Farnsworth B-20 cap colors

Description

B20 contains the cap colors for the Farnsworth B-20 test, in XYZ coordinates. The Farnsworth B-20 is a short test for detecting congenital color vision deficiencies.

Usage

B20

Format

This data frame contains the following columns:

CapNo

Cap Number

Munsell

Munsell color

X

CIE X cap color

Y

CIE Y cap color

Z

CIE Z cap color

Author(s)

Jose Gama

Source

Judd, D.B. and MacAdam, D.L., 1979 Contributions to Color Science University of Rochester. Institute of Optics and Center for Building Technology Department of Commerce, National Bureau of Standards

References

Judd, D.B. and MacAdam, D.L., 1979 Contributions to Color Science University of Rochester. Institute of Optics and Center for Building Technology Department of Commerce, National Bureau of Standards

Examples

data(B20)
B20

Table of color distance scores for quantitative scoring of the Farnsworth panel D-15 test

Description

BowmanTCDS contains the color distance scores for quantitative scoring of the Farnsworth panel D-15 test, from Bowman KJ (1982) The Farnsworth Dichotomous test (D-15) is a short test for detecting congenital color vision deficiencies. Bowman KJ (1982) created a table based on the Commission Internationale de l'Eclairage (International Commission on Illumination, CIE) Space and Color Difference formula, CIE 1976 (L*a*b*) with perceptual distances between pairs of caps. The table is used for the calculation of the Total Color Distance Score (TCDS) which is the sum of the CIELAB space distances between colored caps.

Usage

BowmanTCDS

Format

This data frame contains the following columns:

Pilot

Distances between colored caps for the pilot cap

Cap1

Distances between colored caps for the 1st cap

Cap2

Distances between colored caps for the 2nd cap

Cap3

Distances between colored caps for the 3rd cap

Cap4

Distances between colored caps for the 4th cap

Cap5

Distances between colored caps for the 5th cap

Cap6

Distances between colored caps for the 6th cap

Cap7

Distances between colored caps for the 7th cap

Cap8

Distances between colored caps for the 8th cap

Cap9

Distances between colored caps for the 9th cap

Cap10

Distances between colored caps for the 10th cap

Cap11

Distances between colored caps for the 11th cap

Cap12

Distances between colored caps for the 12th cap

Cap13

Distances between colored caps for the 13th cap

Cap14

Distances between colored caps for the 14th cap

Cap15

Distances between colored caps for the 15th cap

Author(s)

Jose Gama

Source

Bowman KJ: A method for quantitative scoring of the Farnsworth panel D-15. Acta Ophthalmol 60:907, 1982.

References

Bowman KJ: A method for quantitative scoring of the Farnsworth panel D-15. Acta Ophthalmol 60:907, 1982.

Examples

data(BowmanTCDS)
BowmanTCDS

Daltonize images

Description

Color.Vision.Daltonize converts images so that the most problematic colors are more visible to people with CVD.

Usage

Color.Vision.Daltonize(fileIN=NULL, fileOUT=NULL, myoptions=NULL, amount=1.0)

Arguments

Value

none

Author(s)

Jose Gama

References

Michael Deal Daltonize.org http://mudcu.be/labs/Color/Vision http://www.daltonize.org/p/about.html "Analysis of Color Blindness" by Onur Fidaner, Poliang Lin and Nevran Ozguven. "Digital Video Colourmaps for Checking the Legibility of Displays by Dichromats" by Francoise Vienot, Hans Brettel and John D. Mollon http://vision.psychol.cam.ac.uk/jdmollon/papers/colourmaps.pdf

Examples

# a "perfect" score
## Not run: 
fname<-paste(system.file(package='CVD'),'/extdata/fruits.png',sep='')
Color.Vision.Daltonize(fname, 'fruits.Daltonize.Protanope.png','Protanope')
Color.Vision.Daltonize(fname, 'fruits.Daltonize.Deuteranope.png','Deuteranope')
Color.Vision.Daltonize(fname, 'fruits.Daltonize.Tritanope.png','Tritanope')

## End(Not run)

Simulate CVDs on images

Description

Color.Vision.Simulate converts images so that the colors look similar to how they are seen by people with CVD.

Usage

Color.Vision.Simulate(fileIN=NULL, fileOUT=NULL, myoptions=NULL, amount=1.0)

Arguments

Value

none

Author(s)

Jose Gama

References

Michael Deal Daltonize.org http://mudcu.be/labs/Color/Vision http://www.daltonize.org/p/about.html "Analysis of Color Blindness" by Onur Fidaner, Poliang Lin and Nevran Ozguven. "Digital Video Colourmaps for Checking the Legibility of Displays by Dichromats" by Francoise Vienot, Hans Brettel and John D. Mollon http://vision.psychol.cam.ac.uk/jdmollon/papers/colourmaps.pdf

Examples

# a "perfect" score
## Not run: 
fname<-paste(system.file(package='CVD'),'/extdata/fruits.png',sep='')
Color.Vision.Simulate(fname, 'fruits.Simulate.Protanope.png','Protanope')
Color.Vision.Simulate(fname, 'fruits.Simulate.Deuteranope.png','Deuteranope')
Color.Vision.Simulate(fname, 'fruits.Simulate.Tritanope.png','Tritanope')

## End(Not run)

Scoring the results of the "D-15", "D-15DS" or "FM1OO-Hue" tests

Description

Color.Vision.VingrysAndKingSmith takes a vector with cap numbers from the "D-15", "D-15DS" or "FM1OO-Hue" tests and outputs the score by the method from Vingrys and King-Smith.

Usage

Color.Vision.VingrysAndKingSmith(capnumbers=NULL,testType='D-15',silent=TRUE)

Arguments

Value

Author(s)

Jose Gama

References

Vingrys, A.J. and King-Smith, P.E. (1988). A quantitative scoring technique for panel tests of color vision. Investigative Ophthalmology and Visual Science, 29, 50-63.

Examples

Color.Vision.VingrysAndKingSmith(1:15,silent=FALSE)
#result from the original GW Basic version:
#SUMS OF U AND V              41.25999     -4.92
# ANGLE MAJ RAD MIN RAD TOT ERR S-INDEX C-INDEX
#    61.98     9.23     6.71    11.42     1.38     1.00
Color.Vision.VingrysAndKingSmith(1:15,'D-15DS',silent=FALSE)
#result from the original GW Basic version:
#SUMS OF U AND V              26.86001     -38.69
# ANGLE MAJ RAD MIN RAD TOT ERR S-INDEX C-INDEX
#    61.44     5.12     3.60     6.26     1.42     1.00
Color.Vision.VingrysAndKingSmith(1:85, 'FM1OO-Hue',silent=FALSE)
#result from the original GW Basic version:
#SUMS OF U AND V              423.7896      203.7294
# ANGLE MAJ RAD MIN RAD TOT ERR S-INDEX C-INDEX
#    54.15     2.53     1.97     3.20     1.28     1.00

Decolorize an image using the c2g algorithm

Description

Color.Vision.c2g decolorizes an image using the c2g algorithm from Martin Faust (2008). RGBtoHSL converts from RGB to HSL, used by Color.Vision.c2g

Usage

Color.Vision.c2g(fileIN=NULL, fileOUT=NULL, CorrectBrightness=FALSE)

Arguments

Value

none

Author(s)

Jose Gama

References

Martin Faust 2008 http://www.e56.de/c2g.php

Examples

## Not run: 
fname<-paste(system.file(package='CVD'),'/extdata/fruits.png',sep='')
Color.Vision.c2g(fname, 'fruits.c2g.png')

## End(Not run)

Quantitatively analyzes of D15 color panel tests

Description

D15Foutch Calculates angle, magnitude and scatter for VK-S 88 and VK-S 93 (Vingrys, A.J. and King-Smith, P.E. (1988, 1993)), LSA 05 (Foutch/Bassi '05), and JMO 11 (Foutch/Stringham/Vengu '11).

Usage

D15Foutch(userD15values=NULL, testType = 'D-15', dataVKS = NA)

Arguments

Value

Author(s)

Brian K. Foutch

References

A new quantitative technique for grading Farnsworth D-15 color panel tests Foutch, Brian K.; Stringham, James M.; Lakshminarayanan, Vasuvedan Journal of Modern Optics, vol. 58, issue 19-20, pp. 1755-1763

Evaluation of the new web-based" Colour Assessment and Diagnosis" test J Seshadri, J Christensen, V Lakshminarayanan, CJ BASSI Optometry & Vision Science 82 (10), 882-885

Vingrys, A.J. and King-Smith, P.E. (1988). A quantitative scoring technique for panel tests of color vision. Investigative Ophthalmology and Visual Science, 29, 50-63.

Examples

# 2 examples from VK-S
## Not run: 
D15Foutch(userD15values=c(1:7,9,8,10:15))
D15Foutch(userD15values=c(1:7,9,8,10:13,15,14))
## End(Not run)

Farnsworth D-15 cap colors

Description

FarnsworthD15 contains the cap colors for the D-15 tests, in CIELab and RGB from Farnsworth D (1947) The Farnsworth Dichotomous test (D-15) is a short test for detecting congenital color vision deficiencies.

Usage

FarnsworthD15

Format

This data frame contains the following columns:

CapNo

Cap Number

Munsell

Munsell color

x.C

CIE x cap color

y.C

CIE y cap color

R

R channel cap color

G

G channel cap color

B

B channel cap color

Author(s)

Jose Gama

Source

Farnsworth D. The Farnsworth Dichotomous Test for Color Blindness Panel D-15 Manual. New York, The Psychological Corp., 1947, pp. 1-8.

References

Farnsworth D. The Farnsworth Dichotomous Test for Color Blindness Panel D-15 Manual. New York, The Psychological Corp., 1947, pp. 1-8.

Examples

data(FarnsworthD15)
FarnsworthD15

Farnsworth D-15 cap colors

Description

FarnsworthMunsell100Hue contains the cap colors for the Farnsworth Munsell 100-Hue tests, in CIELab and RGB from Farnsworth D (1957) The Farnsworth Munsell 100-Hue is a test for detecting congenital and acquired color vision deficiencies.

Usage

FarnsworthMunsell100Hue

Format

This data frame contains the following columns:

CapNo

Cap Number

Munsell

Munsell color

x.C

CIE x cap color

y.C

CIE y cap color

R

R channel cap color

G

G channel cap color

B

B channel cap color

Author(s)

Jose Gama

Source

Farnsworth D: The Farnsworth-Munsell 100-Hue Test for the Examination of Color Discrimination Manual. Baltimore, Munsell Color Co., 1957, pp. 1-7.

References

Farnsworth D: The Farnsworth-Munsell 100-Hue Test for the Examination of Color Discrimination Manual. Baltimore, Munsell Color Co., 1957, pp. 1-7.

Examples

data(FarnsworthMunsell100Hue)
FarnsworthMunsell100Hue

Table of color distance scores for quantitative scoring of the Lanthony desaturate D-15s test

Description

GellerTCDS contains the color distance scores for quantitative scoring of the Lanthony desaturate D-15s test, from Geller AM. (2001). The Lanthony desaturate test (D-15s) is a short test for detecting acquired color vision deficiencies. Geller AM (2001) created a table based on the Commission Internationale de l'Eclairage (International Commission on Illumination, CIE) Space and Color Difference formula, CIE 1976 (L*a*b*) with perceptual distances between pairs of caps. The table is used for the calculation of the Total Color Distance Score (TCDS) which is the sum of the CIELAB space distances between colored caps.

Usage

GellerTCDS

Format

This data frame contains the following columns:

Pilot

Distances between colored caps for the pilot cap

Cap1

Distances between colored caps for the 1st cap

Cap2

Distances between colored caps for the 2nd cap

Cap3

Distances between colored caps for the 3rd cap

Cap4

Distances between colored caps for the 4th cap

Cap5

Distances between colored caps for the 5th cap

Cap6

Distances between colored caps for the 6th cap

Cap7

Distances between colored caps for the 7th cap

Cap8

Distances between colored caps for the 8th cap

Cap9

Distances between colored caps for the 9th cap

Cap10

Distances between colored caps for the 10th cap

Cap11

Distances between colored caps for the 11th cap

Cap12

Distances between colored caps for the 12th cap

Cap13

Distances between colored caps for the 13th cap

Cap14

Distances between colored caps for the 14th cap

Cap15

Distances between colored caps for the 15th cap

Author(s)

Jose Gama

Source

Geller AM. A table of color distance scores for quantitative scoring of the Lanthony desaturate color vision test. Neurotoxicol Teratol 2001; 23: 265-267.

References

Geller AM. A table of color distance scores for quantitative scoring of the Lanthony desaturate color vision test. Neurotoxicol Teratol 2001; 23: 265-267.

Examples

data(GellerTCDS)
GellerTCDS

Farnsworth H-16 cap colors

Description

H16 contains the cap colors for the Farnsworth H-16 test, in Yxy coordinates. The Farnsworth H-16 is a short test for detecting congenital color vision deficiencies.

Usage

H16

Format

This data frame contains the following columns:

CapNo

Cap Number

x.C

CIE x cap color

y.C

CIE y cap color

Munsell

Munsell color

ProductionNo

Munsell Production Number

Author(s)

Jose Gama

Source

Judd, D.B. and MacAdam, D.L., 1979 Contributions to Color Science University of Rochester. Institute of Optics and Center for Building Technology Department of Commerce, National Bureau of Standards

References

Judd, D.B. and MacAdam, D.L., 1979 Contributions to Color Science University of Rochester. Institute of Optics and Center for Building Technology Department of Commerce, National Bureau of Standards

Examples

data(H16)
H16

Farnsworth H-16 cap colors

Description

LanthonyD15 contains the cap colors for Lanthony D-15 test, in Yxy coordinates. The Lanthony D-15 (desaturated D-15) is a short test for detecting congenital color vision deficiencies.

Usage

LanthonyD15

Format

This data frame contains the following columns:

CapNo

Cap Number

Munsell

Munsell color

x.C

CIE x cap color

y.C

CIE y cap color

R

R channel cap color

G

G channel cap color

B

B channel cap color

Author(s)

Jose Gama

Source

Judd, D.B. and MacAdam, D.L., 1979 Contributions to Color Science University of Rochester. Institute of Optics and Center for Building Technology Department of Commerce, National Bureau of Standards

References

Judd, D.B. and MacAdam, D.L., 1979 Contributions to Color Science University of Rochester. Institute of Optics and Center for Building Technology Department of Commerce, National Bureau of Standards

Examples

data(LanthonyD15)
LanthonyD15

Roth-28 cap colors

Description

Roth28 contains the cap colors for the Roth-28 tests, in CIELab and RGB from Roth A (1966) The Roth-28 is a short test for detecting congenital color vision deficiencies.

Usage

Roth28

Format

This data frame contains the following columns:

CIEL

CIELab L channel cap color

CIEa

CIELab a channel cap color

CIEb

CIELab b channel cap color

R

R channel cap color

G

G channel cap color

B

B channel cap color

Author(s)

Jose Gama

Source

Roth A. Test-28 hue de Roth selon Farnsworth–Munsell (Manual). Paris: Luneau, 1966.

References

Roth A. Test-28 hue de Roth selon Farnsworth–Munsell (Manual). Paris: Luneau, 1966.

Examples

data(Roth28)
Roth28

Graphical score for the D-15 tests

Description

VKSgraphic computes a graphical score based on the Vingrys and King-Smith method (VKS) for the D-15 test or similar tests. VKSvariantGraphic shows the angles with double their value, for a continuous display of the confusion axis.

Usage

VKSgraphic(VKSdata, xLimit=5, yLimit=4, VKStitle='', VKSxlabel='',
VKSylabel='')

Arguments

Value

none

Author(s)

Jose Gama

Source

VKSvariantGraphic - original idea by David Bimler Atchison DA, Bowman KJ, Vingrys AJ Quantitave scoring methods for D15 panel tests in the diagnosis of congenital colour-vision deficiencies. Optometry and Vision Science 1991, 68:41-48.

References

Atchison DA, Bowman KJ, Vingrys AJ Quantitave scoring methods for D15 panel tests in the diagnosis of congenital colour-vision deficiencies. Optometry and Vision Science 1991, 68:41-48.

Examples

# Creating similar graphics to "A Quantitative Scoring Technique For Panel 
#Tests of Color Vision" Algis J. Vingrys and P. Ewen King-Smith
## Not run: 
VKSdata<-VKStable2[,c(1,3:5)]
VKSdata[1,1]<-'Normal no error'
VKSdata[2:9,1]<-'Normal'
VKSdata[10:13,1]<-'Acquired CVD'
# the graphics are similar but not identical because the data used in the 
#plots is the average of the values instead of all the values
VKSgraphic(VKSdata[,1:3],5,4,'D-15 angle vs C-index (Average)','Angle',
'C-index') # Fig. 6
VKSgraphic(VKSdata[,c(1,2,4)],5,4,'D-15 angle vs S-index (Average)','Angle',
'S-index') # Fig. 7

## End(Not run)

Table with results of D-15 tests scored with the Vingrys and King-Smith method

Description

VKStable2 contains tthe results of D-15 tests scored with the Vingrys and King-Smith method, from Vingrys and King-Smith (1988), table 2

Usage

VKStable2

Format

This data frame contains the following columns:

typeCVD

Type of color vision

sample

Number in sample

Angle

Angle

S.index

S-index

C.index

C-index

Major

Major radius

Minor

Minor radius

TES

TES

TCDS

TCDS

Author(s)

Jose Gama

Source

Atchison DA, Bowman KJ, Vingrys AJ Quantitave scoring methods for D15 panel tests in the diagnosis of congenital colour-vision deficiencies. Optometry and Vision Science 1991, 68:41-48.

References

Atchison DA, Bowman KJ, Vingrys AJ Quantitave scoring methods for D15 panel tests in the diagnosis of congenital colour-vision deficiencies. Optometry and Vision Science 1991, 68:41-48.

Examples

data(VKStable2)
VKStable2

Approximation of the scotopic luminance

Description

XYZ2scotopic.Rawtran approximates the scotopic luminance from XYZ values, illuminant D65, from Filip Hroch (1998). Used in the astronomy software Rawtran.

XYZ2scotopic.Rawtran.array idem, however the data type used is array.

Usage

XYZ2scotopic.Rawtran(XYZmatrix)

Arguments

Value

Matrix (or array) with approximated scotopic luminance.

Author(s)

Jose Gama

Source

Filip Hroch, 1998, Computer Programs for CCD Photometry, 20th Stellar Conference of the Czech and Slovak Astronomical Institutes, DusekJ., http://adsabs.harvard.edu/abs/1998stel.conf...30H Rawtran - integral.physics.muni.cz Masaryk University http://integral.physics.muni.cz/rawtran/

References

Filip Hroch, 1998, Computer Programs for CCD Photometry, 20th Stellar Conference of the Czech and Slovak Astronomical Institutes, DusekJ., http://adsabs.harvard.edu/abs/1998stel.conf...30H Rawtran - integral.physics.muni.cz Masaryk University http://integral.physics.muni.cz/rawtran/

Approximation of the scotopic luminance

Description

approx.scotopic.luminance.LarsonEtAl.RGB approximates the scotopic luminance from RGB values. approx.scotopic.luminance.LarsonEtAl.XYZ approximates the scotopic luminance from XYZ values.

Usage

approx.scotopic.luminance.LarsonEtAl.XYZ(XYZmatrix)
approx.scotopic.luminance.LarsonEtAl.RGB(RGBmatrix)

Arguments

Value

approximated scotopic luminance

Author(s)

Jose Gama

Source

Larson, G. W., H. Rushmeier, and C. Piatko (1997, October - December). A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Transactions on Visualization and Computer Graphics 3 (4), 291–306.

References

Larson, G. W., H. Rushmeier, and C. Piatko (1997, October - December). A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Transactions on Visualization and Computer Graphics 3 (4), 291–306.

Examples

## Not run: 
samplePics <- c('fruits', 'pastel_color', 'sample1', 'TurnColorsGrayImage1', 'TurnColorsGrayImage2')
for (pics in samplePics)
{
fname<-paste(system.file(package='CVD'),'/extdata/',pics,'.png',sep='')
imgTest<-loadPNG(fname)
imgTest.array<-approx.scotopic.luminance.LarsonEtAl.RGB.array(imgTest)
png::writePNG(imgTest.array, paste(pics, '.approx.scotopic.luminance.LarsonEtAl.RGB.png',sep=''))
}

## End(Not run)

Attenuation as a function of number of eyes

Description

attenuationNumberOfEyes computes the attenuation as a function M(e) of number of eyes e (1 or 2), from Watson A. B., Yellott J. I. (2012).

Usage

attenuationNumberOfEyes(e)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6.

Examples

## Not run: 
attenuationNumberOfEyes(1)
attenuationNumberOfEyes(2)

## End(Not run)

Generate points from a circle

Description

calculateCircle generates points from a circle with many options, equally spaced, randomly spaced, with noise added to the radius or limited to a segment of angle alpha.

Usage

calculateCircle(x, y, r, steps=50,sector=c(0,360),randomDist=FALSE, 
randomFun=runif,...)

Arguments

Value

Author(s)

Jose Gama

Examples

## Not run: 
# 100 points from a circle at c(0,0) with radius=200
a<-calculateCircle(0,0,200,100)
plot(a[,1],a[,2],xlim=c(-200,200),ylim=c(-200,200))
par(new=TRUE)
# 12 points from a circle at c(0,0) with radius=190, points between 0 and 90
# degrees
a<-calculateCircle(0,0,190,12,c(0,90))
plot(a[,1],a[,2],xlim=c(-200,200),ylim=c(-200,200),col='red')
par(new=TRUE)
# 12 points from a circle at c(0,0) with radius=180, points between 0 and 180
# degrees, uniform random distribution
a<-calculateCircle(0,0,180,12,c(0,180),TRUE)
plot(a[,1],a[,2],xlim=c(-200,200),ylim=c(-200,200),col='green')
par(new=TRUE)
# 12 points from a circle at c(0,0) with radius=170, points between 0 and 180
# degrees, normal random distribution
a<-calculateCircle(0,0,170,12,c(0,180),TRUE,rnorm)
plot(a[,1],a[,2],xlim=c(-200,200),ylim=c(-200,200),col='blue')

## End(Not run)

total error score (TES) using Farnsworth's or Kinnear's method

Description

calculateTES computes the total error score (TES) using Farnsworth's or Kinnear's method for the FM-100, D-15, Roth-28 and so forth. The input is a vector of cap positions.

Usage

calculateTES(fmData, Kinnear=FALSE)

Arguments

Value

Author(s)

Jose Gama

References

Farnsworth D. The Farnsworth-Munsell 100-Hue Test. Baltimore: Munsell Color Company, 1957.

Examples

# a "perfect" score
## Not run: 
calculateTES(userD15values=1:15)
## End(Not run)

Creates PNG files to be used as colored caps (buttons)

Description

createPNGbuttons creates PNG files from a data.frame with RGB values.

Usage

createPNGbuttons(capsData = get("FarnsworthD15", envir = environment()),
 imgLength = 44, imgWidth = 78)

Arguments

Value

png file object.

Author(s)

Jose Gama

Examples

## Not run: 
createPNGbuttons(data.frame(R=0,G=0,B=0))
data(FarnsworthD15)
createPNGbuttons(FarnsworthD15)

## End(Not run)

Decolorize algorithm from Mark Grundland and Neil A. Dodgson

Description

decolorize converts a color image to contrast enhanced greyscale algorithm from Mark Grundland and Neil A. Dodgson. The input is an array of RGB values and the output is an array with the greyscale values. decolorizeFile sends the output to a file instead of returning an array

Usage

decolorize(fileIN=NULL,effect=0.5,scale=NULL,noise=0.001,recolor=FALSE)

Arguments

Value

Author(s)

Jose Gama

References

Mark Grundland and Neil A. Dodgson, "Decolorize: Fast, Contrast Enhancing, Color to Grayscale Conversion", Pattern Recognition, vol. 40, no. 11, pp. 2891-2896, (2007). http://www.Eyemaginary.com/Portfolio/Publications.html

Examples

## Not run: 
samplePics <- c('fruits', 'pastel_color', 'sample1', 'TurnColorsGrayImage1', 'TurnColorsGrayImage2')
for (pics in samplePics)
{
fname<-paste(system.file(package='CVD'),'/extdata/fruits.png',sep='')
g1<-decolorize(fname)
png::writePNG(g1$tones, paste(pics, '.decolorize.png',sep=''))
}

## End(Not run)

Copunctal points derived by Smith and Pokorny (1975)

Description

dichromaticCopunctalPoint contains the copunctal points derived by Smith and Pokorny (1975)

Usage

dichromaticCopunctalPoint

Format

This data frame contains the following columns:

P

copunctal points - protanope

D

copunctal points - deuteranope

T

copunctal points - tritanope

Author(s)

Jose Gama

Source

Smith, V. C. & Pokorny, J. Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm. Vision Research, 15, 1975. 161-171.

References

Smith, V. C. & Pokorny, J. Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm. Vision Research, 15, 1975. 161-171.

Examples

data(dichromaticCopunctalPoint)
dichromaticCopunctalPoint

Effective Corneal Flux Density

Description

effectiveCornealFluxDensity computes the effective Corneal Flux Density = product of luminance, area, and the monocular effect, F = Lae, from Watson A. B., Yellott J. I. (2012).

Usage

effectiveCornealFluxDensity(L=NULL,a=NULL,e=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16.

Examples

# effective Corneal Flux Density, luminance in cd m^-2 = 1, field area in 
# deg^2 = 30, number of eyes = 2
## Not run: effectiveCornealFluxDensity(1,30^2,2)

Effective area of the illuminated pupil

Description

effectivePupilArea computes the effective area of the illuminated pupil from its diameter.

Usage

effectivePupilArea(d)

Arguments

Value

Author(s)

Jose Gama

References

#Smith, VC, Pokorny, J, and Yeh, T: The Farnsworth-Munsell 100-hue test in cone excitation space. Documenta Ophthalmologica Proceedings Series 56:281-291, 1993.

Examples

# Pupil area in mm^2 for diameter = 2 mm
## Not run: effectivePupilArea(2)

Example of cap arrangements for the D-15d test, Simple/Extreme Anomalous Trichromacy

Description

example1Lanthony1978 contains an example of cap arrangements for the D-15d test, Simple/Extreme Anomalous Trichromacy, from Lanthony (1978)

Usage

example1Lanthony1978

Format

This data frame contains the following columns:

SimpleAnomalousTrichromacyD15

example cap arrangements D15 - Simple Anomalous Trichromacy

SimpleAnomalousTrichromacyD15d

example cap arrangements D15d - Simple Anomalous Trichromacy

ExtremeAnomalousTrichromacyD15

example cap arrangements D15 - Extreme Anomalous Trichromacy

ExtremeAnomalousTrichromacyD15d

example cap arrangements D15d - Extreme Anomalous Trichromacy

Author(s)

Jose Gama

Source

The Desaturated Panel D-15 P. Lanthony Documenta Ophthalmologica 46,1: 185-189, 1978

References

The Desaturated Panel D-15 P. Lanthony Documenta Ophthalmologica 46,1: 185-189, 1978

Examples

data(example1Lanthony1978)
example1Lanthony1978

Example of cap arrangements for the D-15d test, Central Serous Choroidopathy/Optic Neuritis/Autosomal Dominant OpticAtrophy

Description

example2Lanthony1978 contains an example of cap arrangements for the D-15d test, Central Serous Choroidopathy/Optic Neuritis/Autosomal Dominant OpticAtrophy, from Lanthony (1978)

Usage

example2Lanthony1978

Format

This data frame contains the following columns:

CentralSerousChoroidopathyD15

example cap arrangements D15 - Central Serous Choroidopathy

CentralSerousChoroidopathyD15d

example cap arrangements D15d - Central Serous Choroidopathy

OpticNeuritisD15

example cap arrangements D15 - Optic Neuritis

OpticNeuritisD15d

example cap arrangements D15d - Optic Neuritis

AutosomalDominantOpticAtrophyD15

example cap arrangements D15 - Autosomal Dominant OpticAtrophy

AutosomalDominantOpticAtrophyD15d

example cap arrangements D15d - Autosomal Dominant OpticAtrophy

Author(s)

Jose Gama

Source

THE DESATURATED PANEL D-15 P. LANTHONY Documenta Ophthalmologica 46,1: 185-189, 1978

References

THE DESATURATED PANEL D-15 P. LANTHONY Documenta Ophthalmologica 46,1: 185-189, 1978

Examples

data(example2Lanthony1978)
example2Lanthony1978

Example of cap arrangements for the D-15d test

Description

exampleBowman1982 contains an example of cap arrangements for the D-15d test, from Bowman (1982)

Usage

exampleBowman1982

Format

This data frame contains the following columns:

A

example cap arrangements A

B

example cap arrangements B

C

example cap arrangements C

D

example cap arrangements D

E

example cap arrangements E

F

example cap arrangements F

Author(s)

Jose Gama

Source

A Method For Quantitative Scoring Of The Farnsworth Panel D-15 K.J. Bowman 1982

References

A Method For Quantitative Scoring Of The Farnsworth Panel D-15 K.J. Bowman 1982

Examples

data(exampleBowman1982)
exampleBowman1982

Example of cap arrangements for the FM-100 test

Description

exampleFM100 contains an example of cap arrangements for the FM-100, from Hidayat (2008)

Usage

exampleFM100

Format

This table contains one example of cap arrangements for the FM-100

Author(s)

Jose Gama

Source

proceedings of the New Zealand Generating fast automated reports for the Farnsworth-Munsell 100-hue colour vision test Ray Hidayat, Computer Science Research Student Conference 2008

References

proceedings of the New Zealand Generating fast automated reports for the Farnsworth-Munsell 100-hue colour vision test Ray Hidayat, Computer Science Research Student Conference 2008

Examples

data(exampleFM100)
exampleFM100

Example of cap arrangements for the D-15 test, deuteranope/protanope/tritanope

Description

exampleFarnsworth1974 contains an example of cap arrangements for the D-15 test, deuteranope/protanope/tritanope, from Farnsworth (1974)

Usage

exampleFarnsworth1974

Format

This data frame contains the following columns:

deuteranope

example cap arrangements D15 - deuteranope

protanope

example cap arrangements D15 - protanope

tritanope

example cap arrangements D15 - tritanope

Author(s)

Jose Gama

Source

Farnsworth D. The Farnsworth Dichotomous Test for Color Blindness. Panel D-15. New York, Psychological Testing, 1974

References

Farnsworth D. The Farnsworth Dichotomous Test for Color Blindness. Panel D-15. New York, Psychological Testing, 1974

Examples

data(exampleFarnsworth1974)
exampleFarnsworth1974

Example of cap arrangements for the D-15 test, protanope/deuteranope/monochromat

Description

exampleNRC1981 contains an example of cap arrangements for the D-15d test, protanope/deuteranope/monochromat, from National Research Council (1981)

Usage

exampleNRC1981

Format

This data frame contains the following columns:

protanope

example cap arrangements D15 - protanope

deuteranope

example cap arrangements D15 - deuteranope

monochromat

example cap arrangements D15 - monochromat

Author(s)

Jose Gama

Source

Procedures for Testing Color Vision: Report of Working Group 41, 1981, Committee on Vision, National Research Council, pp. 107

References

Procedures for Testing Color Vision: Report of Working Group 41, 1981, Committee on Vision, National Research Council, pp. 107

Examples

data(exampleNRC1981)
exampleNRC1981

Example of cap arrangements for the D-15 test, rodMonochromat/blueConeMonochromat

Description

exampleSimunovic2004 contains an example of cap arrangements for the D-15d test, rodMonochromat/blueConeMonochromat, from Lanthony (1978)

Usage

exampleSimunovic2004

Format

This data frame contains the following columns:

rodMonochromat

example cap arrangements D15 - rodMonochromat

blueConeMonochromat

example cap arrangements D15 - blueConeMonochromat

Author(s)

Jose Gama

Source

Cone dystrophies Part 2 Cone dysfunction syndromes, Matthew P Simunovic

References

Cone dystrophies Part 2 Cone dysfunction syndromes, Matthew P Simunovic

Examples

data(exampleSimunovic2004)
exampleSimunovic2004

Greyscale algorithms

Description

Common algorithms to convert color images to greyscale. The input is an array of RGB values and the output is an array with the greyscale values. greyscale.avg Greyscale algorithm, convert to average RGB values. greyscale.Y Greyscale algorithm YIQ/NTSC - RGB colors in a gamma 2.2 color space. greyscale.linear Greyscale algorithm linear RGB colors greyscale.RMY Greyscale algorithm RMY greyscale.BT709 Greyscale algorithm BT709 greyscale.luminosity Greyscale algorithm using luminosity

Usage

greyscale.avg(colorArray)

Arguments

Value

Author(s)

Jose Gama

Examples

## Not run: 
samplePics <- c('fruits', 'pastel_color', 'sample1', 'TurnColorsGrayImage1', 'TurnColorsGrayImage2')
for (pics in samplePics)
{
fname<-paste(system.file(package='CVD'),'/extdata/',pics,'.png',sep='')
imgTest<-loadPNG(fname)
g1<-greyscale.avg(imgTest)
png::writePNG(g1, paste(pics, '.greyscale.avg.png',sep=''))
}

imgTest<-loadPNG(fname)
g1<-greyscale.avg(imgTest)
png::writePNG(g1, paste(pics, '.greyscale.avg.png',sep=''))
g1<-greyscale.BT709(imgTest)
png::writePNG(g1, paste(pics, '.BT709.png',sep=''))
g1<-greyscale.Linear(imgTest)
png::writePNG(g1, paste(pics, '.Linear.png',sep=''))
g1<-greyscale.Luminosity(imgTest)
png::writePNG(g1, paste(pics, '.Luminosity.png',sep=''))
g1<-greyscale.RMY(imgTest)
png::writePNG(g1, paste(pics, '.RMY.png',sep=''))
g1<-greyscale.Y(imgTest)
png::writePNG(g1, paste(pics, '.Y.png',sep=''))


## End(Not run)

Convert from luminance to troland and effective troland

Description

illuminance2troland convert from illuminance (lux) to conventional retinal illuminance (troland) and effective troland (trolands per effective area). luminance2troland convert from luminance (cd/m^2) to troland and effective troland.

Usage

luminance2troland(Lv, d=NA)
illuminance2troland(Ev, lumFactor, d=NA)

Arguments

Value

Author(s)

Jose Gama

References

#Smith, VC, Pokorny, J, and Yeh, T: The Farnsworth-Munsell 100-hue test in cone excitation space. Documenta Ophthalmologica Proceedings Series 56:281-291, 1993.

Examples

# Pupil area in mm^2 for diameter = 2 mm
## Not run: illuminance2troland(2)

Automatic interpretation of test scores

Description

interpretation.VingrysAndKingSmith and interpretation.Foutch perform an interpretation of the test results based on the classification ranges from the authors of the tests.

Usage

interpretation.VingrysAndKingSmith(VKS,optMethod=88)

Arguments

Value

Author(s)

Jose Gama

References

Vingrys, A.J. and King-Smith, P.E. (1988). A quantitative scoring technique for panel tests of color vision. Investigative Ophthalmology and Visual Science, 29, 50-63.

A new quantitative technique for grading Farnsworth D-15 color panel tests Foutch, Brian K.; Stringham, James M.; Lakshminarayanan, Vasuvedan Journal of Modern Optics, vol. 58, issue 19-20, pp. 1755-1763

Evaluation of the new web-based" Colour Assessment and Diagnosis" test J Seshadri, J Christensen, V Lakshminarayanan, CJ BASSI Optometry & Vision Science 82 (10), 882-885

Examples

# a "perfect" score
## Not run: 
interpretation.VingrysAndKingSmith(D15Foutch(1:15))
## End(Not run)

pupil diameter ranges from Barten, L. (1999)

Description

lightAdaptedPupilSize.Barten computes the pupil diameter ranges from Barten, L. (1999).

Usage

lightAdaptedPupilSize.Barten(L=NULL, a=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. Barten, P. G. J. (1999). Contrast sensitivity of the human eye and its effects on image quality. Bellingham, WA: SPIE Optical Engineering Press.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2, field diameter = 30 degrees
## Not run: lightAdaptedPupilSize.Barten(1,30^2)

pupil diameter ranges from Blackie, C. A., & Howland, H. C. (1999)

Description

lightAdaptedPupilSize.BlackieAndHowland computes the pupil diameter ranges from Blackie, C. A., & Howland, H. C., (1999).

Usage

lightAdaptedPupilSize.BlackieAndHowland(L=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. Blackie, C. A., & Howland, H. C. (1999). An extension of an accommodation and convergence model of emmetropization to include the effects of illumination intensity. Ophthalmic and Physiological Optics, 19(2), 112–125.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2
## Not run: lightAdaptedPupilSize.BlackieAndHowland(1)

pupil diameter ranges from Crawford, L. (1936)

Description

lightAdaptedPupilSize.Crawford computes the pupil diameter ranges from Crawford, L. (1936).

Usage

lightAdaptedPupilSize.Crawford(L=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. Crawford, B. H. (1936). The dependence of pupil size upon external light stimulus under static and variable conditions. Proceedings of the Royal Society of London, Series B, Biological Sciences, 121(823), 376–395.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2
## Not run: lightAdaptedPupilSize.Crawford(1)

pupil diameter ranges from DeGrootAndGebhard, L. (1952)

Description

lightAdaptedPupilSize.DeGrootAndGebhard computes the pupil diameter ranges from DeGrootAndGebhard, L. (1952).

Usage

lightAdaptedPupilSize.DeGrootAndGebhard(L=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. De Groot, S. G., & Gebhard, J. W. (1952). Pupil size as determined by adapting luminance. Journal of the Optical Society of America A, 42(7), 492–495.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2
## Not run: lightAdaptedPupilSize.DeGrootAndGebhard(1)

pupil diameter ranges from Holladay, L. (1926)

Description

lightAdaptedPupilSize.Holladay computes the pupil diameter ranges from Holladay, L. (1926).

Usage

lightAdaptedPupilSize.Holladay(L=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. Holladay, L. (1926). The fundamentals of glare and visibility. Journal of the Optical Society of America, 12(4), 271–319.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2
## Not run: lightAdaptedPupilSize.Holladay(1)

pupil diameter ranges from Le Grand (1992)

Description

lightAdaptedPupilSize.LeGrand computes the pupil diameter ranges from Le Grand (1992).

Usage

lightAdaptedPupilSize.LeGrand(L=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Vision, Pierre A. Buser, Michel Imbert, MIT Press, 1992

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2
## Not run: lightAdaptedPupilSize.LeGrand(1)

pupil diameter ranges from MoonAndSpencer, L. (1944)

Description

lightAdaptedPupilSize.MoonAndSpencer computes the pupil diameter ranges from MoonAndSpencer, L. (1944).

Usage

lightAdaptedPupilSize.MoonAndSpencer(L=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. Moon, P., & Spencer, D. E. (1944). On the Stiles-Crawford effect. Journal of the Optical Society of America, 34(6), 319–329, http://www.opticsinfobase. org/abstract.cfm?URI1⁄4josa-34-6-319.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2
## Not run: lightAdaptedPupilSize.MoonAndSpencer(1)

pupil diameter ranges from StanleyAndDavies, L. (1995)

Description

lightAdaptedPupilSize.StanleyAndDavies computes the pupil diameter ranges from StanleyAndDavies, L. (1995).

Usage

lightAdaptedPupilSize.StanleyAndDavies(L=NULL, a=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. Stanley, P. A., & Davies, A. K. (1995). The effect of field of view size on steady-state pupil diameter. Ophthalmic & Physiological Optics, 15(6), 601–603.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2, field diameter = 30 degrees
## Not run: lightAdaptedPupilSize.StanleyAndDavies(1,30^2)

pupil diameter ranges from Watson A. B., Yellott J. I. (2012)

Description

lightAdaptedPupilSize.WatsonAndYellott computes the pupil diameter ranges from Watson A. B., Yellott J. I. (2012).

Usage

lightAdaptedPupilSize.WatsonAndYellott(L=NULL, a=NULL, y=NULL, y0=NULL, e=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://www.ncbi.nlm.nih.gov/pubmed/23012448

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2, field diameter = 30 degrees,
# age=45, estimated reference age = 28.58, eyes = 2
## Not run: lightAdaptedPupilSize.WatsonAndYellott(1,30^2,45,28.58,2)

pupil diameter ranges from Winn et al (1995)

Description

lightAdaptedPupilSize.WinnEtAl computes the pupil diameter ranges from Winn et al (1995).

Usage

lightAdaptedPupilSize.WinnEtAl(L=NULL, y=NULL)

Arguments

Value

Author(s)

Jose Gama

References

Watson A. B., Yellott J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12, 1–16. http://journalofvision.org/12/10/12/, doi:10.1167/5.9.6. Winn, B., Whitaker, D., Elliott, D. B., & Phillips, N. J. (1994). Factors affecting light-adapted pupil size in normal human subjects. Investigative Ophthalmology & Visual Science, 35(3):1132–1137, http://www.iovs.org/content/35/3/1132.

Examples

# Pupil diameter in mm for luminance = 1 cd m^-2, age = 45 years
## Not run: lightAdaptedPupilSize.WinnEtAl(1,45)

Internal CVD functions

Description

Ignore these.

Load a PNG file

Description

loadPNG loads a PNG file and displays the image dimensions.

Usage

loadPNG(fileIN=NULL, silent=FALSE)

Arguments

Value

png file object.

Author(s)

Jose Gama

Examples

## Not run: 
loadPNG(paste(system.file(package='CVD'),'/inst/extdata/fruits.png',sep=''))

## End(Not run)

Neutral points for CIE 1976 uv, CIE 1931 xy and CIE 1960 uv

Description

neutralPoint contains the neutral points for CIE 1976 uv, CIE 1931 xy and CIE 1960 uv

Usage

neutralPoint

Format

This data frame contains the following columns:

CIE1931xy

neutral point CIE 1931 xy

CIE1960uv

neutral point CIE 1976 uv

CIE1960uv

neutral point CIE 1960 uv

Author(s)

Jose Gama

Examples

data(neutralPoint)
neutralPoint

Plot confusion vectors for CIE 1976 uv, CIE 1931 xy and CIE 1960 uv

Description

plotConfusionVectors Plots the confusion vectors for CIE 1976 uv, CIE 1931 xy and CIE 1960 uv.

Usage

plotConfusionVectors(colorSpace='CIE1931xy')

Arguments

Value

none

Author(s)

Jose Gama

Examples

# find duplicate values
## Not run: plotConfusionVectors()

Graphical score for the D-15 tests

Description

scoreD15Graphic computes the graphical score for the D-15 test or similar. The input is either a vector of RGB colors or cap positions.

Usage

scoreD15Graphic(userD15colors=NULL,userD15values=NULL, titleGraphic=
"Farnsworth dichotomous test (D-15) results", okD15colors=NULL)

Arguments

Value

none

Author(s)

Jose Gama

References

Farnsworth D. The Farnsworth Dichotomous Test for Color Blindness Panel D-15 Manual. New York, The Psychological Corp., 1947, pp. 1-8.

Examples

# a "perfect" score
## Not run: scoreD15Graphic(userD15values=1:15)

Total Color Difference Score (TCDS) for the D-15 tests

Description

scoreD15TCDS computes the Total Color Difference Score (TCDS) for the D-15 test, from Bowman's (1982). The input is either a vector of RGB colors or cap positions.

Usage

scoreD15TCDS(userD15colors=NULL,userD15values=NULL,
 distTable = get("BowmanTCDS", envir = environment()), 
D15colors = get("FarnsworthD15", envir = environment()))

Arguments

Value

Author(s)

Jose Gama

References

Bowman's (1982) Total Color Difference Score (TCDS) for congenitally defective observers on the D-15 with enlarged tests. K.J. Bowman, A method for quantitative scoring of the Farnsworth Panel D-15, Acta Ophthalmologica, 60 (1982), pp. 907–916

Examples

# a "perfect" score
## Not run: 
scoreD15TCDS(userD15values=1:15)
## End(Not run)

Graphical score for the D-15 tests

Description

scoreFM100Graphic computes the graphical score for the FM-100 test or similar. The input is either a vector of RGB colors or cap positions.

Usage

scoreFM100Graphic(userFM100colors=NULL,userFM100values=NULL, titleGraphic=
"Farnsworth Munsell 100-Hue test results", okFM100colors=NULL, Kinnear=FALSE)

Arguments

Value

none

Author(s)

Jose Gama

References

Dean Farnsworth, 1943 The Farnsworth Munsell 100-hue dichotomous tests for colour vision Journal of the Optical Society of America, 33 (1943), pp. 568–576

Examples

# an example score
## Not run: 
FM100example<-exampleFM100
userFM100values=cbind(FM100example[1,], FM100example[4,-22],
 FM100example[7,-22], FM100example[10,-22])
userFM100values=as.vector(unlist(userFM100values))
scoreFM100Graphic(userFM100values)

## End(Not run)

Graphical score for the D-15 tests

Description

scoreRoth28Graphic computes the graphical score for the Roth-28 test or similar. The input is either a vector of RGB colors or cap positions.

Usage

scoreRoth28Graphic(userR28colors=NULL,userR28values=NULL, titleGraphic=
"Roth-28 test results", okR28colors=NULL)

Arguments

Value

none

Author(s)

Jose Gama

References

Carl Erb, Martin Adler, Nicole Stübiger, Michael Wohlrab, Eberhart Zrenner, Hans-Jürgen Thiel, Colour vision in normal subjects tested by the colour arrangement test ‘Roth 28-hue desaturated’, Vision Research, Volume 38, Issue 21, November 1998, Pages 3467-3471, ISSN 0042-6989, http://dx.doi.org/10.1016/S0042-6989(97)00433-1.

Examples

# a "perfect" score
## Not run: scoreRoth28Graphic(userD15values=1:28)

Show missing and duplicated cap numbers

Description

showDuplicated shows missing and duplicated cap numbers from D-15, D15d, FM-100 and similar tests.

Usage

showDuplicated(cnum)

Arguments

Value

none

Author(s)

Jose Gama

Examples

# find duplicate values
## Not run: showDuplicated(1:15)
showDuplicated(c(1:4,8,5:14))
# this is an example of a typo in data from a publication
#Procedures for Testing Color Vision: Report of Working Group 41, 1981, 
Committee on Vision, National Research Council, pp. 107
#the "monochromat" data has "16" instead of "6"
data(exampleNRC1981)
showDuplicated(exampleNRC1981[,3])

## End(Not run)

Typical cap arrangements for the D-15 tests

Description

typicalD15 contains typical cap arrangements for the D-15 tests, from Farnsworth D (1947), Simunovic (1998) and NRC (1981)

Usage

typicalD15

Format

This data frame contains the following columns:

protanope

typical cap arrangements - protanope

deuteranope

typical cap arrangements - deuteranope

tritanope

typical cap arrangements - tritanope

monochromat

typical cap arrangements - monochromat

rodMonochromat

typical cap arrangements - rodMonochromat

blueConeMonochromat

typical cap arrangements - blueConeMonochromat

Author(s)

Jose Gama

Source

Farnsworth D. The Farnsworth Dichotomous Test for Color Blindness Panel D-15 Manual. New York, The Psychological Corp., 1947, pp. 1-8. Simunovic MP, Moore AT. The cone dystrophies. Eye 1998;12:553–65. National Research Council (US). Committee on Vision. Procedures for testing color vision: report of Working Group 41. National Academies Press, 1981.

References

Farnsworth D. The Farnsworth Dichotomous Test for Color Blindness Panel D-15 Manual. New York, The Psychological Corp., 1947, pp. 1-8. Simunovic MP, Moore AT. The cone dystrophies. Eye 1998;12:553–65. National Research Council (US). Committee on Vision. Procedures for testing color vision: report of Working Group 41. National Academies Press, 1981.

Examples

data(typicalD15)
typicalD15

Vector of PNG files representing colored caps (buttons)

Description

vectorPNGbuttons returns a vector with the filenames of the PNG files representing colored caps (buttons) from a data.frame.

Usage

vectorPNGbuttons(capsData=get("FarnsworthD15", envir = environment()))

Arguments

Value

vector with path+filenames of PNG files.

Author(s)

Jose Gama

Examples

## Not run: 
vectorPNGbuttons(FarnsworthD15)

## End(Not run)