JP4885082B2 - Lens characteristic distribution display method for progressive power lens - Google Patents

Description

  The present invention relates to a method for displaying a lens characteristic distribution of a progressive-power lens capable of objectively evaluating the difference between the lens and another lens on a scale that serves as an index in selecting a progressive-power lens.

There are various kinds of progressive power lens products. Broadly speaking, there are a perspective type (a wide distance area above the lens is set), a middle and near type where the distance area is narrowed, and a near type where the near area is enlarged and the distance performance is sacrificed. These three types of characteristics are very different from each other, and a suitable type of product may be selected according to the purpose of the user. However, the difference is very difficult to understand between products of the same type. In particular, there are many types of products with similar characteristics because there are many types of most common perspective products.
Furthermore, even for the first time users wearing glasses with progressive-power lenses, the difference between the above three types is difficult to understand at first glance. Therefore, there has been a demand for a method for appropriately evaluating the lens characteristics of the progressive power lens.
Here, as an evaluation method, it is conceivable to perform by subjectively evaluating and analyzing how a large number of people actually feel the lens when wearing the monitor.
However, because there are so many products in the market, it can be very expensive and time consuming to monitor and evaluate all the products that are released with a sufficiently large number of people. In addition, it is difficult for anyone to evaluate subtle differences in wearing feeling in an easily understandable manner, and it is particularly difficult to perform quantitative evaluation (numerical evaluation). At best, it is based on psychological evaluation values and cannot be obtained as objective measurement values. In addition, there is also a problem that wearers are switched when evaluating a monitor for a large number of people over a long period of time (even with the same person, the state of the eye changes as presbyopia progresses over time). Therefore, an objective method has been demanded as an evaluation method.
It can be said that it is appropriate to use data obtained by mechanical measurement as an objective method. For example, it cannot be said that evaluation based on the result of measurement using a mapping measurement apparatus as disclosed in Patent Document 1 is impossible.
JP 2006-267109 A

However, although such a mapping measuring apparatus can qualitatively explain the relative difference between the two products, it cannot easily and easily explain how much the difference is. For example, I don't know if the two are the most different bipolars of all the products on the market, or if there are many much different products. To know it, you need to measure other products and compare a lot of data.
Furthermore, even if such a lot of mapping measurement data is compared, it is very difficult to judge the characteristics of each product accurately unless you are a specialist in product development of progressive-power lens products. difficult. In addition, there is room for subjectivity when explaining the characteristics of a product based on the obtained data, and it cannot be said that it is completely objective. Therefore, an easy-to-understand expression method that can be easily understood by many people who handle progressive-power lenses, including ophthalmologists and eyeglass stores, and a method for evaluating the characteristics of progressive-power lenses based on objective numerical values Was demanded.
The present invention has been made paying attention to such problems existing in the prior art. The object is to provide a method for displaying the lens characteristic distribution of a progressive-power lens that can objectively evaluate the difference in characteristics between the lens and other lenses.

In order to solve the above-mentioned problem, in the invention of claim 1, a first refraction region for viewing a relatively far distance disposed above the lens, and a first refraction region disposed below the first refraction region. A method for displaying a lens characteristic distribution of a progressive power lens having a second refractive region having a refractive power larger than that of the refractive region, and a progressive region that is disposed between these regions and in which the refractive power gradually changes, While setting one or more quantitative scales as an index of lens selection, one or more quantified for each lens by analyzing the lens surface shape transition state of a plurality of lenses based on a predetermined characteristic evaluation index The lens characteristic data is calculated, a relative evaluation value for each lens is determined for each lens based on the obtained lens characteristic data, and the result is displayed based on the relationship with the scale. The summary and That.
In the invention of claim 2, in addition to the configuration of the invention of claim 1, the lens characteristic data is approximated in the form of a linear combination of vectors as Xi of the following equation, and the evaluation value is expressed by the following equation: The gist is that it is determined by the coefficient kij.

The gist of the invention of claim 3 is that, in addition to the configuration of the invention of claim 1 or 2, the scale is set before the evaluation value is determined.
Further, in the invention of claim 4, in addition to the configuration of the invention of any one of claims 1 to 3, the evaluation value derives a covariance matrix or a correlation matrix based on the lens characteristic data, and an eigenvector of the determinant is obtained. The gist is that a principal component corresponding to the eigenvector is calculated and determined as a position on the principal component.
Further, in the invention of claim 5, in addition to the configuration of the invention of any one of claims 1 to 4, one of the scales is characterized by a strong average power below the lens and on the side of the distance portion. .
Further, in the invention of claim 6, in addition to the configuration of the invention of any one of claims 1 to 4, one of the scales has a large astigmatism on the side of the distance portion.
In addition, in the invention of claim 7, in addition to the structure of the invention of any one of claims 1 to 4, one of the scales is that the rise of addition is strong and the bottom of the lens is progressive. And
Further, in the invention of claim 8, in addition to the configuration of the invention of any one of claims 1 to 4, one of the scales has astigmatism concentrated on the side of the middle and near portions and side of the distance portion. The main point is that the astigmatism is small.

In addition, in the invention of claim 9, in addition to the configuration of the invention of any one of claims 1 to 8, each of the lenses displayed based on the relationship with the scale has a relative position with other lenses. Its gist is that it is determined, charted and displayed.
Further, in the invention of claim 10, in addition to the configuration of the invention of claim 9, the first axis direction is set as a predetermined first scale, and the second axis direction intersecting with the first axis is set as a predetermined value. The second scale is displayed on a two-dimensional plane represented by both axes, while the first and second scales are used as principal components calculated based on different lens characteristic data. This is the gist.
In addition, in the invention of claim 11, in addition to the structure of the invention of claim 10, the first scale and the second scale mainly include astigmatism data or average power data as the lens characteristic data. Its gist is that it is a component.
Further, in the invention of claim 12, in addition to the configuration of the invention of claim 1, in addition to setting data acquisition positions of a plurality of elements in the analysis region in order to calculate the lens characteristic data, each lens If there is a difference in the data acquisition position, the gist is to obtain the value of the element at the common position of each lens by interpolation calculation in order to correct the difference in the position.

In the configuration as described above, it is necessary to set one or more quantitative scales as an index for lens selection. The scale setting timing may be performed before calculating the following evaluation value, or may be performed based on the evaluation value calculation result.
Here, the scale refers to a more specific state of the lens shape determined based on a characteristic evaluation index for determining lens characteristics such as power of the lens surface, astigmatism, axial direction of astigmatism, and prism, for example. It is a standard.
For example, as a measure of average frequency,
1) Subscription spreads to the side of the far field.
2) The rise of joining is strong from the distance area to the intermediate area, and it progresses below the near area.
3) In the lower half area of the entire lens, the added area is widely distributed.
It is evaluated by the difference in the state of frequency distribution.
For example, as a measure of astigmatism,
1) Aberration is dispersed to the side of the distance area.
2) There is a large aberration concentration on the side of the near-use area.
3) The aberration near the distance eye point is small.
It is evaluated by the difference in the state of astigmatism distribution.
The operator sets a scale corresponding to the characteristic evaluation index for determining the lens characteristic. Basically, any number of scales can be used.

Next, the transition state of the lens surface shapes of the plurality of lenses is analyzed based on a predetermined characteristic evaluation index, and lens characteristic data quantified for each lens is calculated. This step is the first calculation step. “To analyze the lens surface shape transition state based on a predetermined characteristic evaluation index” means, for example, the lens surface power, astigmatism, axial direction of astigmatism, and a characteristic evaluation index such as a prism. In other words, the lens characteristics are analyzed as they are, or the data are directly or combined or converted, and as a result, numerically expressed lens characteristic data is calculated for each lens.
Here, it is preferable that the elements constituting the lens characteristic data are obtained by uniformly plotting the entire area of the lens surface. In that case, interpolation calculation is appropriately performed for the region connecting the elements.
In addition, in order to calculate lens characteristic data, data acquisition positions of multiple elements are set in the analysis region, and if there is a measurement error at the corresponding data acquisition position of each lens, interpolation calculation is performed to correct the measurement error. This is preferable for obtaining accurate data.
Next, a relative evaluation value with respect to another lens is determined for each lens based on the obtained lens characteristic data, and a relative position for each lens of the same evaluation value is calculated for a predetermined scale. This step is defined as a second calculation step. That is, although the lens characteristic data is data representing the characteristics of each lens, it is difficult to understand how the shape differs from other lenses. The lens characteristic data thus obtained is processed, and the lens is appropriately weighted with respect to the above scale, and an evaluation value for a predetermined scale is determined for each lens. Then, the result is displayed. As the display means, it is easy to understand that each lens determines a relative position with respect to another lens and charts it, but it is also possible to display the calculation data of the evaluation value as a numerical value as it is.

  The evaluation value is not particularly limited as long as it is a calculation method in which a difference according to the lens characteristic data for each lens is objectively recognized. For example,

The evaluation value represented by can be considered. The above equation is a concept that approximates the lens characteristic data Xi of each lens in the form of a linear combination of vectors.
In the same expression, the decorative letter C representing a vector in the same formula is (average frequency of product P _i + average frequency of product P _j ) / 2 or (astigmatism of product P _k + astigmatism of product P ₁ ) in Example 1 below. In the second embodiment, a vector obtained by calculating one average value corresponds to each of 349 columns.
In addition, the decorative character A representing a vector in the same equation corresponds to a vector (average frequency of P _i -average frequency of P _j ) or a vector (astigmatism of P _k -P ₁ astigmatism) in Example 1 below. In the second embodiment, each element of the eigenvector 349 is multiplied by the standard deviation of each column of the data matrix 349 before standardization.
It is also possible to calculate an evaluation value using principal component analysis. That is, the eigenvector is calculated based on the lens characteristic data, and the evaluation value is obtained as the position on the principal component corresponding to the eigenvector.
A principal component is obtained by using principal component analysis. This can be taken as a scale. Since a plurality of principal components are obtained, it is possible to select a principal component according to a desired scale. More specifically, for example, the main component when the average power data is used as the lens characteristic data can be applied to the same scale, for example, the main component when the astigmatism data is used as the lens characteristic data. It is possible to apply to the same scale.
As a scale corresponding to the obtained main component, for example, “the power in the lower part of the lens and the side of the distance portion is strong” can be cited.
As another suitable scale, for example, “the aberration on the side of the distance portion is large” can be cited.
As another suitable measure, for example, “the rise of the addition is strong and the lens rises at the bottom of the lens” can be cited.
As another suitable scale, for example, “the aberration is concentrated on the side of the middle and near portions and the aberration on the side of the distance portion is small” can be cited.

In addition, the principal component analysis is used to calculate the evaluation value, the relative position of the obtained evaluation value for each lens is calculated, and when the result is displayed on the chart, the first axial direction is selected. While displaying as a predetermined first scale and a second axis direction intersecting with the first axis as a predetermined second scale on a two-dimensional plane expressed by both axes, the first scale It is preferable that the second scale is a principal component calculated based on different lens characteristic data.
Specifically, for example, as a main measure when astigmatism data is adopted as lens characteristic data as the first scale, an evaluation value based on the astigmatism data is arranged in the first axial direction, and the second scale is used. It is conceivable that the average power data is adopted as the main component when the lens power data is used, and the average power data is used in the second axial direction.

  In the inventions of the above claims, the difference in characteristics between the lens and other lenses can be objectively evaluated.

Hereinafter, specific embodiments will be described with reference to the drawings.
First, an outline of a peripheral device for executing the lens characteristic distribution display method will be described with reference to FIGS.
FIG. 1 is a schematic block diagram of an apparatus for realizing the characteristic distribution display method of the present invention. The evaluation value calculating computer 1 is connected to a power distribution measuring device 2 for measuring the power distribution of the test lens. Note that the evaluation value calculating computer 1 and the frequency distribution measuring device 2 do not necessarily have to be directly connected as in the case of LAN connection, and conversely, the computer 1 and the frequency distribution measuring device 2 may be integrated. Further, the data obtained by measuring the frequency distribution is not limited to the LAN, and may be transferred to the evaluation value calculating computer 1 using a data storage device (including a medium such as a flexible disk or a USB memory).
Further, a monitor 7 as an output means and a keyboard 7 as an input means for inputting lens data of the analysis target lens 5 are connected. Examples of the output means include an output means for transferring data to a printer and other devices in addition to the monitor 3. In addition to the keyboard 7, the input means includes a two-dimensional code such as a bar code, a means for inputting data transferred from another device such as another computer or data storage device connected via a LAN, and the like.
The frequency distribution measuring apparatus 2 includes a light source 10, a beam splitter 11, a screen 12, and a CCD camera 13 as shown in FIG. An analysis device 14 is connected to the CCD camera 13. The analysis target lens 5 is disposed between the light source 10 and the beam splitter 11. The light source 10 emits parallel light rays toward the beam splitter 11. A plurality of through holes arranged in an orderly manner are formed in the beam splitter 11, and light rays (light beams) that have passed through the through holes are projected onto the screen 12. This projected light spot is used as a mapping point. The CCD camera 13 captures an image of the mapping point projected on the screen 12.
The analysis device 14 calculates the optical characteristics of the lens 5 to be analyzed based on the positional displacement of the light beam captured by the CCD camera 13 with respect to each through-hole position with the corresponding through-hole. The analysis device 14 is provided with a memory 15 as a storage unit, and stores lens characteristic data (S frequency data, C frequency data, astigmatism axis data, prism data) of the analysis target lens 5 obtained by calculation.

In this example, specific data was obtained for the analysis target lens 5 as follows.
Assuming a circle with a diameter of 50 mm centered 2 mm below the fitting point, the average power (S + C / 2) and astigmatism (absolute value of C) on lattice points every 2.5 mm in length and width were measured. Points inside and outside the circle with a diameter of 50 mm were used, and the number of grid points used was 349 out of 21 × 21 = 441 points. As a result, a total of 698 data values of 349 in average power and 349 as astigmatism are obtained.
3 (a) and 3 (b) are respectively obtained for the average power and astigmatism as lens characteristic data of the lens 5 to be analyzed having a distance power of 0.00D (so-called upper flat lens) and an addition power of 2.00D. FIG. 6 is a composite diagram in which the data values are superimposed on the mapped positions.
Incidentally, since the mapping points projected on the screen 12 are refracted according to the lens characteristics of each lens, the mapping points are not actually arranged irregularly and orderly as shown in FIG. For this reason, there is no law at the data setting position, so handling is inconvenient. Therefore, interpolation calculation is performed for each mapping point so that the mapping points are regularly arranged at the crossing positions of the grid as shown in FIG. Interpolation calculation is performed by known spline interpolation or higher order polynomials.

Example 1
In the first embodiment, a method of charting a plurality of progressive-power lenses having different characteristics based on data values obtained by using the frequency distribution measuring device 2 will be described.
<Evaluation of distance between each lens data>
First, data is obtained for the average power and astigmatism as described above for each of the products P _{1 to} P _n ( _n : natural number). Here, the obtained data is expressed as follows. For each product P _{1 to} P _n , the distance power is 0.00D (so-called upper flat lens) and the addition power is 2.00D.
Of the average frequency of the product P _{1 data: P 1 X 1, P 1} X 2, P 1 X 3 ··· P 1 X 349
Average frequency data of the product P ₂ : P ₂ X ₁ , P ₂ X ₂ , P ₂ X ₃ ... P ₂ X ₃₄₉
・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・
Average frequency data of the product P _n : P _n X ₁ , P _n X ₂ , P _n X ₃ ... P _n X ₃₄₉
Astigmatism product P _{1 Data: P 1 Y 1, P 1} Y 2, P 1 Y 3 ··· P 1 Y 349
Astigmatism data of product P ₂ : P ₂ Y ₁ , P ₂ Y ₂ , P ₂ Y ₃ ... P ₂ Y ₃₄₉
・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・
Data of astigmatism of product P _n : P _n Y ₁ , P _n Y ₂ , P _n Y ₃ ... P _n Y ₃₄₉

<Determination of scale>
Next, two products are selected from the products P _{1 to} P _n for the purpose of measuring the average power and astigmatism.
Here, regarding the average frequency, the difference between the product P _i and the product P _j is a first measure. For astigmatism, the difference between product P _k and product P _l is the second measure ( _{i, j, k, l} are natural numbers, where _i and _j are different, and _k and _l are different) To do.)
<Determination of evaluation value>
The average frequency is defined as the distance between data (so-called Euclidean distance) by taking the square root of the difference between the corresponding elements of P _i and P _j for all products and adding all the obtained values.
Specifically, for example, when P _i = P ₁ and P _j = P ₂ , the inter-data distance is obtained as follows.

Then, based on the distances between the data obtained between the products P _{1 to} P _n and the products P _i and P _j , the products P _{1 to} P _n are “distance from the product P _i ” and “product P _j. It is calculated how close it is to "distance". For example, if the distance between P _{1 and} P _i : the distance between P _{1 and} P _j = 1: 1, it is considered that the product P ₁ has an intermediate characteristic between the product P _i and the product P _j . Further, if the distance between P _{2 and} P _i : the distance between P _{2 and} P _j = 4: 1, the product P ₂ is considered to be close to the product P _j .

That is, where the products P _{1 to} P _n are located on the straight line L in relation to the points mi and mj where the perpendicular drawn from the products P _i and P _j to the predetermined straight line L intersects the straight line L. determining a other words have unique weights based on product P ₁ to P _n to the data distance (scalar quantity), the product P ₁ to P _n at a position corresponding to the weight in the vector direction of the first measure Can be considered. If this is an approximate general formula, it can be expressed as follows.
Average frequency of P _n ≒
(Average frequency of P _i + average frequency of P _j ) / 2 + coefficient _An × (average frequency of P _i −average frequency of P _j ) vector Similarly, the products P _{1 to} P _n and the product P _k are astigmatism. and to weight similarly measured with respect to the data distance between product P _l. As a general formula, it can be expressed as follows.
Astigmatism of P _n ≒
(Astigmatism astigmatism -P _l of _{P k)} vector _(P astigmatism astigmatism + _{P l} of _k) / 2 + coefficients B _n ×

FIG. 5 is an example of a chart in which products P _{1 to} P _n are arranged in a plane when the first scale for the average power is on the horizontal axis and the second scale for astigmatism is on the vertical axis. . The origin in FIG. 5 is the average of P ₁ and P ₂ for the average power, and the average of P ₃ and P ₄ for astigmatism. The first scale is defined as a vector defined as the difference between the average frequencies of the products P ₁ and P ₂ , and the second scale is defined as the astigmatism difference between the products P ₃ and P _4. Selected vector. Home position the midpoint of transverse rated value of product P ₁ and the product P _2, the vertical direction is the midpoint of the evaluation value of the product P ₃ and the product P _4.

(Example 2)
In the second embodiment as well, a method for charting a plurality of progressive-power lenses having different characteristics based on data values obtained by using the frequency distribution measuring apparatus 2 will be described. In the second embodiment, the scale is obtained using principal component analysis.
In this example, as shown in Table 1, 349 pieces of data regarding the average power and astigmatism were collected using a total of 40 types of lenses as the analysis target lens 5, respectively. The obtained data can be expressed as a data matrix as shown in FIG. In FIG. 6, j is a predetermined row and k is a column.

<Standardization of data for each lens>
First, standardize the data values obtained. Hereinafter, a specific calculation example will be described for the data of the average power, but the same operation is performed for astigmatism.
Considering 349 sets of average frequency data at a common position for each lens (one set consists of 40 pieces of data), the average and standard deviation of the numerical values of 349 sets are obtained. Specifically, an average is first obtained from the numerical values of each lens, the difference from each data is squared and summed, and this is divided by (40-1 = 39) to obtain the variance. The square root of this value is taken as the standard deviation. The general formula is as follows. And for 349 sets of average frequency data at a common position (one set consists of 40 data), the data is obtained by subtracting the average value of each set from each of the 40 sets of data and dividing by the standard deviation of each set. Standardize the matrix.

<Calculation of covariance matrix>
The j-by-k element of the covariance matrix is calculated based on the standardized data matrix. This is a standardized data matrix,
1) 1 row multiplied by j column element and k column element 2) 2 rows multiplied by j column element and k column element 3) i row j column element multiplied by k column element It is obtained by calculating the sum of things.
Generally speaking, as shown in FIG. 7, a product of the j column element and the k column element of a certain row is added to all the rows.
This operation is performed by an algorithm as shown in FIG. In FIG. 8, a two-dimensional array xd [] [] represents an element of the data matrix of FIG. A two-dimensional array a [] [] represents an element of a covariance matrix. nn is the number of data, and is 40 in the embodiment. np is the number of data elements, and is 349 in the embodiment.
In this algorithm, elements of j rows and k columns are obtained in order from the top along the arrows in the figure as shown in FIG. Since it is a diagonal matrix, when obtaining an element of j rows and k columns, an element of k rows and j columns is simultaneously determined (same value).

<Calculation of principal components based on eigenvalues>
The eigenvalue is obtained by calculating the covariance matrix. Similarly, eigenvalues are obtained for astigmatism. The average power and the astigmatism eigenvalue for each main component (up to the fourth main component) in this example are as shown in Table 2 below.

<Determination of scale>
Several specific measures as shown in Table 3 are deduced for the average power and astigmatism from the principal component. These are measures of typical differences in the properties of mean power and astigmatism, and other measures are free to use.

Further, eigenvectors of 349 data for the average power and astigmatism are obtained based on the eigenvalues, and a principal component score corresponding to the principal component is calculated for each lens. In the second embodiment, the correspondence is as follows: first scale → first principal component, second scale → second principal component, third scale → third principal component.
FIG. 10 shows an example in which the horizontal axis is a first scale of average power and the vertical axis is a first scale of astigmatism. The scale of the vertical axis and the horizontal axis can be changed as appropriate. FIG. 11 is a composite diagram in which the values of the eigenvectors of the first principal component of average power are superimposed on the mapped positions, and FIG. 12 is superimposed on the positions of the mapped eigenvector values of the first principal component of astigmatism. FIG. In the figure, the numerical value is shown multiplied by 100 to reduce the number of written digits.
In FIG. 10, the vertical axis represents a relative difference depending on a difference in distance between the 40 types of lenses and other lenses on a scale of “aberration is more dispersive toward the upper side”. The horizontal axis direction represents a relative difference depending on a difference in distance from the other lenses of the 40 types of lenses on a scale of “the power is dispersed laterally in the distance”. In FIG. 10, the lenses of company B can be grouped as a group of properties that are close to each other (not much changed) as surrounded by a broken line in light of the first and second scales.

It should be noted that the present invention can be modified and embodied as follows.
In the first embodiment and the second embodiment, an example is illustrated in which the scale of 1 or 2 is represented in a planar manner. However, a larger number of scales may be represented simultaneously.
In the first embodiment, the evaluation values are calculated separately for the average power and astigmatism. However, only one evaluation value may be obtained by setting each of 349 × 2 = 698 number sequences as one set. Absent.
-In Example 2, the vertical axis direction is "the aberration disperses in the distance toward the upper side", and the horizontal axis direction is "the lens characteristic distribution is plotted on the scale that the power is dispersed in the distance side". These scales may be arranged on the vertical axis and the horizontal axis.
In Example 2, the vertical axis is a chart that sets the scale of average power and the horizontal axis is the scale of astigmatism (that is, a scale based on different characteristic evaluation indices). You may chart on the scale based on the same characteristic evaluation index.
-In Example 2, the prescription was calculated from the obtained main component, but once the prescription is obtained in this way, it should be used as a prescription that presupposes this result as a prescription for the subsequent progressive-power lens. Is possible.
In FIG. 10 of the second embodiment, the characteristic distribution is represented by a display method in which scales in two directions are plotted on one plane. However, a display method in which only one scale is charted may be used.
In the second embodiment, it is possible to use a correlation matrix in addition to the covariance matrix as a solution for the principal component analysis. As a calculation method, it is also possible to use a varimax method or a Jacobian method.
In each of the above embodiments, the average power and astigmatism are employed as the lens characteristics, but other lens characteristics may be employed.
The conditions such as the number of data to be obtained and the distribution interval and distribution area of data on the analysis target lens 5 can be appropriately changed.
In addition, it is free to implement in a mode that does not depart from the spirit of the present invention.

1 is a schematic block diagram of an apparatus for carrying out the present invention. The conceptual diagram of a frequency distribution measuring apparatus. (A) is a composite diagram in which the data values obtained for the average power as lens characteristic data of the lens to be analyzed are superimposed on the mapped position, and (b) is the position where the data values obtained for astigmatism are also mapped. Superposed composite diagram. (A) is expansion explanatory drawing of the mapped light spot, (b) is explanatory drawing of the state which rearranged the light spot orderly by interpolation calculation. A scatter diagram in which products P _{1 to} P _n are arranged in a plane when the first scale for average power is taken on the horizontal axis and the second scale for astigmatism is taken on the vertical axis. Explanatory drawing explaining expressing with the matrix format of the data extract | collected about the lens and each lens. Explanatory drawing explaining the method of calculating a covariance matrix based on the standardized data matrix. Explanatory drawing explaining the algorithm of calculation of a covariance matrix. Explanatory drawing explaining the process which calculates the element of a covariance matrix. FIG. 5 is a lens characteristic diagram in which test lenses given weights based on evaluation values are arranged on a plane with the horizontal axis as a first scale of average power and the vertical axis as a first scale of astigmatism. The composite figure which piled up the value of the eigenvector of the 1st principal component of average frequency on the mapped position. The composite figure which piled up the value of the eigenvector of the 1st principal component of astigmatism at the mapped position.

Claims (12)

A first refracting region disposed above the lens for viewing relatively far away, and a second refracting region disposed below the first refracting region and having a refractive power greater than that of the first refracting region. And a method for displaying a lens characteristic distribution of a progressive power lens having a progressive region that is disposed between these regions and in which the refractive power gradually changes,
While setting one or more quantitative scales as an index of lens selection, one or more quantified for each lens by analyzing the lens surface shape transition state of a plurality of lenses based on a predetermined characteristic evaluation index The lens characteristic data is calculated, a relative evaluation value for each lens is determined for each lens based on the obtained lens characteristic data, and the result is displayed based on the relationship with the scale. A method for displaying a lens characteristic distribution of a progressive-power lens, characterized by comprising: 2. The progressive power according to claim 1, wherein the lens characteristic data is approximated in the form of a linear combination of vectors as Xi of the following formula, and the evaluation value is determined by a coefficient kij of the following formula. Lens characteristic distribution display method for lenses.

3. The method for displaying a lens characteristic distribution of a progressive power lens according to claim 1, wherein the scale is set before the evaluation value is determined. The evaluation value is obtained as a position on the principal component by deriving a covariance matrix or correlation matrix based on the lens characteristic data, calculating an eigenvector of the determinant to determine a principal component corresponding to the eigenvector. The method for displaying a lens characteristic distribution of a progressive-power lens according to claim 1, wherein: 5. The method for displaying a lens characteristic distribution of a progressive power lens according to claim 1, wherein one of the scales has a strong average power at the lower side of the lens and the side of the distance portion. 5. The method of displaying a lens characteristic distribution of a progressive power lens according to claim 1, wherein one of the scales is a large astigmatism on the side of the distance portion. One of the scales is that the rise of the addition is strong and the addition occurs at the lower part of the lens, and the method for displaying the lens characteristic distribution of the progressive power lens according to any one of claims 1 to 4. 5. The scale according to claim 1, wherein one of the scales is that the astigmatism is concentrated on the side of the middle and near portions and the astigmatism on the side of the distance portion is small. Lens characteristic distribution display method for progressive-power lenses. 9. Each of the lenses displayed based on a relationship with a scale is displayed with a relative position determined with respect to other lenses determined and displayed. Lens characteristic distribution display method for progressive-power lenses. The first axis direction is set as a predetermined first scale, and the second axis direction intersecting with the first axis is displayed as a predetermined second scale on a two-dimensional plane expressed by both axes. 10. The method of claim 9, wherein the first scale and the second scale are used as principal components calculated based on different lens characteristic data. The progressive power lens according to claim 10, wherein the first scale and the second scale are main components when astigmatism data or average power data is adopted as the lens characteristic data. Lens characteristic distribution display method. In order to calculate the lens characteristic data, a data acquisition position of a plurality of elements is set in the analysis region. 12. The method for displaying a lens characteristic distribution of a progressive power lens according to claim 1, wherein the value of the element at the common position is obtained by interpolation calculation.

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