def progressdialog(self, progress):
pdialog = QProgressDialog()
pdialog.setWindowTitle("Progress")
pdialog.setLabelText("Voortgang van importeren:")
pbar = QProgressBar(pdialog)
pbar.setTextVisible(True)
pbar.setValue(progress)
pdialog.setBar(pbar)
pdialog.setMinimumWidth(300)
pdialog.show()
return pdialog, pbar
class Create_model:
def __init__(self, dlg, current_layer):
"""This constructor need Qt Dialog class as dlg and need current layer to execute the algorithm
in current_layer parameter"""
self.layers = current_layer
self.bar = QProgressBar()
self.dlg = dlg
#self.list = []
self.border = []
self.X = []
self.Y = []
self.Z = []
self.faces = []
self.points = []
#self.list_of_all=[]
self.NoData = -3.4028234663852886e+38
'''def iterator(self):
"""Main algorithm to iterate through all the pixels and also to create boundaries"""
self.layer = self.dlg.cmbSelectLayer.currentLayer()
#get the extent of layer
provider = self.layer.dataProvider()
extent = provider.extent()
xmin = extent.xMinimum()
ymax = extent.yMaximum()
rows = self.layer.height()
cols = self.layer.width()
xsize = self.layer.rasterUnitsPerPixelX()
ysize = self.layer.rasterUnitsPerPixelY()
xinit = xmin + xsize / 2
yinit = ymax - ysize / 2
block = provider.block(1, extent, cols, rows)
#iterate the raster to get the values of pixels
k=1
for i in range(rows):
for j in range(cols):
x = xinit + j * xsize
y = yinit
k += 1
if block.value(i, j) == self.NoData:
self.list_of_all.append([i,j,x,y,block.value(i,j)])
elif block.value(i,j)>=self.dlg.dsbDatum.value():
self.list.append([x, y, block.value(i, j)])
self.list_of_all.append([i,j,x,y,block.value(i,j)])
else:
self.list_of_all.append([i,j,x,y,self.NoData])
xinit = xmin + xsize / 2
yinit -= ysize
#get minimal value to stretching method
print(len(self.list_of_all))
height=[]
for searching in self.list:
height.append(searching[2])
self.minimal=min(height)
#iterate the raster to get the boundaries
colrow=[]
rowcol=[]
for pixelo in self.list_of_all:
rowcol.append(pixelo)
if pixelo[1]==j:
colrow.append(rowcol)
rowcol=[]
for pixel in self.list_of_all:
if pixel[4] != self.NoData:
if pixel[0]==0 or pixel[1]==0 or pixel[0]==i or pixel[1]==j:
pixel[4] = float(self.dlg.dsbDatum.value())
self.border.append([pixel[2],pixel[3],pixel[4]])
#self.list = self.border + self.list
else:
wii=pixel[0]
kol=pixel[1]
pixel[4]=float(self.dlg.dsbDatum.value())
condition1 = colrow[wii-1][kol][4]
condition2 = colrow[wii][kol-1][4]
condition3 = colrow[wii+1][kol][4]
condition4 = colrow[wii][kol+1][4]
if condition1> self.NoData or condition2> self.NoData or condition3> self.NoData or condition4 > self.NoData:
if condition1 == self.NoData or condition2== self.NoData or condition3== self.NoData or condition4 == self.NoData:
self.border.append([pixel[2],pixel[3],pixel[4]])
#self.list=self.border+self.list
self.list += self.border
print(len(self.border))
#print(self.list)
print(len(self.list))
return self.list, self.minimal'''
def iterator(self):
#path = iface.activeLayer().source()
path = self.dlg.cmbSelectLayer.currentLayer().source()
data_source = gdal.Open(path)
#extract one band, because we don't need 3d matrix
band = data_source.GetRasterBand(1)
#read matrix as numpy array
raster = band.ReadAsArray().astype(np.float)
#threshold = 222 #poziom odniesienia - wyzsze od 222
threshold = self.dlg.dsbDatum.value()
#change no data to nan value
raster[raster == band.GetNoDataValue()] = np.nan
raster2 = raster[np.logical_not(
np.isnan(raster)
)] #w raster2 nie mam nanow i sa to tylko wartosci wysokosci
(y_index, x_index) = np.nonzero(raster >= threshold)
#get the minimal value to stretching method
self.minimal = np.nanmin(raster)
#To demonstate this compare a.shape to band.XSize and band.YSize
(upper_left_x, x_size, x_rotation, upper_left_y, y_rotation,
y_size) = data_source.GetGeoTransform()
x_coords = x_index * x_size + upper_left_x + (
x_size / 2) #add half the cell size
y_coords = y_index * y_size + upper_left_y + (y_size / 2
) #to centre the point
raster3 = raster2[raster2 >= threshold]
z_coords = np.asarray(raster3).reshape(-1)
entire_matrix = np.stack((x_coords, y_coords, z_coords), axis=-1)
#add outer
bounder = np.pad(raster,
pad_width=1,
mode='constant',
constant_values=np.nan)
bounder_inner = (np.roll(bounder, 1, axis=0) *
np.roll(bounder, -1, axis=0) *
np.roll(bounder, 1, axis=1) *
np.roll(bounder, -1, axis=1) *
np.roll(np.roll(bounder, 1, axis=0), 1, axis=1) *
np.roll(np.roll(bounder, 1, axis=0), -1, axis=1) *
np.roll(np.roll(bounder, -1, axis=0), 1, axis=1) *
np.roll(np.roll(bounder, -1, axis=0), -1, axis=1))
is_inner = (np.isnan(bounder_inner) == False)
b = bounder
b[is_inner] = np.nan
b[~np.isnan(b)] = threshold
boundary_real = b[1:-1, 1:-1]
boundary_real_2 = boundary_real[np.logical_not(
np.isnan(boundary_real))]
#create boundary coordinates
(y_index_boundary,
x_index_boundary) = np.nonzero(boundary_real == threshold)
#print(len(boundary_real_2))
x_coords_boundary = x_index_boundary * x_size + upper_left_x + (
x_size / 2) #add half the cell size
y_coords_boundary = y_index_boundary * y_size + upper_left_y + (
y_size / 2) #to centre the point
z_coords_boundary = np.asarray(boundary_real_2).reshape(-1)
boundary_the_end = np.stack(
(x_coords_boundary, y_coords_boundary, z_coords_boundary), axis=-1)
boundary_the_end = np.repeat(boundary_the_end, 10, axis=0)
self.entire_mat_with_heights = np.concatenate(
(entire_matrix, boundary_the_end))
#entire_mat_with_heights[entire_mat_with_heights[:, [0,1,2]].argsort()]
self.entire_mat_with_heights = self.entire_mat_with_heights[np.argsort(
self.entire_mat_with_heights[:, 2])]
return self.entire_mat_with_heights, self.minimal
def delaunay(self):
"""This is Delaunay algorithm from Scipy lib
This is needed to create vertices and faces which will be going to executed in creating STL model"""
self.x = self.entire_mat_with_heights[:, 0]
self.y = self.entire_mat_with_heights[:, 1]
self.z = self.entire_mat_with_heights[:, 2]
#print(self.x.shape)
self.tri = Delaunay(np.array([self.x, self.y]).T)
for vert in self.tri.simplices:
self.faces.append([vert[0], vert[1], vert[2]])
for i in range(self.x.shape[0]):
self.points.append([self.x[i], self.y[i], self.z[i]])
return self.faces, self.points, self.x, self.y, self.z, self.tri
def saver(self):
""" Create STL model """
# Define the vertices
vertices = np.array(self.points)
# Define the triangles
facess = np.array(self.faces)
# Create the mesh
self.figure = mesh.Mesh(
np.zeros(facess.shape[0], dtype=mesh.Mesh.dtype))
all_percentage = len(facess)
value = self.bar.value()
for i, f in enumerate(facess):
if value < all_percentage:
value = value + 1
self.bar.setValue(value)
else:
self.timer.stop()
for j in range(3):
self.figure.vectors[i][j] = vertices[f[j], :]
filename = self.dlg.lineEdit.text()
self.figure.save(filename)
return self.figure
def create_graph(self):
""" Visualize model by Matplotlib lib"""
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.plot_trisurf(self.x,
self.y,
self.z,
triangles=self.tri.simplices,
cmap=plt.cm.Spectral)
ax.set_title('3D_Graph')
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
plt.show()
def stretching(self):
""" This method stretching the entire model to the given Datum level"""
for cords in self.entire_mat_with_heights:
if cords[2] > self.minimal:
height_stretched = cords[2] - float(self.dlg.dsbDatum.value())
height_stretched = height_stretched * self.dlg.sbStretch.value(
)
height_stretched += float(self.dlg.dsbDatum.value())
cords[2] = height_stretched
return self.entire_mat_with_heights
def loading(self):
""" Loading progress bar """
self.dialog = QProgressDialog()
self.dialog.setWindowTitle("Loading")
self.dialog.setLabelText("That's your progress")
self.bar = QProgressBar()
self.bar.setTextVisible(True)
self.dialog.setBar(self.bar)
self.dialog.setMinimumWidth(300)
self.dialog.show()
self.timer = QTimer()
self.timer.timeout.connect(self.saver)
self.timer.start(1000)
def shape(self, direction):
""" This algorithm convert ShapeFile to the .tif file.
To created that process I used a lot of GDAL processing algorithms
and this gave me possibility to convert the shape to .tif file,
drape them to the correct elevation and merge this new raster to the current main tif """
self.plugin_dir = direction
buffer_distance = self.dlg.dsbBuffer.value()
output_data_type = self.dlg.sbOutputData.value()
output_raster_size_unit = 0
no_data_value = 0
layer2 = self.dlg.cmbSelectShape.currentLayer()
shape_dir = os.path.join(self.plugin_dir, 'TRASH')
layer_ext_cor = self.dlg.cmbSelectLayer.currentLayer()
provider = layer_ext_cor.dataProvider()
extent = provider.extent()
xmin = extent.xMinimum()
ymax = extent.yMaximum()
xmax = extent.xMaximum()
ymin = extent.yMinimum()
cord_sys = layer_ext_cor.crs().authid()
coords = "%f,%f,%f,%f " % (xmin, xmax, ymin,
ymax) + '[' + str(cord_sys) + ']'
rows = layer_ext_cor.height()
cols = layer_ext_cor.width()
set_shp_height = self.dlg.sbHeight.value()
processing.run(
"native:buffer", {
'INPUT': layer2,
'DISTANCE': buffer_distance,
'SEGMENTS': 5,
'END_CAP_STYLE': 0,
'JOIN_STYLE': 0,
'MITER_LIMIT': 2,
'DISSOLVE': False,
'OUTPUT': os.path.join(shape_dir, 'shape_bufor.shp')
}) #### tu poprawic ten dissolve \/ zredukowac ten na dole
processing.run(
"native:dissolve", {
'INPUT': os.path.join(shape_dir, 'shape_bufor.shp'),
'FIELD': [],
'OUTPUT': os.path.join(shape_dir, 'shape_dissolve.shp')
})
processing.run(
"qgis:generatepointspixelcentroidsinsidepolygons", {
'INPUT_RASTER':
self.dlg.cmbSelectLayer.currentLayer().dataProvider().
dataSourceUri(),
'INPUT_VECTOR':
os.path.join(shape_dir, 'shape_dissolve.shp'),
'OUTPUT':
os.path.join(shape_dir, 'shape_points.shp')
})
processing.run(
"native:setzfromraster", {
'INPUT':
os.path.join(shape_dir, 'shape_points.shp'),
'RASTER':
self.dlg.cmbSelectLayer.currentLayer().dataProvider().
dataSourceUri(),
'BAND':
1,
'NODATA':
0,
'SCALE':
1,
'OUTPUT':
os.path.join(shape_dir, 'shape_drape.shp')
})
layer3 = iface.addVectorLayer(
os.path.join(shape_dir, 'shape_drape.shp'), "Shape_Drape", "ogr")
if not layer3:
print("Layer failed to load!")
field_name = "height"
field_namess = [field.name() for field in layer3.fields()]
i = 0
for l in range(100):
i += 1
if field_name in field_namess:
print('Exist')
field_name = field_name + str(i)
continue
else:
print('Doesn\'t Exist')
break
processing.run(
"qgis:fieldcalculator", {
'INPUT': os.path.join(shape_dir, 'shape_drape.shp'),
'FIELD_NAME': field_name,
'FIELD_TYPE': 0,
'FIELD_LENGTH': 10,
'FIELD_PRECISION': 3,
'NEW_FIELD': True,
'FORMULA': 'z($geometry)+' + str(set_shp_height),
'OUTPUT': os.path.join(shape_dir, 'shape_drape_c.shp')
})
processing.run(
"gdal:rasterize", {
'INPUT': os.path.join(shape_dir, 'shape_drape_c.shp'),
'FIELD': field_name,
'BURN': 0,
'UNITS': output_raster_size_unit,
'WIDTH': cols,
'HEIGHT': rows,
'EXTENT': coords,
'NODATA': no_data_value,
'OPTIONS': '',
'DATA_TYPE': output_data_type,
'INIT': None,
'INVERT': False,
'OUTPUT': os.path.join(shape_dir, 'shape_to_raster.tif')
})
iface.addRasterLayer(os.path.join(shape_dir, 'shape_to_raster.tif'),
"Shape_to_Raster")
QgsProject.instance().removeMapLayers([layer3.id()])
processing.run(
"gdal:merge", {
'INPUT': [
self.dlg.cmbSelectLayer.currentLayer().dataProvider().
dataSourceUri(),
os.path.join(shape_dir, 'shape_to_raster.tif')
],
'PCT':
False,
'SEPARATE':
False,
'NODATA_INPUT':
None,
'NODATA_OUTPUT':
None,
'OPTIONS':
'',
'DATA_TYPE':
5,
'OUTPUT':
os.path.join(shape_dir, 'merged.tif')
})
iface.addRasterLayer(os.path.join(shape_dir, 'merged.tif'),
"Raster_With_Shape")
shape_to_raster = QgsProject.instance().mapLayersByName(
'Shape_to_Raster')
QgsProject.instance().removeMapLayers([shape_to_raster[0].id()])