AnalogWaveform.scaled_data makes an unnecessary copy

Bug Report

Testing with nidaqmx in https://github.com/ni/nidaqmx-python/pull/828 revealed that AnalogWaveform.scaled_data always copies the data array.

Repro or Code Sample

>>> import numpy as np
>>> x = np.linspace(0.0, 5.0, 10, dtype=np.float64)
>>> y = x[::2]
>>> from nitypes.waveform import AnalogWaveform
>>> w = AnalogWaveform(raw_data=y)
>>> w.raw_data.flags
  C_CONTIGUOUS : False
  F_CONTIGUOUS : False
  OWNDATA : False
  WRITEABLE : True
  ALIGNED : True
  WRITEBACKIFCOPY : False

>>> w.scaled_data.flags
  C_CONTIGUOUS : True
  F_CONTIGUOUS : True
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  WRITEBACKIFCOPY : False

>>> w.raw_data.astype(np.float64).flags
  C_CONTIGUOUS : True
  F_CONTIGUOUS : True
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  WRITEBACKIFCOPY : False

>>> w.raw_data.astype(np.float64, copy=False).flags
  C_CONTIGUOUS : False
  F_CONTIGUOUS : False
  OWNDATA : False
  WRITEABLE : True
  ALIGNED : True
  WRITEBACKIFCOPY : False

Expected Behavior

When raw_data.dtype == np.float64 and scale_mode == NO_SCALING, scaled_data returns raw_data without making a copy.

Current Behavior

scaled_data always makes a copy.

Possible Solution

Add copy=False to the astype call in _convert_data.

Context

Reviewing nidaqmx changes.

Your Environment

N/A

AB#3262958

Start at AnalogWaveform.scaled_data and follow its _convert_data call, using the reproduction with a non-contiguous float64 raw_data array and NO_SCALING. Done means scaled_data preserves the raw_data view instead of allocating a copy under the stated conditions, as shown by the array flags.