rminstr_specs.HP3458A

Classes

DatasheetDCI

Class that defines the current datasheet uncertainties for the HP3458A.

DatasheetDCV

Class that defines the datasheet uncertainties for the HP3458A.

DatasheetDCOhm

Class that defines the current datasheet uncertainties for the HP3458A.

Package Contents

class rminstr_specs.HP3458A.DatasheetDCI(name: str = 'HP3458ADCI', serial: str = 'NA', i_range: float = None, days_since_cal: int = None, delta_t_cal=None, acal: bool = None, time_zero: float = None, nplc: float = None, suppress_warnings: bool = False, **kwargs)

Bases: rminstr_specs.Specification

Class that defines the current datasheet uncertainties for the HP3458A.

This model assumes a uniform distribution between the datasheet ranges, the functions output the standard deviation (1/sqrt(3)) of the posted errors.

Initialize instance of DCV datasheet specs of HP3458A.

Parameters:
namestr,

Used in spec_manager to generate names for uncertainty mechanisms. Used for identifying instruments in warnings. The default is ‘HP3458ADCI’.

serialstr,

Serial of instrument. Used to identify calibration history in log books. The default is ‘NA’.

i_rangefloat, optional

Current measurement range. The default is None.

days_since_calint, optional

Days since the last calibration. The default is None.

delta_t_calfloat, optional

Ambient temperature of measurement. The default is None.

acalbool, optional

Whether or not the instrument was autocalibrated before measurements. The default is None.

time_zero: float, optional

Used as comparison time when trying to infer days since cal from logbook.

nplc: float, optional

Power lince cycle integrations. Default is None.

suppress_warningsbool, optional

Suppress warning output to the console. The default is False

Returns:
None.
components
i_range = None
days_since_cal = None
delta_t_cal = None
acal = None
nplc = None
all_manufacturer_errors(readings: numpy.ndarray, addition_method: str = 'spec')

Calculate all manufacturer errors and add them together.

Add together all the manufacture errors using rules given by the datasheet.

Parameters:
readings_np.ndarray

Readings to get errors for.

addition_methodstr, optional

Specifies how the errors are added together. Linear will add all the standard deviations linearly, whereas quad will do a quadrature sum. Linear will give a worst case. Setting this to ‘spec’ will do whatever the specsheet says if stated, otherwise it will revert to linear. The default is ‘spec’.

Returns:
errnp.ndarray

Total manufacturer errors.

accuracy_offset(readings: numpy.ndarray)

Get the offset accuracy errors.

accuracy_slope(readings: numpy.ndarray)

Get the slope accuracy errors.

temperature_coef_offset(readings: numpy.ndarray)

Get the temperature coefficient errors.

temperature_coef_slope(readings: numpy.ndarray)

Get the temperature coefficient slope errors.

powerline_cycles(readings: numpy.ndarray)

Get errors associates with powerline cycle readings

This is specific as Root mean square of noise, so presumably k=1 uncertainty.

class rminstr_specs.HP3458A.DatasheetDCV(name: str = 'HP3458ADCV', serial: str = 'NA', v_range: float = None, days_since_cal: int = None, delta_t_cal: float = None, acal: bool = None, time_zero: float = None, nplc: float = None, suppress_warnings: bool = False, **kwargs)

Bases: rminstr_specs.Specification

Class that defines the datasheet uncertainties for the HP3458A.

This model assumes a uniform distribution between the datasheet ranges, the functions output the standard deviation (1/sqrt(3)) of the posted errors.

Initialize instance of DCV datasheet specs of HP3458A.

Parameters:
namestr,

Used in spec_manager to generate names for uncertainty mechanisms. Used for identifying instruments in warnings. The default is ‘HP3458ADCV’

serialstr,

Serial of instrument. Used to identify calibration history in log books. The default is ‘NA’

v_rangefloat, optional

Current measurement range. The default is None.

days_since_calint, optional

Days since the last calibration. The default is None.

delta_t_calfloat, optional

Ambient temperature of measurement. The default is None.

acalbool, optional

Whether or not the instrument was auto calibrated before measurements. The default is None.

time_zerofloat, optional

Used as comparison time when trying to infer days since cal from logbook

nplcfloat, optional

Power lince cycle integrations. Default is None.

suppress_warningsbool, optional

Suppress warning output to the console. The default is False

Returns:
None.
components
v_range = None
days_since_cal = None
delta_t_cal = None
acal = None
nplc = None
suppress_warnings = False
all_manufacturer_errors(readings: numpy.ndarray, addition_method: str = 'spec')

Return the sum of all manufacturer errors for readings.

Ensure that errors are added in the way specified by the data sheet, if provided. The default is spec unless overridden by a child class.

if spec, it will use the spec sheet addition which is linear if linear, it will add linearly if quadrature, it will add in quadrature

Parameters:
readings_np.ndarray

Array of measurements to get uncertainties for.

addition_methodstr, optional

Specifies how the errors are added together. Linear will add all the standard deviations linearly, whereas quad will do a quadrature sum. Linear will give a worst case. Setting this to ‘spec’ will do whatever the specsheet says if stated, otherwise it will revert to linear. The default is ‘spec’.

Returns:
np.ndarray

Array of manufacturer errors of same shape as readings.

accuracy_offset(readings: numpy.ndarray)

Get the offset accuracy errors.

accuracy_slope(readings: numpy.ndarray)

Get the slope accuracy errors.

temperature_coef_offset(readings: numpy.ndarray)

Get the temperature coefficient errors.

temperature_coef_slope(readings: numpy.ndarray)

Get the temperature coefficient slope errors.

powerline_cycles(readings: numpy.ndarray)

Get errors associates with powerline cycle readings

This is specifiec as Root mean square of noise, so presumably k=1 uncertainty.

class rminstr_specs.HP3458A.DatasheetDCOhm(name: str = 'HP3458ADCI', serial: str = 'NA', ohm_range: float = None, days_since_cal: int = None, delta_t_cal=None, acal: bool = None, time_zero: float = None, nplc: float = None, wires: int = None, suppress_warnings: bool = False, **kwargs)

Bases: rminstr_specs.Specification

Class that defines the current datasheet uncertainties for the HP3458A.

This model assumes a uniform distribution between the datasheet ranges, the functions output the standard deviation (1/sqrt(3)) of the posted errors.

Initialize instance of DCV datasheet specs of HP3458A.

Parameters:
namestr,

Used in spec_manager to generate names for uncertainty mechanisms. Used for identifying instruments in warnings. The default is ‘HP3458ADCI’.

serialstr,

Serial of instrument. Used to identify calibration history in log books. The default is ‘NA’.

ohm_rangefloat, optional

Current measurement range. The default is None.

days_since_calint, optional

Days since the last calibration. The default is None.

delta_t_calfloat, optional

Ambient temperature of measurement. The default is None.

acalbool, optional

Whether or not the instrument was auto calibrated before measurements. The default is None.

time_zero: float, optional

Used as comparison time when trying to infer days since cal from logbook.

nplc: float, optional

Power line cycle integrations. Default is None.

wires: int, optional

How many wires measured with. The default is 2.

suppress_warningsbool, optional

Suppress warning output to the console. The default is False

Returns:
None.
components
i_range = None
days_since_cal = None
delta_t_cal = None
acal = None
nplc = None
wires = None
all_manufacturer_errors(readings: numpy.ndarray, addition_method: str = 'spec')

Calculate all manufacturer errors and add them together.

Add together all the manufacture errors using rules given by the datasheet.

Parameters:
readings_np.ndarray

Readings to get errors for.

addition_methodstr, optional

Specifies how the errors are added together. Linear will add all the standard deviations linearly, whereas quad will do a quadrature sum. Linear will give a worst case. Setting this to ‘spec’ will do whatever the specsheet says if stated, otherwise it will revert to linear. The default is ‘spec’.

Returns:
errnp.ndarray

Total manufacturer errors.

accuracy_offset(readings: numpy.ndarray)

Get the offset accuracy errors.

accuracy_2wire(readings: numpy.array)
accuracy_slope(readings: numpy.ndarray)

Get the slope accuracy errors.

temperature_coef_offset(readings: numpy.ndarray)

Get the temperature coefficient errors.

temperature_coef_slope(readings: numpy.ndarray)

Get the temperature coefficient slope errors.

powerline_cycles(readings: numpy.ndarray)

Get errors associates with powerline cycle readings

This is specific as Root mean square of noise, so presumably k=1 uncertainty.