code: def query_array(ncfile, name) -> numpy.ndarray:
      
      variable = query_variable(ncfile, name)
      maskedarray = variable[:]
      fillvalue_ = getattr(variable, '_FillValue', numpy.nan)
      if not numpy.isnan(fillvalue_):
          maskedarray[maskedarray.mask] = numpy.nan
      return maskedarray.data
docs: Return the data of the variable with the given name from the given
      NetCDF file.
  
      The following example shows that |query_array| returns |nan| entries
      to represent missing values even when the respective NetCDF variable
      defines a different fill value:
  
      >>> from hydpy import TestIO
      >>> from hydpy.core.netcdftools import netcdf4
      >>> from hydpy.core import netcdftools
      >>> netcdftools.fillvalue = -999.0
      >>> with TestIO():
      ...     with netcdf4.Dataset('test.nc', 'w') as ncfile:
      ...         netcdftools.create_dimension(ncfile, 'dim1', 5)
      ...         netcdftools.create_variable(ncfile, 'var1', 'f8', ('dim1',))
      ...     ncfile = netcdf4.Dataset('test.nc', 'r')
      >>> netcdftools.query_variable(ncfile, 'var1')[:].data
      array([-999., -999., -999., -999., -999.])
      >>> netcdftools.query_array(ncfile, 'var1')
      array([ nan,  nan,  nan,  nan,  nan])
      >>> import numpy
      >>> netcdftools.fillvalue = numpy.nan