StatisticalTestMeanAdjustedCUSUM¶

class StatisticalTestMeanAdjustedCUSUM(self: visp._visp.core.StatisticalTestMeanAdjustedCUSUM, h: float = 4.f, k: float = 1.f, nbPtsForStats: int = 30)¶

Bases: StatisticalTestAbstract

Class that permits to perform a mean adjusted Cumulative Sum test.

The mean adjusted CUSUM test is designed to detect drift in the mean \(\mu\) of an observed signal \(s(t)\) .

Be \(\delta\) the amplitude of the mean drift we want to detect. Two test signals are computed at each iteration:

\(S_-(t) = max\{0, S_-(t-1) - (s(t) - \mu) - \frac{\delta}{2}\}\)

\(S_+(t) = max\{0, S_+(t-1) + (s(t) - \mu) - \frac{\delta}{2}\}\)

A downward alarm is raised if: \(S_-(t) >= thresh\)

An upward alarm is raised if: \(S_+(t) >= thresh\)

To ease the understanding of the detection threshold \(\delta\) and the alarm threshold \(thresh\) , ViSP implemented these two thresholds as a multiple of the standard deviation of the signal \(\sigma\) :

\(\delta = k \sigma , k \in R^{+*}\)

\(thresh = h \sigma , h \in R^{+*}\)

To have an Average Run Lenght of ~374 samples for a detection threshold \(\delta\) of 1 standard deviation \(\sigma\) , set \(h\) to 4.76 .

To detect only downward drifts of the input signal \(s(t)\) use testDownwardMeanDrift() .To detect only upward drifts in \(s(t)\) use testUpwardMeanDrift() . To detect both, downward and upward drifts use testDownUpwardMeanDrift() .

Construct a new vpStatisticalTestMeanAdjustedCUSUM object.

Parameters:

h: The alarm factor that permits to determine when the process is out of control from the standard deviation of the signal.
k: The detection factor that permits to determine the slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect, from the standard deviation of the signal.
nbPtsForStats: The number of samples to use to compute the mean and the standard deviation of the signal to monitor.

Methods

`__init__`	Construct a new vpStatisticalTestMeanAdjustedCUSUM object.
`getDelta`	Get the slack of the CUSUM test, i.e. amplitude of mean shift we want to be able to detect.
`getH`	Get the alarm factor.
`getK`	Get the detection factor.
`getTestSignalMinus`	Get the latest value of the test signal for downward jumps of the mean.
`getTestSignalPlus`	Get the latest value of the test signal for upward jumps of the mean.
`init`	Overloaded function.
`setDelta`	Set the slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect.
`setLimits`	Set the upward and downward jump limits.

Inherited Methods

`getAvailableMeanDriftType`	Get the list of available vpMeanDriftType objects that are handled.
`setMinStdev`	Set the minimum value of the standard deviation that is expected.
`testUpwardMeanDrift`	Test if an upward mean drift occurred according to the new value of the signal.
`MEAN_DRIFT_DOWNWARD`
`MEAN_DRIFT_NONE`
`setNbSamplesForStat`	Set the number of samples required to compute the mean and standard deviation of the signal and allocate the memory accordingly.
`getStdev`	Get the standard deviation used as reference.
`testDownUpwardMeanDrift`	Test if a downward or an upward mean drift occurred according to the new value of the signal.
`MeanDriftType`	Enum that indicates if a drift of the mean occurred.
`vpMeanDriftTypeToString`
`MEAN_DRIFT_BOTH`
`MEAN_DRIFT_UNKNOWN`
`vpMeanDriftTypeFromString`	Cast a string into a vpMeanDriftType .
`getLimits`	Get the upper and lower limits of the test signal.
`MEAN_DRIFT_UPWARD`
`MEAN_DRIFT_COUNT`
`testDownwardMeanDrift`	Test if a downward mean drift occurred according to the new value of the signal.
`print`
`getMean`	Get the mean used as reference.

Operators

`__doc__`
`__init__`	Construct a new vpStatisticalTestMeanAdjustedCUSUM object.
`__module__`

Attributes

`MEAN_DRIFT_BOTH`
`MEAN_DRIFT_COUNT`
`MEAN_DRIFT_DOWNWARD`
`MEAN_DRIFT_NONE`
`MEAN_DRIFT_UNKNOWN`
`MEAN_DRIFT_UPWARD`
`__annotations__`

class MeanDriftType(self, value: int)¶

Bases: pybind11_object

Enum that indicates if a drift of the mean occurred.

Values:

MEAN_DRIFT_NONE: No mean drift occurred
MEAN_DRIFT_DOWNWARD: A downward drift of the mean occurred.
MEAN_DRIFT_UPWARD: An upward drift of the mean occurred.
MEAN_DRIFT_BOTH: Both an aupward and a downward drifts occurred.
MEAN_DRIFT_COUNT
MEAN_DRIFT_UNKNOWN

__and__(self, other: object) → object¶

__eq__(self, other: object) → bool¶

__ge__(self, other: object) → bool¶

__getstate__(self) → int¶

__gt__(self, other: object) → bool¶

__hash__(self) → int¶

__index__(self) → int¶

__init__(self, value: int)¶

__int__(self) → int¶

__invert__(self) → object¶

__le__(self, other: object) → bool¶

__lt__(self, other: object) → bool¶

__ne__(self, other: object) → bool¶

__or__(self, other: object) → object¶

__rand__(self, other: object) → object¶

__ror__(self, other: object) → object¶

__rxor__(self, other: object) → object¶

__setstate__(self, state: int) → None¶

__xor__(self, other: object) → object¶

property name : str¶

__init__(self: visp._visp.core.StatisticalTestMeanAdjustedCUSUM, h: float = 4.f, k: float = 1.f, nbPtsForStats: int = 30)¶

Construct a new vpStatisticalTestMeanAdjustedCUSUM object.

Parameters:

h: The alarm factor that permits to determine when the process is out of control from the standard deviation of the signal.
k: The detection factor that permits to determine the slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect, from the standard deviation of the signal.
nbPtsForStats: The number of samples to use to compute the mean and the standard deviation of the signal to monitor.

static getAvailableMeanDriftType(prefix: str = <, sep: str =, suffix: str = >) → str¶

Get the list of available vpMeanDriftType objects that are handled.

Parameters:

prefix: The prefix that should be placed before the list.
sep: The separator between each element of the list.
suffix: The suffix that should terminate the list.

Returns:

std::string The list of handled type of process tests, presented as a string.

getDelta(self) → float¶

Get the slack of the CUSUM test, i.e. amplitude of mean shift we want to be able to detect.

Returns:: float The slack of the CUSUM test.

getH(self) → float¶

Get the alarm factor.

Returns:: float The alarm factor.

getK(self) → float¶

Get the detection factor.

Returns:: float The detection factor.

getLimits(self, limitDown: float, limitUp: float) → tuple[float, float]¶

Get the upper and lower limits of the test signal.

Parameters:

limitDown: float¶: The lower limit.
limitUp: float¶: The upper limit.

Returns:

A tuple containing:

limitDown: The lower limit.
limitUp: The upper limit.

getMean(self) → float¶

Get the mean used as reference.

Returns:: float The mean.

getStdev(self) → float¶

Get the standard deviation used as reference.

Returns:: float The standard deviation.

getTestSignalMinus(self) → float¶

Get the latest value of the test signal for downward jumps of the mean.

Returns:: float Its latest value.

getTestSignalPlus(self) → float¶

Get the latest value of the test signal for upward jumps of the mean.

Returns:: float Its latest value.

init(*args, **kwargs)¶

Overloaded function.

init(self: visp._visp.core.StatisticalTestMeanAdjustedCUSUM, h: float, k: float, nbPtsForStats: int) -> None

(Re)Initialize the mean adjusted CUSUM test.

Parameters:

h: The alarm factor that permits to determine when the process is out of control from the standard deviation of the signal.
k: The detection factor that permits to determine the slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect, from the standard deviation of the signal.
nbPtsForStats: The number of points to use to compute the mean and the standard deviation of the signal

init(self: visp._visp.core.StatisticalTestMeanAdjustedCUSUM, delta: float, limitDown: float, limitUp: float, nbPtsForStats: int) -> None

Initialize the mean adjusted CUSUM test.

Parameters:

delta: The slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect.
limitDown: The lower limit of the CUSUM test, for the downward jumps.
limitUp: The upper limit of the CUSUM test, for the upward jumps.
nbPtsForStats: The number of points to use to compute the mean and the standard deviation of the signal to monitor.

init(self: visp._visp.core.StatisticalTestMeanAdjustedCUSUM, h: float, k: float, mean: float, stdev: float) -> None

Initialize the mean adjusted CUSUM test.

Parameters:

h: The alarm factor that permits to determine when the process is out of control from the standard deviation of the signal.
k: The detection factor that permits to determine the slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect, from the standard deviation of the signal.
mean: The expected mean of the signal to monitor.
stdev: The expected standard deviation of the signal to monitor.

init(self: visp._visp.core.StatisticalTestMeanAdjustedCUSUM, delta: float, limitDown: float, limitUp: float, mean: float, stdev: float) -> None

Initialize the mean adjusted CUSUM test.

Parameters:

delta: The slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect.
limitDown: The lower limit of the CUSUM test, for the downward jumps.
limitUp: The upper limit of the CUSUM test, for the upward jumps.
mean: The expected mean of the signal to monitor.
stdev: The expected standard deviation of the signal to monitor.

init(self: visp._visp.core.StatisticalTestAbstract) -> None

(Re)Initialize the algorithm.

static print(type: visp._visp.core.StatisticalTestAbstract.MeanDriftType) → None¶

setDelta(self, delta: float) → None¶

Set the slack of the CUSUM test, i.e. the minimum value of the jumps we want to detect.

Parameters:

delta: float¶: The slack of the CUSUM test.

setLimits(self, limitDown: float, limitUp: float) → None¶

Set the upward and downward jump limits.

Parameters:

limitDown: float¶: The limit for the downward jumps.
limitUp: float¶: The limit for the upward jumps.

setMinStdev(self, stdevmin: float) → None¶

Set the minimum value of the standard deviation that is expected. The computed standard deviation cannot be lower this value if set.

Parameters:

stdevmin: float¶: The minimum value of the standard deviation that is expected.

setNbSamplesForStat(self, nbSamples: int) → None¶

Set the number of samples required to compute the mean and standard deviation of the signal and allocate the memory accordingly.

Parameters:

nbSamples: int¶: The number of samples we want to use.

testDownUpwardMeanDrift(self, signal: float) → visp._visp.core.StatisticalTestAbstract.MeanDriftType¶

Test if a downward or an upward mean drift occurred according to the new value of the signal.

Note

See testDownwardMeanDrift() testUpwardMeanDrift()

Parameters:

signal: float¶: The new value of the signal.

Returns:

vpMeanDriftType The type of mean drift that occurred.

testDownwardMeanDrift(self, signal: float) → visp._visp.core.StatisticalTestAbstract.MeanDriftType¶

Test if a downward mean drift occurred according to the new value of the signal.

Note

See testUpwardMeanDrift()

Parameters:

signal: float¶: The new value of the signal.

Returns:

vpMeanDriftType The type of mean drift that occurred.

testUpwardMeanDrift(self, signal: float) → visp._visp.core.StatisticalTestAbstract.MeanDriftType¶

Test if an upward mean drift occurred according to the new value of the signal.

Note

See testDownwardMeanDrift()

Parameters:

signal: float¶: The new value of the signal.

Returns:

vpMeanDriftType The type of mean drift that occurred.

static vpMeanDriftTypeFromString(name: str) → visp._visp.core.StatisticalTestAbstract.MeanDriftType¶

Cast a string into a vpMeanDriftType .

Parameters:

name: str¶: The name of the mean drift.

Returns:

vpMeanDriftType The corresponding vpMeanDriftType .

static vpMeanDriftTypeToString(type: visp._visp.core.StatisticalTestAbstract.MeanDriftType) → str¶