session.py 文件源码

def _create_waveform_f64_numpy(self, waveform_data_array):
        '''_create_waveform_f64

        Creates an onboard waveform from binary F64 (floating point double) data
        for use in Arbitrary Waveform output mode or Arbitrary Sequence output
        mode. The **waveformHandle** returned can later be used for setting the
        active waveform, changing the data in the waveform, building sequences
        of waveforms, or deleting the waveform when it is no longer needed.

        Note:
        You must call the nifgen_ConfigureOutputMode function to set the
        **outputMode** parameter to NIFGEN_VAL_OUTPUT_ARB or
        NIFGEN_VAL_OUTPUT_SEQ before calling this function.

        Tip:
        This method requires repeated capabilities (usually channels). If called directly on the
        nifgen.Session object, then the method will use all repeated capabilities in the session.
        You can specify a subset of repeated capabilities using the Python index notation on an
        nifgen.Session instance, and calling this method on the result.:

            session['0,1']._create_waveform_f64(waveform_data_array)

        Args:
            waveform_data_array (numpy array of float64): Specifies the array of data you want to use for the new arbitrary
                waveform. The array must have at least as many elements as the value
                that you specify in **waveformSize**.

                You must normalize the data points in the array to be between –1.00 and
                +1.00.

                **Default Value**: None

        Returns:
            waveform_handle (int): The handle that identifies the new waveform. This handle is used later
                when referring to this waveform.
        '''
        import numpy

        if type(waveform_data_array) is not numpy.ndarray:
            raise TypeError('waveform_data_array must be {0}, is {1}'.format(numpy.ndarray, type(waveform_data_array)))
        if numpy.isfortran(waveform_data_array) is True:
            raise TypeError('waveform_data_array must be in C-order')
        if waveform_data_array.dtype is not numpy.dtype('float64'):
            raise TypeError('waveform_data_array must be numpy.ndarray of dtype=float64, is ' + str(waveform_data_array.dtype))
        vi_ctype = visatype.ViSession(self._vi)  # case 1
        channel_name_ctype = ctypes.create_string_buffer(self._repeated_capability.encode(self._encoding))  # case 2
        waveform_size_ctype = visatype.ViInt32(0 if waveform_data_array is None else len(waveform_data_array))  # case 6
        waveform_data_array_ctype = numpy.ctypeslib.as_ctypes(waveform_data_array)  # case 13.5
        waveform_handle_ctype = visatype.ViInt32()  # case 14
        error_code = self._library.niFgen_CreateWaveformF64(vi_ctype, channel_name_ctype, waveform_size_ctype, waveform_data_array_ctype, ctypes.pointer(waveform_handle_ctype))
        errors.handle_error(self, error_code, ignore_warnings=False, is_error_handling=False)
        return int(waveform_handle_ctype.value)