DM_numpy_null_value.py

## @package python.demo.DM_numpy_null_value
# "
# example script showing how to handle null values with numpy dictionary
# 
 
from __future__ import print_function
import sys, random
 
import numpy
from opals import pyDM
 
# create an attribute layout for generating points with the corresponding attributes
lf = pyDM.AddInfoLayoutFactory()
lf.addColumn(pyDM.ColumnType.uint16, "_attr1")
shortLayout = lf.getLayout(clear=False) # shortLayout only contains _attr1
lf.addColumn(pyDM.ColumnType.float_, "_attr2")
layout = lf.getLayout() # layout contains _attr1 and _attr2
 
def create_test_odm(filename):
  # create 10 random points with two attributes:
  #  _attr1 (type: uint16) also set with random values for all points
  #  _attr2 (type: float_) filled with random values for half of the points
  pcount = 10
  print(f"Generate {pcount} random points")
  pts = []
  for i in range(pcount):
    pt = pyDM.Point(layout)
    pt.x = random.uniform(-10, 10)
    pt.y = random.uniform(-10, 10)
    pt.z = random.uniform(-10, 10)
    pt.info().set(0, random.randint(0,5000))   # _attr1 (type: uint16)
    if i % 2:
      pt.info().set(1, random.uniform(0.5, 20))  # _attr2 (type: float_) is filled every second point only
    pts.append(pt)
 
 
  # write points to pyDM 'test.pyDM'
  print("Add points into manager '" + filename + "'")
 
  dm = pyDM.Datamanager.create(filename, False)
  if not dm:
    print("Unable to create ODM '" + odm + "'")
    sys.exit(1)
 
  for pt in pts:
    dm.addPoint(pt)
 
  return dm
 
 
def DM_numpy_null_value(dm):
  queryWin = pyDM.Window(-10, -10, 10, 10) # window
 
  print("case 1: no null values -----------------------------------")
  # [no null values]
  # We know that shortLayout, which only contains _attr1, doesn't have any null values.
  # Hence, there is no need to provide noDataObj
  resultNoNulls = pyDM.NumpyConverter.searchPoint(dm, queryWin, shortLayout, withCoordinates=True)
  resultNoNulls2 = None
  try:
    # since _attr2 is not set for all points an exception will occur. catch it and continue
    resultNoNulls2 = pyDM.NumpyConverter.searchPoint(dm, queryWin, layout, withCoordinates=True)
  except Exception as e:
    print("Exception occurred as expected:", e)
  assert resultNoNulls2 == None # just to make sure that resultNoNulls2 is still none
  print("\tno nulls=", resultNoNulls)
  # [no null values]
 
 
  print("\ncase 2: use no data value ------------------------------")
  # [use no data value]
  # use the minimum of the corresponding data type for all attributes as no data value
  resultNoData1 = pyDM.NumpyConverter.searchPoint(dm, queryWin, layout, withCoordinates=True, noDataObj='min')
  # use 0 as no data value for attr1 and NaN (=Not a Number) for attr2 (only possible for float and double attributes)
  resultNoData2 = pyDM.NumpyConverter.searchPoint(dm, queryWin, layout, withCoordinates=True, noDataObj=[0, numpy.nan])
  print("\tnodata1=", resultNoData1)
  print("\tnodata2=", resultNoData2)
  # [use no data value]
 
 
  print("\ncase 3: use masked arrays ------------------------------")
  # [use masked arrays]
  # use masked arrays for all attributes
  resultMasked1 = pyDM.NumpyConverter.searchPoint(dm, queryWin, layout, withCoordinates=True, noDataObj='mask')
  # use the maximum value as no data for attr1 and a MaskedArray for attr2
  resultMasked2 = pyDM.NumpyConverter.searchPoint(dm, queryWin, layout, withCoordinates=True, noDataObj=['max', 'mask'])
  print("\tmasked1=", resultMasked1)
  print("\tmasked2=", resultMasked2)
  # [use masked arrays]
 
  print("\ncase 4: define value type of output arrays -------------")
  # [define output value type]
  # returns float64/double arrays, as defined by NumPy dtype
  resultType1 = pyDM.NumpyConverter.searchPoint(dm, queryWin, layout, withCoordinates=True, noDataObj=numpy.nan,
                          valueType=numpy.dtype(float))
  # returns float64/double arrays, as defined by pyDM.ColumnType
  resultType2 = pyDM.NumpyConverter.searchPoint(dm, queryWin, layout, withCoordinates=True, noDataObj=numpy.nan,
                          valueType=pyDM.ColumnType.double_)
  print("\tvalueType1=", resultType1)
  print("\tvalueType2=", resultType2)
  # [define output value type]
 
 
 
dm = create_test_odm("test.odm")
 
DM_numpy_null_value(dm)