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# Mapping Color to Meaning in Colormap Data Visualizations

• Karen B. Schloss, Department of Psychology and Wisconsin Institute for
Discovery, University of Wisconsin–Madison. Email: kschloss@wisc.edu.
• Connor C. Gramazio, Department of Computer Science, Brown University,
Email: connor@cs.brown.edu.
• A Taylor Silverman, School of Public Health, Brown University. Email:
taylor silverman@alumni.brown.edu.
• Madeline L. Parker, Department of Psychology and Wisconsin Institute for
Discovery, University of Wisconsin–Madison. Email: parker
• Audrey S. Wang, Department of Applied and Computational Mathematics,
California Institute of Technology. Email: aswang@alumni.caltech.edu.

==>是哪些因素会造成人们不同的推断映射。

==>过去的文献在这方面是相互矛盾的（背景颜色影响人们先验推断上面),对其进行了解释说明

### 结论

==>在不同的背景下(浅色、深色)，会造成冲突.

(opaque-is-more bias)有时候没啥用，有时候要超过(dark-is-more bias)

### Introduction

==>研究背景颜色和colormap颜色不同造成的影响

1.背景颜色只有在colormap在透明度上有变化时才有作用.

2.当透明度不变化时，dark-is-more bias更有明显的作用。这和contrast-is-more bias相左.

3.透明度变化时，其影响作用随着透明度的变化幅度增大而增大.opaque-is-more bias和contrast-is-more bias只有细微的差别.因为当透明度变化时，对比度才有意义.

### 相关工作

#### designing color scales for colormaps

Discriminative power

Uniformity

Order

#### selecting color scales according to data and task

Different color scales are more or less effective, depending on the properties of data they represent and the tasks needed to interpret the data.

### 实验一

#### Aim at

how the background color influenced inferred mappings when colormaps were constructed using various standard color scales for visualization

#### Design

20 colormap conditions(5 color scales * 2 background color * 2(left/right balance))

20 diffierent colormaps per conditon

20 * 20 = 400 unique colormap imgs

repeat 4 times for four different legend conditions(light/dark-more, greater/fewer-high)

different legend只是为了保证他们看了图例

#### Conclusion

==>所以还要看每个colormap的透明度变化.

Figure 6.如果只有dark-is-more bias,那么每条线的斜率应该是0，即不受透明度影响,该快多少块多少。但显然，Opacity Variation Index的变化，Faster RTs有变化，说明了这是dark-is-more 和opaque-is-more共同作用的记过

#### Summary

1.when color scales did not appear to vary in opacity, inferred mappings were dominated by a dark-is-more bias, regardless of the background.

2.However, as evidence for opacity variation increased, inferred mappings became increasingly more influenced by an opaque-is-more bias.

## 实验二

#### Aim at

tested our hypothesis that there is an opaque-ismore bias.

#### Method

participants: 36 – 6(为了让实验人数和实验一相同，并且准确率要>90%)

conditions: 3 color scales * 3 backgroud colors * 2 encoded lightness mappings * 2 lengend text positions * 2 (left/right balance) = 72

all: 72 *20 = 1440 trails

pre-trails: 20

#### Results

RTs:(mean accuracy:97% range: 92%-99%, -6之后 < 90%)

## General Discussion

Cuff：表明有dark-is-more bias的存在，但是没有考虑背景颜色

McGranaghan:表明有contrast-is-more bias，但是切换不同的背景颜色时,dark-is-more bias总是存在，只是在black background上减少了.

Roth et al.提出dark background上用lighter colors来编码大数据(没有实验测试).这和McGranaghan冲突了.

### LAB颜色空间

1. Q 回复
2019 年 5 月 16 日 at 下午 3:01

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