def ai_meas_types(self):
"""
List[:class:`nidaqmx.constants.UsageTypeAI`]: Indicates the
measurement types supported by the channel.
"""
cfunc = lib_importer.windll.DAQmxGetPhysicalChanAISupportedMeasTypes
cfunc.argtypes = [
ctypes_byte_str, wrapped_ndpointer(dtype=numpy.int32,
flags=('C','W')), ctypes.c_uint]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.int32)
size_or_code = cfunc(
self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return [UsageTypeAI(e) for e in val]
def table_scaled_vals(self):
"""
List[float]: Specifies a list of scaled values. These values map
directly to the values in **table_pre_scaled_vals**.
"""
cfunc = lib_importer.windll.DAQmxGetScaleTableScaledVals
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
ctypes_byte_str,
wrapped_ndpointer(dtype=numpy.float64,
flags=('C', 'W')), ctypes.c_uint
]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.float64)
size_or_code = cfunc(self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return val.tolist()
def do_samp_modes(self):
"""
List[:class:`nidaqmx.constants.AcquisitionType`]: Indicates the
sample modes supported by devices that support sample
clocked digital output.
"""
cfunc = lib_importer.windll.DAQmxGetPhysicalChanDOSampModes
cfunc.argtypes = [
ctypes_byte_str, wrapped_ndpointer(dtype=numpy.int32,
flags=('C','W')), ctypes.c_uint]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.int32)
size_or_code = cfunc(
self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return [AcquisitionType(e) for e in val]
def teds_template_ids(self):
"""
List[int]: Indicates the IDs of the templates in the bitstream
in **teds_bit_stream**.
"""
cfunc = lib_importer.windll.DAQmxGetPhysicalChanTEDSTemplateIDs
cfunc.argtypes = [
ctypes_byte_str, wrapped_ndpointer(dtype=numpy.uint32,
flags=('C','W')), ctypes.c_uint]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.uint32)
size_or_code = cfunc(
self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return val.tolist()
def ao_power_amp_scaling_coeff(self):
"""
List[float]: Indicates the coefficients of a polynomial equation
used to scale from pre-amplified values.
"""
cfunc = lib_importer.windll.DAQmxGetAOPowerAmpScalingCoeff
cfunc.argtypes = [
ctypes_byte_str, wrapped_ndpointer(dtype=numpy.float64,
flags=('C','W')), ctypes.c_uint]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.float64)
size_or_code = cfunc(
self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return val.tolist()
def teds_bit_stream(self):
"""
List[int]: Indicates the TEDS binary bitstream without
checksums.
"""
cfunc = lib_importer.windll.DAQmxGetPhysicalChanTEDSBitStream
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
ctypes_byte_str, wrapped_ndpointer(dtype=numpy.uint8,
flags=('C','W')), ctypes.c_uint]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.uint8)
size_or_code = cfunc(
self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return val.tolist()
def ao_power_up_output_types(self):
"""
List[:class:`nidaqmx.constants.AOPowerUpOutputBehavior`]:
Indicates the power up output types supported by the
channel.
"""
cfunc = (lib_importer.windll.
DAQmxGetPhysicalChanAOSupportedPowerUpOutputTypes)
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
ctypes_byte_str, wrapped_ndpointer(dtype=numpy.int32,
flags=('C','W')), ctypes.c_uint]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.int32)
size_or_code = cfunc(
self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return [AOPowerUpOutputBehavior(e) for e in val]
def poly_reverse_coeff(self):
"""
List[float]: Specifies a list of coefficients for the polynomial
that converts scaled values to pre-scaled values. Each
element of the list corresponds to a term of the equation.
For example, if index three of the list is 9, the fourth
term of the equation is 9y^3.
"""
cfunc = lib_importer.windll.DAQmxGetScalePolyReverseCoeff
cfunc.argtypes = [
ctypes_byte_str,
wrapped_ndpointer(dtype=numpy.float64, flags=('C', 'W')),
ctypes.c_uint
]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.float64)
size_or_code = cfunc(self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return val.tolist()
def ai_sensor_power_voltage_range_vals(self):
"""
List[float]: Indicates pairs of sensor power voltage ranges
supported by this channel. Each pair consists of the low
value followed by the high value.
"""
cfunc = (lib_importer.windll.
DAQmxGetPhysicalChanAISensorPowerVoltageRangeVals)
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
ctypes_byte_str,
wrapped_ndpointer(dtype=numpy.float64,
flags=('C', 'W')), ctypes.c_uint
]
temp_size = 0
while True:
val = numpy.zeros(temp_size, dtype=numpy.float64)
size_or_code = cfunc(self._name, val, temp_size)
if is_array_buffer_too_small(size_or_code):
# Buffer size must have changed between calls; check again.
temp_size = 0
elif size_or_code > 0 and temp_size == 0:
# Buffer size obtained, use to retrieve data.
temp_size = size_or_code
else:
break
check_for_error(size_or_code)
return val.tolist()
