from __future__ import annotations
from nidaqmx.constants import READ_ALL_AVAILABLE, FillMode
from nidaqmx.stream_readers._channel_reader_base import ChannelReaderBase
[docs]
class AnalogUnscaledReader(ChannelReaderBase):
"""Reads unscaled samples from one or more analog input channels in an NI-DAQmx task."""
[docs]
def read_int16(self, data, number_of_samples_per_channel=READ_ALL_AVAILABLE, timeout=10.0):
"""Reads one or more unscaled 16-bit integer samples from one or more analog input channels in a task.
This read method accepts a preallocated NumPy array to hold the
samples requested, which can be advantageous for performance and
interoperability with NumPy and SciPy.
Passing in a preallocated array is valuable in continuous
acquisition scenarios, where the same array can be used
repeatedly in each call to the method.
Args:
data (numpy.ndarray): Specifies a preallocated 2D NumPy
array of unscaled 16-bit integer values to hold the
samples requested. The size of the array must be large
enough to hold all requested samples from all channels
in the task; otherwise, an error is thrown.
Each row corresponds to a channel in the task. Each
column corresponds to a sample from each channel. The
order of the channels in the array corresponds to the
order in which you add the channels to the task or to
the order of the channels you specify with the
"channels_to_read" property.
If the size of the array is too large or the array is
shaped incorrectly, the previous statement may not hold
true as the samples read may not be separated into rows
and columns properly. Set the "verify_array_shape"
property on this channel reader object to True to
validate that the NumPy array object is shaped properly.
Setting this property may marginally adversely impact
the performance of the method.
number_of_samples_per_channel (Optional[int]): Specifies the
number of samples to read.
If you set this input to nidaqmx.constants.
READ_ALL_AVAILABLE, NI-DAQmx determines how many samples
to read based on if the task acquires samples
continuously or acquires a finite number of samples.
If the task acquires samples continuously and you set
this input to nidaqmx.constants.READ_ALL_AVAILABLE, this
method reads all the samples currently available in the
buffer.
If the task acquires a finite number of samples and you
set this input to nidaqmx.constants.READ_ALL_AVAILABLE,
the method waits for the task to acquire all requested
samples, then reads those samples. If you set the
"read_all_avail_samp" property to True, the method reads
the samples currently available in the buffer and does
not wait for the task to acquire all requested samples.
timeout (Optional[float]): Specifies the amount of time in
seconds to wait for samples to become available. If the
time elapses, the method returns an error and any
samples read before the timeout elapsed. The default
timeout is 10 seconds. If you set timeout to
nidaqmx.constants.WAIT_INFINITELY, the method waits
indefinitely. If you set timeout to 0, the method tries
once to read the requested samples and returns an error
if it is unable to.
Returns:
int:
Indicates the number of samples acquired by each channel.
NI-DAQmx returns a single value because this value is the
same for all channels.
""" # noqa: W505 - doc line too long (110 > 100 characters) (auto-generated noqa)
number_of_samples_per_channel = self._task._calculate_num_samps_per_chan(
number_of_samples_per_channel
)
self._verify_array(data, number_of_samples_per_channel, True, True)
_, samps_per_chan_read = self._interpreter.read_binary_i16(
self._handle,
number_of_samples_per_channel,
timeout,
FillMode.GROUP_BY_CHANNEL.value,
data,
)
return samps_per_chan_read
[docs]
def read_int32(self, data, number_of_samples_per_channel=READ_ALL_AVAILABLE, timeout=10.0):
"""Reads one or more unscaled 32-bit integer samples from one or more analog input channels in a task.
This read method accepts a preallocated NumPy array to hold the
samples requested, which can be advantageous for performance and
interoperability with NumPy and SciPy.
Passing in a preallocated array is valuable in continuous
acquisition scenarios, where the same array can be used
repeatedly in each call to the method.
Args:
data (numpy.ndarray): Specifies a preallocated 2D NumPy
array of unscaled 32-bit integer values to hold the
samples requested. The size of the array must be large
enough to hold all requested samples from all channels
in the task; otherwise, an error is thrown.
Each row corresponds to a channel in the task. Each
column corresponds to a sample from each channel. The
order of the channels in the array corresponds to the
order in which you add the channels to the task or to
the order of the channels you specify with the
"channels_to_read" property.
If the size of the array is too large or the array is
shaped incorrectly, the previous statement may not hold
true as the samples read may not be separated into rows
and columns properly. Set the "verify_array_shape"
property on this channel reader object to True to
validate that the NumPy array object is shaped properly.
Setting this property may marginally adversely impact
the performance of the method.
number_of_samples_per_channel (Optional[int]): Specifies the
number of samples to read.
If you set this input to nidaqmx.constants.
READ_ALL_AVAILABLE, NI-DAQmx determines how many samples
to read based on if the task acquires samples
continuously or acquires a finite number of samples.
If the task acquires samples continuously and you set
this input to nidaqmx.constants.READ_ALL_AVAILABLE, this
method reads all the samples currently available in the
buffer.
If the task acquires a finite number of samples and you
set this input to nidaqmx.constants.READ_ALL_AVAILABLE,
the method waits for the task to acquire all requested
samples, then reads those samples. If you set the
"read_all_avail_samp" property to True, the method reads
the samples currently available in the buffer and does
not wait for the task to acquire all requested samples.
timeout (Optional[float]): Specifies the amount of time in
seconds to wait for samples to become available. If the
time elapses, the method returns an error and any
samples read before the timeout elapsed. The default
timeout is 10 seconds. If you set timeout to
nidaqmx.constants.WAIT_INFINITELY, the method waits
indefinitely. If you set timeout to 0, the method tries
once to read the requested samples and returns an error
if it is unable to.
Returns:
int:
Indicates the number of samples acquired by each channel.
NI-DAQmx returns a single value because this value is the
same for all channels.
""" # noqa: W505 - doc line too long (110 > 100 characters) (auto-generated noqa)
number_of_samples_per_channel = self._task._calculate_num_samps_per_chan(
number_of_samples_per_channel
)
self._verify_array(data, number_of_samples_per_channel, True, True)
_, samps_per_chan_read = self._interpreter.read_binary_i32(
self._handle,
number_of_samples_per_channel,
timeout,
FillMode.GROUP_BY_CHANNEL.value,
data,
)
return samps_per_chan_read
[docs]
def read_uint16(self, data, number_of_samples_per_channel=READ_ALL_AVAILABLE, timeout=10.0):
"""Reads one or more unscaled 16-bit unsigned integer samples from one or more analog input channels in a task.
This read method accepts a preallocated NumPy array to hold the
samples requested, which can be advantageous for performance and
interoperability with NumPy and SciPy.
Passing in a preallocated array is valuable in continuous
acquisition scenarios, where the same array can be used
repeatedly in each call to the method.
Args:
data (numpy.ndarray): Specifies a preallocated 2D NumPy
array of unscaled 16-bit unsigned integer values to
hold the samples requested. The size of the array must
be large enough to hold all requested samples from all
channels in the task; otherwise, an error is thrown.
Each row corresponds to a channel in the task. Each
column corresponds to a sample from each channel. The
order of the channels in the array corresponds to the
order in which you add the channels to the task or to
the order of the channels you specify with the
"channels_to_read" property.
If the size of the array is too large or the array is
shaped incorrectly, the previous statement may not hold
true as the samples read may not be separated into rows
and columns properly. Set the "verify_array_shape"
property on this channel reader object to True to
validate that the NumPy array object is shaped properly.
Setting this property may marginally adversely impact
the performance of the method.
number_of_samples_per_channel (Optional[int]): Specifies the
number of samples to read.
If you set this input to nidaqmx.constants.
READ_ALL_AVAILABLE, NI-DAQmx determines how many samples
to read based on if the task acquires samples
continuously or acquires a finite number of samples.
If the task acquires samples continuously and you set
this input to nidaqmx.constants.READ_ALL_AVAILABLE, this
method reads all the samples currently available in the
buffer.
If the task acquires a finite number of samples and you
set this input to nidaqmx.constants.READ_ALL_AVAILABLE,
the method waits for the task to acquire all requested
samples, then reads those samples. If you set the
"read_all_avail_samp" property to True, the method reads
the samples currently available in the buffer and does
not wait for the task to acquire all requested samples.
timeout (Optional[float]): Specifies the amount of time in
seconds to wait for samples to become available. If the
time elapses, the method returns an error and any
samples read before the timeout elapsed. The default
timeout is 10 seconds. If you set timeout to
nidaqmx.constants.WAIT_INFINITELY, the method waits
indefinitely. If you set timeout to 0, the method tries
once to read the requested samples and returns an error
if it is unable to.
Returns:
int:
Indicates the number of samples acquired by each channel.
NI-DAQmx returns a single value because this value is the
same for all channels.
""" # noqa: W505 - doc line too long (119 > 100 characters) (auto-generated noqa)
number_of_samples_per_channel = self._task._calculate_num_samps_per_chan(
number_of_samples_per_channel
)
self._verify_array(data, number_of_samples_per_channel, True, True)
_, samps_per_chan_read = self._interpreter.read_binary_u16(
self._handle,
number_of_samples_per_channel,
timeout,
FillMode.GROUP_BY_CHANNEL.value,
data,
)
return samps_per_chan_read
[docs]
def read_uint32(self, data, number_of_samples_per_channel=READ_ALL_AVAILABLE, timeout=10.0):
"""Reads one or more unscaled unsigned 32-bit integer samples from one or more analog input channels in a task.
This read method accepts a preallocated NumPy array to hold the
samples requested, which can be advantageous for performance and
interoperability with NumPy and SciPy.
Passing in a preallocated array is valuable in continuous
acquisition scenarios, where the same array can be used
repeatedly in each call to the method.
Args:
data (numpy.ndarray): Specifies a preallocated 2D NumPy
array of unscaled 32-bit unsigned integer values to
hold the samples requested. The size of the array must
be large enough to hold all requested samples from all
channels in the task; otherwise, an error is thrown.
Each row corresponds to a channel in the task. Each
column corresponds to a sample from each channel. The
order of the channels in the array corresponds to the
order in which you add the channels to the task or to
the order of the channels you specify with the
"channels_to_read" property.
If the size of the array is too large or the array is
shaped incorrectly, the previous statement may not hold
true as the samples read may not be separated into rows
and columns properly. Set the "verify_array_shape"
property on this channel reader object to True to
validate that the NumPy array object is shaped properly.
Setting this property may marginally adversely impact
the performance of the method.
number_of_samples_per_channel (Optional[int]): Specifies the
number of samples to read.
If you set this input to nidaqmx.constants.
READ_ALL_AVAILABLE, NI-DAQmx determines how many samples
to read based on if the task acquires samples
continuously or acquires a finite number of samples.
If the task acquires samples continuously and you set
this input to nidaqmx.constants.READ_ALL_AVAILABLE, this
method reads all the samples currently available in the
buffer.
If the task acquires a finite number of samples and you
set this input to nidaqmx.constants.READ_ALL_AVAILABLE,
the method waits for the task to acquire all requested
samples, then reads those samples. If you set the
"read_all_avail_samp" property to True, the method reads
the samples currently available in the buffer and does
not wait for the task to acquire all requested samples.
timeout (Optional[float]): Specifies the amount of time in
seconds to wait for samples to become available. If the
time elapses, the method returns an error and any
samples read before the timeout elapsed. The default
timeout is 10 seconds. If you set timeout to
nidaqmx.constants.WAIT_INFINITELY, the method waits
indefinitely. If you set timeout to 0, the method tries
once to read the requested samples and returns an error
if it is unable to.
Returns:
int:
Indicates the number of samples acquired by each channel.
NI-DAQmx returns a single value because this value is the
same for all channels.
""" # noqa: W505 - doc line too long (119 > 100 characters) (auto-generated noqa)
number_of_samples_per_channel = self._task._calculate_num_samps_per_chan(
number_of_samples_per_channel
)
self._verify_array(data, number_of_samples_per_channel, True, True)
_, samps_per_chan_read = self._interpreter.read_binary_u32(
self._handle,
number_of_samples_per_channel,
timeout,
FillMode.GROUP_BY_CHANNEL.value,
data,
)
return samps_per_chan_read