绍了使用PyQGIS进行地图层操作的方法，包括获取地图层名称列表、编辑属性表、添加栅格图层、重投影、创建矢量文件及裁剪栅格图层等关键功能。

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Getting list of layer names using PyQGIS?

from qgis.core import QgsProject
names = [layer.name() for layer in QgsProject.instance().mapLayers().values()]
print(names)

this produces a list of layers in the current project:

['GoogleSat', 'MyPointsLayer', 'Roads', 'House_numbers']

Edit shapefile attibute

layer = iface.activeLayer()
selection = layer.selectedFeatures()
layer.startEditing()
for feature in selection:
  layer.changeAttributeValue(feature.id(), 1, 0)
layer.commitChanges()

Add raster

from qgis.analysis import QgsRasterCalculator, QgsRasterCalculatorEntry
# Add raster 
rasterpath  = r'C:\Users\wgy\Desktop\fire\test\lc08_roi.tif'
bohLayer  = QgsRasterLayer(rasterpath, 'boh')
if not bohLayer.isValid():  print("Layer failed to load!")
QgsProject.instance().addMapLayer(bohLayer) # Load raster layer into canvas if needed
entries = []
ras = QgsRasterCalculatorEntry()
ras.ref = 'boh@1'
ras.raster = bohLayer
ras.bandNumber = 1
entries.append(ras)
outputfile_path = r'C:\Users\wgy\Desktop\fire\test\tmp.tif'
calc = QgsRasterCalculator( 'boh@1 > 10000', outputfile_path, 'GTiff', bohLayer.extent(), bohLayer.width(), bohLayer.height(), entries )
calc.processCalculation()

Do the reproject to a raster data:

rlayer = QgsProject.instance().mapLayersByName('tmp')[0]
parameter = {'INPUT': rlayer,\
    'TARGET_CRS': 'EPSG:32610', \
    'OUTPUT': r'C:/Users/wgy/Desktop/fire/test/tmp1.tif'}
processing.run('qgis:reprojectlayer', parameter)

the tutorial of raster calculator

outLayerName = 'rndbr_tmp'
lyr = QgsProject.instance().mapLayersByName(outLayerName)[0]
QgsProject.instance().removeMapLayer(lyr.id())
layername = 'ca3958812158520171009_20171004_20171105_rdnbr'
dir_path = r'C:\Users\wgy\Desktop\literature\forestFire\postFire\c\Landsat5TMSardinia\camp\DATA\2017\fire_level_tar_files'
lyr = QgsProject.instance().mapLayersByName(layername)[0]
entries = []
outputfile_path = os.path.join(dir_path, 'tiftif.tif')
ras = QgsRasterCalculatorEntry()
ras.ref = layername + '@1'
ras.raster = lyr
ras.bandNumber = 1
entries.append(ras)
calc = QgsRasterCalculator( ras.ref+'>400', outputfile_path, 'GTiff', lyr.extent(), lyr.width(), lyr.height(), entries )
calc.processCalculation()
bohLayer  = QgsRasterLayer(outputfile_path, outLayerName)
if bohLayer.isValid():
    QgsProject.instance().addMapLayer(bohLayer)

open the hdf5 file

import os, gdal
import numpy as np
## List input raster files
os.chdir(r'C:\Users\wgy\Desktop\fire\test\goesrVSmod14a1_cloudMask')
rasterFiles = os.listdir(os.getcwd())
dataset = gdal.Open(rasterFiles[0], gdal.GA_ReadOnly)
# Open raster layer
rlayer = gdal.Open(hdflayer.GetSubDatasets()[0][0], gdal.GA_ReadOnly)
raster_data = rlayer.ReadAsArray(0, 0, rlayer.RasterXSize, rlayer.RasterYSize)
for i in np.arange(raster_data.shape[0]):
    print(np.unique(raster_data[i,:,:]))

#*****************************************************
# read the nc file using netCDF4
import netCDF4
import os
dir_path = r'C:/Users/wgy/Desktop/fire/test/'
input_raster = r'OR_ABI-L1b-RadC-M3C07_G16_s20183121842181_e20183121844565_c20183121845003.nc'
database = netCDF4.Dataset(os.path.join(dir_path, input_raster))
raster = database.variables['Rad'] # temperature variable
raster = raster[:]

#*****************************************************
# read the TIF using rasterio
import rasterio as rio
import numpy as np
dir_path = 'C:/Users/wgy/Desktop/fire/test/'
file_name = 'c07_rad_roi.tif'
raster = rio.open(os.path.join(dir_path, file_name))
data = raster.read(1)
for i in np.arange(data.shape[0]):
    for j in np.arange(data.shape[1]):
        tmp = data[i,j]!=16383
        print('%d'%tmp, end='')
        print(' ', end='')
        if j == data.shape[1]-1:
            print('')

save as a tif file

import gdal, osr, netCDF4, os
import numpy as np
dir_path = r'C:/Users/wgy/Desktop/fire/test/University of Wisconsin Baseline Fit/'
input_raster = 'global_emis_inf10_location.nc'
file_path = dir_path + input_raster
dataset = gdal.Open("NETCDF:{0}:{1}".format(file_path, 'lat'))
band = dataset.GetRasterBand(1)
raster_lat = dataset.ReadAsArray(0, 0, dataset.RasterXSize, dataset.RasterYSize).astype(np.float)
raster_lat = np.swapaxes(raster_lat, 0, 1)
raster_lat = np.flipud(raster_lat)
dataset = gdal.Open("NETCDF:{0}:{1}".format(file_path, 'lon'))
band = dataset.GetRasterBand(1)
raster_lon = dataset.ReadAsArray(0, 0, dataset.RasterXSize, dataset.RasterYSize).astype(np.float)
raster_lon = np.swapaxes(raster_lon, 0, 1)
raster_lon = np.flipud(raster_lon)
input_raster = 'global_emis_inf10_monthFilled_MYD11C3.A2016306.041.nc'
# emis1, emis2, emis3, ..., emis10, emis_flag
file_path = dir_path + input_raster
dataset = netCDF4.Dataset(file_path)
raster_data = dataset.variables['emis1'][:]
raster_data = np.swapaxes(raster_data, 0, 1)
raster_data = np.flipud(raster_data)
outputfile_path = os.path.join(dir_path, 'uw_bf_emis306_01.tif')
driver = gdal.GetDriverByName("GTiff")
dst_ds = driver.Create(outputfile_path,
                       band.YSize,
                       band.XSize,
                       1,
                       band.DataType)
#setting extension of output raster
# top left x, w-e pixel resolution, rotation, top left y, rotation, n-s pixel resolution
geotransform = [0 for _ in np.arange(6)]
geotransform[0] = raster_lon[-1, -1]    # xOrigin
geotransform[1] = 0.05                # pixelWidth
geotransform[3] = raster_lat[0, -1]    # yOrigin
geotransform[5] = 0.05                # pixelHeight
dst_ds.GetRasterBand(1).WriteArray(raster_data)
dst_ds.SetGeoTransform(geotransform)
# setting spatial reference of output raster 
srs = osr.SpatialReference()
srs.ImportFromProj4('+proj=longlat +datum=WGS84 +no_defs')
dst_ds.SetProjection(srs.ExportToWkt())
dst_ds = None  #Close output raster dataset 
dataset = None  #Close main raster dataset

save a tif

import gdal,osr
import numpy as np
import struct
def changeRasterValues(band):
    fmttypes = {'Byte':'B', 'UInt16':'H', 'Int16':'h', 'UInt32':'I', 'Int32':'i', 'Float32':'f', 'Float64':'d'}
    data_type = band.DataType
    BandType = gdal.GetDataTypeName(band.DataType)
    raster = []
    for y in range(band.YSize):
        scanline = band.ReadRaster(0, y, band.XSize, 1, band.XSize, 1, data_type)
        values = struct.unpack(fmttypes[BandType] * band.XSize, scanline)
        raster.append(values)
    raster = [list(item) for item in raster]
    tmp = np.asarray(raster)
    # changing raster values
    for i, item in enumerate(raster):
        for j, value in enumerate(item):
            pass#raster[i][j] = int(raster[i][j] * 1000)
    raster = np.asarray(raster)  #transforming list in array
    return raster

dir_path = r'C:/Users/wgy/Desktop/fire/test/'
input_file = 'c07_rad_wgs84.tif'
dataset = gdal.Open(os.path.join(dir_path, input_file))
band = dataset.GetRasterBand(1)
geotransform = dataset.GetGeoTransform()  # Get raster metadata
outputfile_path = os.path.join(dir_path, 'c07_rad_lat_lon.tif')  # Set name of output raster
# Create gtiff file with rows and columns from parent raster 
driver = gdal.GetDriverByName("GTiff")
raster1 = dataset.ReadAsArray(0, 0, dataset.RasterXSize, dataset.RasterYSize).astype(np.float)
raster = changeRasterValues(band)
dst_ds = driver.Create(outputfile_path, 
                       band.XSize, 
                       band.YSize, 
                       number_band, 
                       band.DataType)
#writting output raster
# coordinates in grid
import rasterio
bounds = rasterio.open(os.path.join(dir_path, input_file)).bounds
lon = np.linspace(bounds[0], bounds[2], band.XSize+1)
lat = np.linspace(bounds[3], bounds[1], band.YSize+1)
latC, lonC = 0.5 * (lat[:-1] + lat[1:]), 0.5 * (lon[:-1] + lon[1:])  # center points
latgrid, longrid = np.meshgrid(latC, lonC)  # make grid
dst_ds.GetRasterBand(1).WriteArray(raster)
#setting extension of output raster
# top left x, w-e pixel resolution, rotation, top left y, rotation, n-s pixel resolution
dst_ds.SetGeoTransform(geotransform)
# setting spatial reference of output raster 
srs = osr.SpatialReference(wkt = prj)  # prj???
dst_ds.SetProjection(srs.ExportToWkt())
dst_ds = None  #Close output raster dataset 
dataset = None  #Close main raster dataset

reprojection

dir_path = r'C:/Users/wgy/Desktop/fire/test/'
input_raster = r'c14_rad.tif'
input_raster = os.path.join(dir_path, input_raster)
output_raster = r"c14_rad_epsg4326.tif"
output_raster = os.path.join(dir_path, output_raster)
setting = 'gdalwarp' + \
          ' ' + '-s_srs EPSG:4326' + \
          ' ' + '-t_srs EPSG:4326' + \
          ' ' + '-r near' + \
          ' ' + '-of GTiff' + \
          ' ' + input_raster + \
          ' ' + output_raster
os.system(setting)

create shp (point)

from qgis.core import QgsFields, QgsFeature
fn = r'C:/Users/wgy/Desktop/fire/test/newpoints.shp'
fn = r'C:\Users\wgy\Desktop\literature\forestFire\火后\c\Landsat5TMSardinia\qinyuan\newpoints.shp'
layerFields = QgsFields()
layerFields.append(QgsField('id', QVariant.Int))
layerFields.append(QgsField('value', QVariant.Double))
layerFields.append(QgsField('name', QVariant.String))
writer = QgsVectorFileWriter(fn, 'UTF-8', layerFields, QgsWkbTypes.Point,\
         QgsCoordinateReferenceSystem('EPSG:26912'), 'ESRI Shapefile')
feat = QgsFeature()
feat.setGeometry(QgsGeometry.fromPointXY(QgsPointXY(455618, 463221)))
feat.setAttributes([1, 1.1, 'name'])
writer.addFeature(feat)
iface.addVectorLayer(fn, 'points', 'ogr')
del(writer)

create shp (polygen)

import numpy as np
from qgis.core import QgsFields, QgsFeature
fn = r'C:\Users\wgy\Desktop\literature\forestFire\火后\c\Landsat5TMSardinia\qinyuan\mask.shp'
layerFields = QgsFields()
layerFields.append(QgsField('id', QVariant.Int))
layerFields.append(QgsField('name', QVariant.String))
writer = QgsVectorFileWriter(fn, 'UTF-8', layerFields, QgsWkbTypes.Point,\
         QgsCoordinateReferenceSystem('EPSG:32649'), 'ESRI Shapefile')

rlayer = iface.setActiveLayer()
width = rlayer.width()
height = rlayer.height()
pixelX = rlayer.rasterUnitsPerPixelX()
pixelY = rlayer.rasterUnitsPerPixelY()
for i in np.arange(width):
    for j in np.arange(height):
        x = 618805.34299999999348074
        y = 4077616.23410000000149012
        x_cur = x + pixelX*i + pixelX/2
        y_cur = y - pixelY*j - pixelY/2
        feat = QgsFeature()
        feat.setGeometry(QgsGeometry.fromPointXY(QgsPointXY(x_cur, y_cur)))
        feat.setAttributes([1, 'roi'])
        writer.addFeature(feat)

iface.addVectorLayer(fn, 'points', 'ogr')
del(writer)

clip raster with a shapefile

import os
import numpy as np
for i in np.arange(1, 12):
    dir_path = r'C:\Users\wgy\Desktop\literature\forestFire\火后\c\Landsat5TMSardinia\qinyuan\post\LC08_L1TP_125035_20190916_20190925_01_T1'
    input_raster = r'LC08_L1TP_125035_20190916_20190925_01_T1_B%d.tif' % i
    input_raster = os.path.join(dir_path, input_raster)
    output_raster = r"LC08_L1TP_125035_20190916_20190925_01_T1_B%d_roi.tif" % i
    output_raster = os.path.join(dir_path, output_raster)
    input_vector = r"roi.shp"
    input_vector = os.path.join(os.path.dirname(os.path.dirname(dir_path)), input_vector)
    if input_raster.split('.')[-1] == 'nc':
        input_raster_tmp = 'NETCDF:"{0}":{1}'.format(input_raster, 'Rad')
    elif input_raster.split('.')[-1] == 'tif':
        input_raster_tmp = '{0}'.format(input_raster)
    
    setting = 'gdalwarp' + \
        ' -of GTiff' + \
        ' -cutline ' + input_vector + \
        ' -cl roi'  + ' -crop_to_cutline' + \
        ' ' + input_raster_tmp + \
        ' ' + output_raster
    
    os.system(setting)

clip raster by mask layer

import os
def clip_raster_by_vector(input_raster, input_vector, output_raster, overwrite=False):
    if overwrite:
        if os.path.isfile(output_raster):
            os.remove(output_raster)
    if not os.path.isfile(input_raster):
        print ("File doesn't exists", input_raster)
        return None
    else:
        if input_raster.split('.')[-1] == 'nc':
            input_raster_tmp = "NETCDF:{0}:{1}".format(input_raster, 'Rad')
        else:
            input_raster_tmp = input_raster
        dataset = gdal.Open(input_raster_tmp)
        band = dataset.GetRasterBand(1)
        data_type = band.DataType
        params = {'INPUT': input_raster,
                  'MASK': input_vector,
                  'NODATA': 0,
                  'ALPHA_BAND': False,
                  'CROP_TO_CUTLINE': True,
                  'KEEP_RESOLUTION': True,
                  'OPTIONS': 'COMPRESS=LZW',
                  'DATA_TYPE': data_type,  # Byte
                  'OUTPUT': output_raster,
                  }
        feedback = qgis.core.QgsProcessingFeedback()
        alg_name = 'gdal:cliprasterbymasklayer'
        result = processing.run(alg_name, params, feedback=feedback)
        return result
dir_path = r'C:/Users/wgy/Desktop/fire/test/'
input_raster = r'OR_ABI-L1b-RadC-M3C07_G16_s20183121842181_e20183121844565_c20183121845003.nc'
input_raster = os.path.join(dir_path, input_raster)
output_raster = r"c07_rad_roi.tif"
output_raster = os.path.join(dir_path, output_raster)
input_vector = r"roi.shp"
input_vector = os.path.join(dir_path, input_vector)
result = clip_raster_by_vector(input_raster, input_vector, output_raster, overwrite=True)
print('result =', result)

临

#***********How to show a cube view of hyperspectral image??*********
from osgeo import gdal
src_filepath='rimData_int.tif'
src_fname = 'file.tif'
dst_fname = src_filepath[:-4]+'_show.tif'
driver = gdal.GetDriverByName('LAN')  #???
sds = gdal.Open(src_filepath)


# # load the data
# result = []
# for i in range(1,225):
#   band = sds.GetRasterBand(1)
#   band1 = band.ReadAsArray()
#   print(i, type(band1), band1.dtype, band1.shape)
#   band1 = np.expand_dims(band1, axis=2)*10000
#   band1 = band1.astype(np.int16)
#   if i==1:
#     result = band1
#   else:
#     result = np.concatenate([result, band1], axis=2)
# print(result.shape)
# geotransform = list(sds.GetGeoTransform())  # Get raster metadata
# prj = sds.GetProjection()
# outputfile_path = os.path.join('rimData_int.tif')  # Set name of output raster  
# # Create gtiff file with rows and columns from parent raster 
# driver = gdal.GetDriverByName("GTiff")
# dst_ds = driver.Create(outputfile_path,
#                     result.shape[1],
#                     result.shape[0],
#                     224,
#                     gdal.GDT_Int16)
# #writting output raster
# for i in range(1,225):
#   dst_ds.GetRasterBand(i).WriteArray(result[:,:,i-1])
# #setting extension of output raster
# # top left x, w-e pixel resolution, rotation, top left y, rotation, n-s pixel resolution
# dst_ds.SetGeoTransform(geotransform)
# # setting spatial reference of output raster 
# srs = osr.SpatialReference(wkt = prj)  # prj???
# dst_ds.SetProjection(srs.ExportToWkt())
# dst_ds = None  #Close output raster dataset 
# assert 1==2


# the following Show errors!!!
dst = driver.CreateCopy(dst_fname, sds)
from spectral import view_cube,open_image,imshow
img = open_image(dst)
view = imshow(img, (29, 19, 9))
#view_cube(img, bands=[29, 19, 9])
dst = None  # close dataset; the file can now be used by other processes
'''