def RequestData(self, request, inInfo, outInfo):
logger.info("Loading waveform data...")
start_time = time.time()
output = dsa.WrapDataObject(vtkTable.GetData(outInfo))
if (self._filename is not None and self._subfile is not None
and len(self.mode_names) > 0):
with h5py.File(self._filename, "r") as f:
strain = f[self._subfile]
t = strain["Y_l2_m2.dat"][:, 0]
col_time = vtknp.numpy_to_vtk(t, deep=False)
col_time.SetName("Time")
output.AddColumn(col_time)
for mode_name in self.mode_names:
logger.debug(f"Reading mode '{mode_name}'...")
col_mode = vtknp.numpy_to_vtk(strain[mode_name +
".dat"][:, 1:],
deep=False)
col_mode.SetName(mode_name)
output.AddColumn(col_mode)
logger.info(
f"Waveform data loaded in {time.time() - start_time:.3f}s.")
return 1
def RequestData(self, request, inInfoVec, outInfoVec):
from vtkmodules.vtkCommonDataModel import vtkTable
from vtkmodules.numpy_interface import dataset_adapter as dsa
table = dsa.WrapDataObject(vtkTable.GetData(inInfoVec[0], 0))
kwargs = {}
for aname in table.RowData.keys():
kwargs[aname] = table.RowData[aname]
import numpy
numpy.savez_compressed(self._filename, **kwargs)
return 1
def RequestData(self, request, inInfoVec, outInfoVec):
from vtkmodules.vtkCommonDataModel import vtkTable
from vtkmodules.numpy_interface import dataset_adapter as dsa
data_time = self._get_update_time(outInfoVec.GetInformationObject(0))
raw_data = self._get_raw_data(data_time)
output = dsa.WrapDataObject(vtkTable.GetData(outInfoVec, 0))
for name in raw_data.dtype.names:
if self._arrayselection.ArrayIsEnabled(name):
output.RowData.append(raw_data[name], name)
if data_time is not None:
output.GetInformation().Set(output.DATA_TIME_STEP(), data_time)
return 1
def RequestData(self, request, inInfoVec, outInfoVec):
from vtkmodules.vtkCommonDataModel import vtkTable
from vtk.util import numpy_support
from vtk import vtkPolyData, vtkPoints, vtkCellArray, vtkFloatArray, VTK_FLOAT
import pandas as pd
import numpy as np
import lasio
import math
import time
t0 = time.time()
las = lasio.read(self._filename)
# DEPTH is index
df_curves = las.df()
headers = []
for (section, items) in las.sections.items():
if items is None or items in ('',[]):
continue
if isinstance(items, (str,unicode)):
headers.append((section,'','',items,''))
elif isinstance(items, (list)):
for item in items:
headers.append((section,item['mnemonic'],item['unit'],item['value'],item['descr']))
else:
print ("Unknown LAS header section type", type(items), iyems)
df_header = pd.DataFrame(headers, columns=('Section','Mnemonic','Unit','Value','Description'))
vtk_arrays = _NcubeDataFrameToVTKArrays(df_header)
vtk_table_header = vtkTable()
for vtk_arr in vtk_arrays:
vtk_table_header.AddColumn(vtk_arr)
outputHeader = vtkTable.GetData(outInfoVec, 0)
outputHeader.ShallowCopy(vtk_table_header)
# define scale factor by depth units
unit = las.curves[0]['unit']
if unit in ['FT','ft']:
scale = 0.3048
elif unit in ['M','m']:
scale = 1.0
else:
# we can use additional ParaView filter to fix it later
scale = 1.0
print ("Unknown LAS header unit", unit)
# set of vtk arrays with column names
vtk_arrays = _NcubeDataFrameToVTKArrays(df_curves)
# https://github.com/mobigroup/gis-snippets/blob/master/ParaView/ProgrammableFilter/vtkMultiblockDataSet.md
# https://en.wikipedia.org/wiki/Spherical_coordinate_system
# Spherical coordinates (r, θ, φ) as often used in mathematics:
# radial distance r, azimuthal angle θ, and polar angle φ.
theta = 1./2*math.pi - math.pi*self._az/180
phi = math.pi*(90 - self._dip)/180
#print ("theta",theta,"phi",phi)
df_curves['dx'] = np.round(scale*df_curves.index*np.sin(phi)*np.cos(theta),10)
df_curves['dy'] = np.round(scale*df_curves.index*np.sin(phi)*np.sin(theta),10)
df_curves['dz'] = np.round(scale*df_curves.index*np.cos(phi),10)
vtk_polyData = vtkPolyData()
vtk_points = vtkPoints()
vtk_cells = vtkCellArray()
vtk_cells.InsertNextCell(len(df_curves))
for row in df_curves.itertuples(index=False):
pointId = vtk_points.InsertNextPoint(self._x+row.dx, self._y+row.dy, self._z+row.dz)
vtk_cells.InsertCellPoint(pointId)
vtk_polyData.SetPoints(vtk_points)
vtk_polyData.SetLines(vtk_cells)
for vtk_arr in vtk_arrays:
# vtk_polyData.GetCellData().AddArray(vtk_arr)
vtk_polyData.GetPointData().AddArray(vtk_arr)
# vtk_polyData.GetPointData().SetActiveScalars("DEPTH")
# print (df_curves['DEPTH'].dtype)
# vtk_array = numpy_support.numpy_to_vtk(num_array=df_curves['DEPTH'].values, deep=True, array_type=VTK_FLOAT)
# vtk_array.SetName("DEPTH")
# vtk_polyData.GetPointData().SetScalars(vtk_array)
outputCurves = vtkPolyData.GetData(outInfoVec, 1)
outputCurves.ShallowCopy(vtk_polyData)
t1 = time.time()
print ("t1-t0", t1-t0)
return 1
