CN114636827B - Method, device, equipment and medium for eliminating abnormal points of reaction curve - Google Patents
Method, device, equipment and medium for eliminating abnormal points of reaction curve Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a medium for eliminating abnormal points of a reaction curve, wherein the method comprises the following steps: fitting the current reaction curve based on the reaction curve model so as to obtain a trend line currently corresponding to the current reaction curve; and calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal points in the current reaction curve according to the fitting degree and the variation coefficient. If yes, calculating the deviation of the current reaction curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, constructing a deviation interval of the current reaction curve according to the average deviation and the variance to determine abnormal points in the current reaction curve, removing the abnormal points, taking the removed reaction curve as the current reaction curve, and performing the fitting step and the subsequent steps in a circulating manner until the abnormal points in the current reaction curve are determined not to be removed. All abnormal points in the original reaction curve are gradually found and removed, and the detection accuracy is greatly improved.
Description
Technical Field
The invention relates to the technical field of protein detection, in particular to a method, a device, equipment and a medium for eliminating abnormal points of a reaction curve.
Background
The detection of specific proteins is of great clinical value. Usually, an immunoturbidimetry is adopted for specific proteins, and the detection principle is that soluble antigen antibodies freely move and collide with each other in a liquid phase environment to complete specific binding of the soluble antigen antibodies, immune complex particles are formed, when light passes through the immune complex particles, absorption and scattering/transmission of light are formed, the change of light intensity after the absorption and scattering/transmission is detected, and the content of substances to be detected in a solution is calculated.
The full-automatic specific protein detection instrument can automatically collect reagents and samples to a reaction container for immunoreaction through machinery, but the existence of interference factors such as instrument factors (such as operations of air bubbles, uniform mixing and the like), reagent factors (such as precipitates, impurities and the like), sample factors (such as incomplete hemolysis and the like) and the like often causes the instrument to detect a plurality of interference signals, thereby influencing the accuracy of specific protein detection.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a device and a medium for eliminating abnormal points of a reaction curve to solve the problem of inaccurate protein detection.
A method for rejecting outliers of a response curve, said method comprising:
acquiring an original reaction curve and a reaction curve model, and taking the original reaction curve as a current reaction curve to be identified; wherein the reaction curve model is used to indicate a curve trend of the original reaction curve;
fitting the current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve;
calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal point in the current reaction curve according to the fitting degree and the variation coefficient;
if the abnormal points in the current response curve are determined to be eliminated, calculating the deviation of the current response curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, and constructing a deviation interval of the current response curve according to the average deviation and the variance; the deviation interval is used for indicating the upper and lower limit values of the deviation of a normal point in the current reaction curve;
determining normal points and abnormal points in the current reaction curve according to the deviations of all sampling points and the deviation intervals, eliminating all abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step of fitting the current reaction curve based on the reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are not eliminated.
In one embodiment, after determining not to eliminate the abnormal point in the current response curve, the method further includes:
acquiring a trend line corresponding to the current reaction curve when the abnormal point in the current reaction curve is not eliminated, and taking the trend line as a target trend line;
and correcting all the reaction values determined as abnormal points in the original reaction curve into the reaction values on the target trend line at the same sampling moment.
In one embodiment, the method further comprises:
calculating the deviation of the original reaction curve and each same sampling point in the target trend line to obtain a plurality of early warning deviations;
counting the number of the early warning deviations which are larger than a preset deviation threshold value in the plurality of early warning deviations to obtain the early warning number;
and when the ratio of the early warning quantity to the quantity of the sampling points in the original reaction curve is greater than a preset ratio threshold value, determining that the original reaction curve is abnormal.
In one embodiment, the obtaining an original response curve and a response curve model, and using the original response curve as a current response curve to be identified includes:
acquiring the original reaction curve, at least one segmentation point and a plurality of sub-reaction curve models, and splitting the original reaction curve into a plurality of segments of sub-original reaction curves based on the at least one segmentation point; wherein one of the sub-response curve models is used for corresponding to a curve trend indicating a section of the sub-original response curve;
taking the multi-segment sub-original reaction curve as a current reaction curve to be identified currently;
the fitting the current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve includes:
fitting a target reaction curve based on a target reaction curve model to obtain a trend line currently corresponding to the current reaction curve; the target reaction curve model is any one of the multiple sub-reaction curve models, and the target reaction curve is one of the multiple sub-original reaction curves corresponding to the target reaction curve model.
In one embodiment, the determining whether to reject the outlier in the current response curve according to the fitting degree and the variation coefficient comprises:
acquiring the current iteration times, and determining to remove abnormal points in the current reaction curve if the current iteration times are less than or equal to a preset time threshold, wherein the current iteration times indicate the times of executing the step of fitting the current reaction curve based on the reaction curve model; or the like, or a combination thereof,
if the fitting degree is less than or equal to a preset fitting degree threshold value, determining to reject abnormal points in the current reaction curve; or the like, or a combination thereof,
and if the coefficient of variation is greater than or equal to a preset coefficient of variation threshold, determining to remove the abnormal point in the current reaction curve.
In one embodiment, the constructing a deviation interval of the current response curve according to the average deviation and the variance includes:
acquiring a preset interval coefficient, and calculating the product of the interval coefficient and the variance;
calculating the sum of the average deviation and the product, and taking the obtained first calculated value as the upper limit value of the deviation interval;
and calculating the difference between the average deviation and the product, and taking the obtained second calculated value as the lower limit value of the deviation interval.
In one embodiment, the determining normal points and abnormal points in the current response curve according to the deviations of all the sampling points and the deviation interval includes:
if the target sampling point falls into the deviation interval, determining the target sampling point as the normal point; wherein, the target sampling point is any one sampling point in the current reaction curve;
and if the target sampling point does not fall into the deviation interval, determining the target sampling point as the abnormal point.
An abnormal point rejection device for a response curve, the device comprising:
the system comprises an original reaction curve and model acquisition module, a response curve identification module and a response curve identification module, wherein the original reaction curve and model acquisition module is used for acquiring an original reaction curve and a response curve model and taking the original reaction curve as a current reaction curve to be identified currently; wherein the reaction curve model is used to indicate a curve trend of the original reaction curve;
the abnormal point removing module is used for fitting the current reaction curve based on the reaction curve model to obtain a trend line corresponding to the current reaction curve; calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal point in the current reaction curve according to the fitting degree and the variation coefficient; if the abnormal points in the current response curve are determined to be eliminated, calculating the deviation of the current response curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, and constructing a deviation interval of the current response curve according to the average deviation and the variance; the deviation interval is used for indicating the upper and lower limit values of the deviation of a normal point in the current reaction curve; determining normal points and abnormal points in the current reaction curve according to the deviations of all sampling points and the deviation intervals, eliminating all abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step of fitting the current reaction curve based on the reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are not eliminated.
A computer-readable storage medium, storing a computer program which, when executed by a processor, causes the processor to execute the steps of the above-described method for outlier rejection of a response curve.
An abnormal point rejection device of a reaction curve comprises a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to enable the processor to execute the steps of the abnormal point rejection method of the reaction curve.
The invention provides a method, a device, equipment and a medium for eliminating abnormal points of a reaction curve, which are characterized in that an original reaction curve and a reaction curve model are firstly obtained, then the original reaction curve is used as the current reaction curve to be identified, and the current reaction curve is fitted based on the reaction curve model, so that the current corresponding trend line of the current reaction curve is obtained; and calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether abnormal points in the current reaction curve are eliminated according to the fitting degree and the variation coefficient so as to judge whether the condition that sampling points are abnormal exists in the current reaction curve. If the abnormal points in the current reaction curve are determined to be eliminated, calculating the deviation of the current reaction curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, constructing the deviation interval of the current reaction curve according to the average deviation and the variance, determining the normal points and the abnormal points in the current reaction curve, eliminating all the abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and circularly executing the step of fitting the current reaction curve based on a reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are determined not to be eliminated. Therefore, all abnormal points in the original reaction curve can be gradually found and removed by continuously optimizing the trend line, data which is possible to have abnormal reaction is prevented from being used as a detection result without processing, and the detection accuracy is greatly improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
FIG. 1 is a schematic flowchart of a method for rejecting abnormal points from a reaction curve according to a first embodiment;
FIG. 2 is a schematic representation of the original reaction curve;
FIG. 3 is a schematic diagram of fitting a current response curve based on a response curve model to obtain a corresponding trend line;
FIG. 4 is a schematic diagram of rejecting all outliers in a current response curve;
FIG. 5 is a schematic diagram of rejecting all outliers in the original response curve;
FIG. 6 is a schematic flow chart of the modification of the raw reaction curve in one embodiment;
FIG. 7 is a schematic diagram of correcting outliers in the original reaction curve;
FIG. 8 is a schematic flow chart illustrating the process for determining anomalies in an original response curve in one embodiment;
FIG. 9 is a schematic flowchart of a method for rejecting abnormal points of a reaction curve according to a second embodiment;
FIG. 10 is a schematic diagram of splitting an original reaction curve into multiple sub-original reaction curves based on segmentation points;
FIG. 11 is a schematic diagram showing an example of the structure of an abnormal point elimination apparatus for a reaction curve;
FIG. 12 is a block diagram showing an arrangement of an outlier rejection unit of the reaction curve in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, fig. 1 is a schematic flow chart of a method for rejecting abnormal points of a response curve in a first embodiment, where the method for rejecting abnormal points of a response curve in the first embodiment includes:
and 102, acquiring an original reaction curve and a reaction curve model, and taking the original reaction curve as a current reaction curve to be identified currently.
The original reaction curve refers to a reaction curve acquired by an instrument initially, the reaction curve is not processed, abnormal points caused by interference factors such as instrument factors (such as operations of air bubbles, uniform mixing and the like), reagent factors (such as precipitates, impurities and the like), sample factors (such as incomplete hemolysis and the like) and the like exist in the curve, and the invention aims to identify and remove the abnormal points so as to realize the detection accuracy. The reaction curve model is used for indicating the curve trend of the original reaction curve and is determined by observing the curve trend of the original reaction curve by an inspector. The general reaction curve model may be a linear function, a polynomial function, a sigmoid function, an exponential function, a power function, a logarithmic function, or the like.
Illustratively, as shown in fig. 2, the raw reaction curve is obtained, wherein the horizontal axis represents time (the number of points of the sampling point) and the vertical axis represents the sampling value. Further, the examiner determines the reaction curve model as a linear function y = ax + b by observing the curve trend thereof. And taking the original reaction curve as the current reaction curve to be identified, and removing abnormal points in the current reaction curve.
And 104, fitting the current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve.
As shown in fig. 3, the current response curve is fitted based on the response curve model y = ax + b to obtain a trend line currently corresponding to the current response curve. Wherein, the current reaction curve can be fitted by a least square method or other existing methods, and the specific process is not repeated. Referring to fig. 3, it can be seen that the initially obtained trend line cannot completely fit the current response curve due to the interference of the outliers.
And 106, calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal points in the current reaction curve according to the fitting degree and the variation coefficient. If it is determined to eliminate the abnormal points in the current response curve, step 108 is executed.
Wherein, it is provided with
Is the ith sampling point in the current response curve y, and the mean value of y is
,
Is a trend line
If the number of the sampling points is n, the fitting degree is calculated as follows:
total square sum (totalsumofsquares, SST):
regression sum of squares
regressionsumofsquares，SSR):
Residual Sum of Squares (SSE):
degree of fitting:
the coefficient of variation is calculated as:
standard deviation:
coefficient of variation:
in one embodiment, the determining the condition for rejecting outliers in the current response curve comprises:
wherein, only any one of the above conditions needs to be satisfied,namely, the abnormal points in the current reaction curve are determined to be removed. In the above condition, iter is the current iteration count, and indicates the number of times to execute step 104;
a preset time threshold value;
is a preset threshold of fitness;
is a preset variation coefficient threshold.
And step 108, calculating the deviation of the current reaction curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, and constructing the deviation interval of the current reaction curve according to the average deviation and the variance.
That is to say:
sampling point
Deviation of (c):
average deviation:
variance:
in this embodiment, the deviation interval is used to indicate the upper and lower limit values of the deviation of the normal point in the current response curve. In one embodiment, the deviation interval
Is constructed by the following formula:
wherein minRange is the lower limit value of the deviation interval, and maxRange is the upper limit value of the deviation interval; the sigma is a preset interval coefficient and can be set according to requirements.
And step 110, determining normal points and abnormal points in the current reaction curve according to the deviations and deviation intervals of all the sampling points, eliminating all the abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to the step 104 until determining that the abnormal points in the current reaction curve are not eliminated.
In one embodiment, the normal point and the abnormal point are determined in the following manner: if the target sampling point
Fall into the deviation interval
Internally, determining the target sampling point
Is a normal point; if the target sampling point
Does not fall within the deviation interval
Then determining the target sampling point
Is an outlier. That is to say expressed as:
and then all abnormal points in the current reaction curve are removed, and the reaction curve after removal is used as the current reaction curve. For example, as shown in fig. 4, for example, when the abnormal point is removed for the first time, the sampling point in the elliptical region is removed as the abnormal point, then the non-removed portion is used as the current response curve, the step 104 and the subsequent steps are executed again to perform iteration until the abnormal point in the current response curve is determined not to be removed when a certain iteration reaches the step 106, and the whole process is ended. Illustratively, through multiple iterations, the result shown in fig. 5 can be obtained finally; in fig. 5, the sampling points in the area indicated by the ellipse are abnormal points, and the other sampling points are normal points, and all the abnormal points in the original reaction curve can be gradually found and removed through the iteration, so that the detection accuracy is improved.
The method for eliminating the abnormal points of the reaction curve comprises the steps of firstly obtaining an original reaction curve and a reaction curve model, then taking the original reaction curve as a current reaction curve to be identified currently, and fitting the current reaction curve based on the reaction curve model so as to obtain a trend line corresponding to the current reaction curve currently; and calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether abnormal points in the current reaction curve are eliminated according to the fitting degree and the variation coefficient so as to judge whether the sampling points in the current reaction curve are abnormal. If the abnormal points in the current reaction curve are determined to be eliminated, calculating the deviation of the current reaction curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, constructing the deviation interval of the current reaction curve according to the average deviation and the variance, determining the normal points and the abnormal points in the current reaction curve, eliminating all the abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and circularly executing the step of fitting the current reaction curve based on a reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are determined not to be eliminated. Therefore, all abnormal points in the original reaction curve can be gradually found and removed by continuously optimizing the trend line, data which is possible to have abnormal reaction is prevented from being used as a detection result without processing, and the detection accuracy is greatly improved.
Furthermore, the original reaction curve is corrected to obtain the correct reaction curve. In one embodiment, as shown in fig. 6, after determining not to reject the abnormal point in the current response curve, the following steps are further performed:
That is, the trend line shown in fig. 5 is obtained as the target trend line, and the degree of fitting of the target trend line to all normal points is high, so that the curve trend of the response value in the data acquisition process can be more accurately indicated.
Illustratively, as shown in fig. 7, for one abnormal point a in the original response curve, the response value of the abnormal point is replaced by the response value of the point B on the target trend line at the same sampling time. And for the rest reaction points in the original reaction curve, the same treatment is also carried out, and finally, a corrected reaction curve can be obtained, and the corrected reaction curve can reduce the real reaction value in the data acquisition process to the maximum extent, so that the influence of interference factors is eliminated.
Furthermore, the invention also designs an alarm mechanism which identifies and alarms the abnormal original reaction curve, thereby prompting detection personnel to timely eliminate interference factors such as instrument factors (such as operations of air bubbles, uniform mixing and the like), reagent factors (such as precipitates, impurities and the like), sample factors (such as incomplete hemolysis and the like) and the like, and further improving the detection accuracy. In one embodiment, as shown in fig. 8, the following steps are also performed:
and step 802, calculating the deviation of the original reaction curve and each same sampling point in the target trend line to obtain a plurality of early warning deviations.
For example, set
Is the original reaction curve
The (ii) th sampling point in (d),
is a target trend line
The ith sampling point in, the number of sampling points is n, and then the early warning deviation of sampling point i is:
and 804, counting the number of the early warning deviations which are larger than a preset deviation threshold value in the plurality of early warning deviations to obtain the early warning number.
That is, a deviation threshold value is set
When there is one sampling point i satisfying the condition:
and if so, enabling the early warning number M = M +1. And performing the statistics on all the early warning deviations to obtain the final early warning quantity M.
That is, a ratio threshold is set
When it is satisfied
And then, determining that the original reaction curve is abnormal, and performing abnormal alarm to remind detection personnel to eliminate interference factors.
As shown in fig. 9, fig. 9 is a schematic flow chart of a method for rejecting abnormal points of a response curve in a second embodiment, where the method for rejecting abnormal points of a response curve in the second embodiment includes:
Wherein one of the sub-response curve models is used to correspond to a curve trend indicative of a segment of the sub-original response curve.
Exemplarily, as shown in fig. 10, assuming that the original response curve cannot be covered by a single function as a whole by the inspection personnel, 2 segmentation points are set as shown in fig. 10, the original response curve is divided into 3 segments of sub-original response curves, and the sub-response curves are determined to be modeled as functions
A sum function
. It can be seen that the model of the response curve is a sub-curve
Can indicate the curve trend of two sides of two segmentation points, and can indicate the curve trend of two sides of two segmentation points through a sub-reaction curve model
A curve trend inside the two segmentation points may be indicated. And taking the multiple sections of sub-original reaction curves as the current reaction curve to be identified so as to independently remove the abnormal points.
And 904, fitting the target reaction curve based on the target reaction curve model to obtain a current corresponding trend line of the current reaction curve.
The target reaction curve model is any one of a plurality of sub-reaction curve models, and the target reaction curve is one of a plurality of sections of sub-original reaction curves corresponding to the target reaction curve model. That is to saySay, by the sub-reaction curve model
Fitting the reaction curves at two sides of the two segmentation points; and passing the sub-reaction curve model
To fit the reaction curve inside the two segmentation points. The fitting between the reaction curves of different segments is not interfered with each other, thereby realizing the fitting of the original reaction curve which is more complex.
And 910, determining normal points and abnormal points in the current reaction curve according to the deviations and deviation intervals of all sampling points, eliminating all abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step 904 and the subsequent steps until the abnormal points in the current reaction curve are determined not to be eliminated.
In this embodiment, steps 906 to 910 are substantially the same as steps 106 to 110 in the method for rejecting abnormal points of a response curve in the first embodiment provided by the present invention, and are not repeated here.
Therefore, the method can eliminate abnormal points of the original complex reaction curve, and expand the practical application scene of the method.
In one embodiment, as shown in fig. 11, an abnormal point rejecting apparatus for a response curve is provided, the apparatus including:
an original reaction curve and model obtaining module 1102, configured to obtain an original reaction curve and a reaction curve model, and use the original reaction curve as a current reaction curve to be identified; wherein the reaction curve model is used to indicate a curve trend of the original reaction curve;
an abnormal point removing module 1104, configured to fit the current response curve based on the response curve model to obtain a trend line currently corresponding to the current response curve; calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal point in the current reaction curve according to the fitting degree and the variation coefficient; if the abnormal points in the current response curve are determined to be eliminated, calculating the deviation of the current response curve and each same sampling point in the trend line, and the average deviation and variance of all sampling points, and constructing a deviation interval of the current response curve according to the average deviation and the variance; the deviation interval is used for indicating the upper and lower limit values of the deviation of a normal point in the current reaction curve; determining normal points and abnormal points in the current reaction curve according to the deviations of all sampling points and the deviation intervals, eliminating all abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step of fitting the current reaction curve based on the reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are not eliminated.
FIG. 12 is a diagram showing an internal structure of an abnormal point elimination device of the reaction curve in one embodiment. As shown in fig. 12, the abnormal point rejection apparatus of the response curve includes a processor, a memory, and a network interface connected by a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the abnormal point rejection device for the reaction curve stores an operating system and also stores a computer program, and when the computer program is executed by a processor, the processor can realize the abnormal point rejection method for the reaction curve. The internal memory may also store a computer program, and the computer program, when executed by the processor, may cause the processor to perform a method of outlier rejection of a response curve. It will be understood by those skilled in the art that the structure shown in fig. 12 is a block diagram of only a part of the structure related to the present application, and does not constitute a limitation to the abnormal point rejection apparatus of the reaction curve to which the present application is applied, and the abnormal point rejection apparatus of a specific reaction curve may include more or less components than those shown in the figure, or may combine some components, or have a different arrangement of components.
An abnormal point rejection device of a reaction curve comprises a memory, a processor and a computer program which is stored in the memory and can be executed on the processor, wherein the processor executes the computer program to realize the following steps: acquiring an original reaction curve and a reaction curve model, and taking the original reaction curve as a current reaction curve to be identified; fitting a current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve; calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal points in the current reaction curve according to the fitting degree and the variation coefficient; if the abnormal points in the current response curve are determined to be eliminated, calculating the deviation of the current response curve and each same sampling point in the trend line, and the average deviation and variance of all the sampling points, and constructing the deviation interval of the current response curve according to the average deviation and variance; and determining normal points and abnormal points in the current reaction curve according to the deviations and deviation intervals of all sampling points, eliminating all the abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step of fitting the current reaction curve based on the reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are not eliminated.
A computer-readable storage medium storing a computer program which, when executed by a processor, performs the steps of: acquiring an original reaction curve and a reaction curve model, and taking the original reaction curve as a current reaction curve to be identified; fitting a current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve; calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal points in the current reaction curve according to the fitting degree and the variation coefficient; if the abnormal points in the current response curve are determined to be eliminated, calculating the deviation of the current response curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, and constructing the deviation interval of the current response curve according to the average deviation and the variance; and determining normal points and abnormal points in the current reaction curve according to the deviations and deviation intervals of all sampling points, eliminating all the abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step of fitting the current reaction curve based on the reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are not eliminated.
It should be noted that the method, the apparatus, the device and the computer-readable storage medium for rejecting abnormal points of a response curve belong to a general inventive concept, and the contents in the embodiments of the method, the apparatus, the device and the computer-readable storage medium for rejecting abnormal points of a response curve can be mutually applicable.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for eliminating abnormal points of a reaction curve is characterized by comprising the following steps:
acquiring an original reaction curve and a reaction curve model, and taking the original reaction curve as a current reaction curve to be identified; the reaction curve model is used for indicating the curve trend of the original reaction curve and comprises a linear function, a polynomial function, an S-shaped function, an exponential function, a power function and a logarithmic function;
fitting the current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve;
calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal point in the current reaction curve according to the fitting degree and the variation coefficient;
if the abnormal points in the current response curve are determined to be eliminated, calculating the deviation of the current response curve and each same sampling point in the trend line, and the average deviation and the variance of all the sampling points, and constructing a deviation interval of the current response curve according to the average deviation and the variance; the deviation interval is used for indicating the upper and lower limit values of the deviation of a normal point in the current reaction curve;
determining normal points and abnormal points in the current reaction curve according to the deviations of all sampling points and the deviation intervals, eliminating all abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step of fitting the current reaction curve based on the reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are not eliminated.
2. The method of claim 1, wherein after determining not to cull outliers in the current response curve, further comprising:
acquiring a trend line corresponding to the current reaction curve when the abnormal point in the current reaction curve is not eliminated, and taking the trend line as a target trend line;
and correcting all the reaction values determined as abnormal points in the original reaction curve into the reaction values on the target trend line at the same sampling moment.
3. The method of claim 2, further comprising:
calculating the deviation of the original reaction curve and each same sampling point in the target trend line to obtain a plurality of early warning deviations;
counting the number of the early warning deviations which are larger than a preset deviation threshold value in the plurality of early warning deviations to obtain the early warning number;
and when the ratio of the early warning quantity to the quantity of the sampling points in the original reaction curve is greater than a preset ratio threshold value, determining that the original reaction curve is abnormal.
4. The method of claim 1, wherein the obtaining of the original response curve and the response curve model, and using the original response curve as a current response curve to be identified, comprises:
acquiring the original reaction curve, at least one segmentation point and a plurality of sub-reaction curve models, and splitting the original reaction curve into a plurality of sub-original reaction curves based on the at least one segmentation point; wherein one of the sub-response curve models is used to correspond to a curve trend indicating a segment of the sub-original response curve;
taking the multi-segment sub-original reaction curve as a current reaction curve to be identified currently;
the fitting the current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve includes:
fitting a target reaction curve based on the target reaction curve model to obtain a current corresponding trend line of the current reaction curve; the target reaction curve model is any one of the multiple sub-reaction curve models, and the target reaction curve is one of the multiple sub-original reaction curves corresponding to the target reaction curve model.
5. The method of claim 1, wherein the determining whether to reject outliers in the current response curve based on the fitness and the coefficient of variation comprises:
acquiring the current iteration times, and determining to remove abnormal points in the current reaction curve if the current iteration times are less than or equal to a preset time threshold, wherein the current iteration times indicate the times of executing the step of fitting the current reaction curve based on the reaction curve model; or the like, or, alternatively,
if the fitting degree is less than or equal to a preset fitting degree threshold value, determining to reject abnormal points in the current reaction curve; or the like, or a combination thereof,
and if the coefficient of variation is larger than or equal to a preset coefficient of variation threshold, determining to remove the abnormal point in the current reaction curve.
6. The method of claim 1, wherein said constructing a deviation interval for said current response curve based on said mean deviation and said variance comprises:
acquiring a preset interval coefficient, and calculating the product of the interval coefficient and the variance;
calculating the sum of the average deviation and the product, and taking the obtained first calculated value as the upper limit value of the deviation interval;
and calculating the difference between the average deviation and the product, and taking the obtained second calculated value as the lower limit value of the deviation interval.
7. The method of claim 1, wherein the determining normal points and abnormal points in the current response curve according to the deviations of all the sampling points and the deviation interval comprises:
if the target sampling point falls into the deviation interval, determining the target sampling point as the normal point; wherein, the target sampling point is any one sampling point in the current reaction curve;
and if the target sampling point does not fall into the deviation interval, determining the target sampling point as the abnormal point.
8. An abnormal point removing device for a reaction curve, the device comprising:
the system comprises an original reaction curve and model acquisition module, a response curve identification module and a response curve identification module, wherein the original reaction curve and model acquisition module is used for acquiring an original reaction curve and a response curve model and taking the original reaction curve as a current reaction curve to be identified; wherein the response curve model is used for indicating the curve trend of the original response curve, and the response curve model comprises a linear function, a polynomial function, an S-shaped function, an exponential function, a power function and a logarithmic function;
the outlier removing module is used for fitting the current reaction curve based on the reaction curve model to obtain a trend line currently corresponding to the current reaction curve; calculating the fitting degree and the variation coefficient of the current reaction curve and the trend line, and determining whether to eliminate the abnormal point in the current reaction curve according to the fitting degree and the variation coefficient; if the abnormal points in the current response curve are determined to be eliminated, calculating the deviation of the current response curve and each same sampling point in the trend line, and the average deviation and variance of all sampling points, and constructing a deviation interval of the current response curve according to the average deviation and the variance; the deviation interval is used for indicating the upper and lower limit values of the deviation of a normal point in the current reaction curve; determining normal points and abnormal points in the current reaction curve according to the deviations of all sampling points and the deviation intervals, eliminating all abnormal points in the current reaction curve, taking the eliminated reaction curve as the current reaction curve, and returning to execute the step of fitting the current reaction curve based on the reaction curve model and the subsequent steps until the abnormal points in the current reaction curve are not eliminated.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, causes the processor to carry out the steps of the method according to any one of claims 1 to 7.
10. An outlier rejection device of a response curve comprising a memory and a processor, characterized in that said memory stores a computer program which, when executed by said processor, causes said processor to perform the steps of the method according to any of the claims 1 to 7.
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