df_rate_flat <- structure(list(pair = c("0841_0851_Mandaic", "0843_0850_Mandaic", "0846_0855_Mandaic", "0849_0856_Mandaic", "084A_084D_Mandaic", "0853_0857_Mandaic", "10332_10338_Gothic", "10334_10340_Gothic", "10336_10348_Gothic", "1033A_10342_Gothic", "1033B_1034A_Gothic", "10345_10347_Gothic", "10380_10397_Ugaritic", "10381_1038B_Ugaritic", "10382_1039C_Ugaritic", "10386_10398_Ugaritic", "10388_1039D_Ugaritic", "10389_1038C_Ugaritic", "109A5_109AA_MeroiticCursive", "109A9_109B2_MeroiticCursive", "109AC_109B3_MeroiticCursive", "109AD_109AE_MeroiticCursive", "109AF_109B5_MeroiticCursive", "109B0_109B4_MeroiticCursive", "110A_1164_Hangul", "110B_116B_Hangul", "1112_1175_Hangul", "1169_116E_Hangul", "116A_116F_Hangul", "116D_1172_Hangul", "1683_168B_Ogham", "1685_168C_Ogham", "1687_168D_Ogham", "1689_168A_Ogham", "168E_168F_Ogham", "1695_1696_Ogham", "16AD1_16AE7_BassaVah", "16ADA_16AE4_BassaVah", "16ADC_16AE9_BassaVah", "16ADD_16ADE_BassaVah", "16ADF_16AE8_BassaVah", "16AE1_16AE2_BassaVah", "1761_1762_Tagbanwa", "1763_176C_Tagbanwa", "1764_1768_Tagbanwa", "1765_1770_Tagbanwa", "1769_176E_Tagbanwa", "176A_176F_Tagbanwa", "1A05_1A0A_Buginese", "1A07_1A12_Buginese", "1A08_1A13_Buginese", "1A0C_1A0F_Buginese", "1A10_1A15_Buginese", "1A14_1A16_Buginese", "A805_A807_SylotiNagri", "A810_A812_SylotiNagri", "A811_A813_SylotiNagri", "A814_A822_SylotiNagri", "A818_A81C_SylotiNagri", "A819_A81B_SylotiNagri"), Script = c("Mandaic", "Mandaic", "Mandaic", "Mandaic", "Mandaic", "Mandaic", "Gothic", "Gothic", "Gothic", "Gothic", "Gothic", "Gothic", "Ugaritic", "Ugaritic", "Ugaritic", "Ugaritic", "Ugaritic", "Ugaritic", "MeroiticCursive", "MeroiticCursive", "MeroiticCursive", "MeroiticCursive", "MeroiticCursive", "MeroiticCursive", "Hangul", "Hangul", "Hangul", "Hangul", "Hangul", "Hangul", "Ogham", "Ogham", "Ogham", "Ogham", "Ogham", "Ogham", "BassaVah", "BassaVah", "BassaVah", "BassaVah", "BassaVah", "BassaVah", "Tagbanwa", "Tagbanwa", "Tagbanwa", "Tagbanwa", "Tagbanwa", "Tagbanwa", "Buginese", "Buginese", "Buginese", "Buginese", "Buginese", "Buginese", "SylotiNagri", "SylotiNagri", "SylotiNagri", "SylotiNagri", "SylotiNagri", "SylotiNagri"), average.rate = c(6.54444444444444, 6.5, 5.80555555555556, 3.44444444444444, 3.49444444444444, 5.78888888888889, 6.75, 6.65555555555556, 6.93333333333333, 3.53888888888889, 6.32777777777778, 5.58333333333333, 4.08888888888889, 4.77222222222222, 5.24444444444444, 6.37777777777778, 5.83888888888889, 5.03333333333333, 6.36666666666667, 3.52777777777778, 6.36666666666667, 6.37222222222222, 6.81111111111111, 6.44444444444444, 6.72222222222222, 6.92222222222222, 6.76111111111111, 2.35555555555556, 2.99444444444444, 2.4, 6.38333333333333, 5.97777777777778, 5.71111111111111, 2.14444444444444, 2.05, 6.1, 2.97777777777778, 6.43888888888889, 3.71111111111111, 6.22222222222222, 6.73333333333333, 6.78333333333333, 6.51666666666667, 6.71111111111111, 3.03888888888889, 6.31666666666667, 2.71111111111111, 5.6, 6.31666666666667, 5.91111111111111, 3.66666666666667, 5.68333333333333, 2.33888888888889, 3.16666666666667, 6.11111111111111, 5.41111111111111, 2.11666666666667, 4.91111111111111, 2.00555555555556, 5.50555555555556), average.hamming = c(0.73, 0.87, 0.13, 0.13, 0.13, 0.73, 0.77, 0.69, 0.69, 0.15, 0.15, 0.15, 0.17, 0.56, 0.56, 0.61, 0.17, 0.11, 0.13, 0.13, 0.63, 0.13, 0.75, 0.63, 0.76, 0.76, 0.71, 0.1, 0.1, 0.1, 0.69, 0.69, 0.77, 0.15, 0.15, 0.15, 0.14, 0.76, 0.14, 0.14, 0.81, 0.81, 0.78, 0.78, 0.22, 0.89, 0.22, 0.22, 0.75, 0.83, 0.17, 0.75, 0.25, 0.25, 0.7, 0.09, 0.04, 0.65, 0.09, 0.7)), class = c("grouped_df", "tbl_df", "tbl", "data.frame"), row.names = c(NA, -60L), groups = structure(list( pair = c("0841_0851_Mandaic", "0843_0850_Mandaic", "0846_0855_Mandaic", "0849_0856_Mandaic", "084A_084D_Mandaic", "0853_0857_Mandaic", "10332_10338_Gothic", "10334_10340_Gothic", "10336_10348_Gothic", "1033A_10342_Gothic", "1033B_1034A_Gothic", "10345_10347_Gothic", "10380_10397_Ugaritic", "10381_1038B_Ugaritic", "10382_1039C_Ugaritic", "10386_10398_Ugaritic", "10388_1039D_Ugaritic", "10389_1038C_Ugaritic", "109A5_109AA_MeroiticCursive", "109A9_109B2_MeroiticCursive", "109AC_109B3_MeroiticCursive", "109AD_109AE_MeroiticCursive", "109AF_109B5_MeroiticCursive", "109B0_109B4_MeroiticCursive", "110A_1164_Hangul", "110B_116B_Hangul", "1112_1175_Hangul", "1169_116E_Hangul", "116A_116F_Hangul", "116D_1172_Hangul", "1683_168B_Ogham", "1685_168C_Ogham", "1687_168D_Ogham", "1689_168A_Ogham", "168E_168F_Ogham", "1695_1696_Ogham", "16AD1_16AE7_BassaVah", "16ADA_16AE4_BassaVah", "16ADC_16AE9_BassaVah", "16ADD_16ADE_BassaVah", "16ADF_16AE8_BassaVah", "16AE1_16AE2_BassaVah", "1761_1762_Tagbanwa", "1763_176C_Tagbanwa", "1764_1768_Tagbanwa", "1765_1770_Tagbanwa", "1769_176E_Tagbanwa", "176A_176F_Tagbanwa", "1A05_1A0A_Buginese", "1A07_1A12_Buginese", "1A08_1A13_Buginese", "1A0C_1A0F_Buginese", "1A10_1A15_Buginese", "1A14_1A16_Buginese", "A805_A807_SylotiNagri", "A810_A812_SylotiNagri", "A811_A813_SylotiNagri", "A814_A822_SylotiNagri", "A818_A81C_SylotiNagri", "A819_A81B_SylotiNagri" ), .rows = structure(list(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -60L), .drop = TRUE))
library(tidyverse)
library(ggrepel)
for (s in script <- unique(df_rate_flat$Script)) {
p <- df_rate_flat %>% filter(Script == s) %>%
ggplot(aes(x = average.rate, y = average.hamming, color = Script)) +
geom_point(size = 3) +
geom_text_repel(aes(label = pair), nudge_x = 0.2, nudge_y = 0.2, size = 6) +
theme_bw() +
theme(legend.position = "none",
plot.background = element_blank(),
plot.title = element_text(hjust = 0.5),
axis.text = element_text(color = "black", size = 14),
axis.line = element_line(color = "black")
) +
ggtitle(s)
print(p)
ggsave(paste0("Graphiques/plot_point_", s, ".png"),
plot = p,
width = 4.385417, height = 6.083333,
device = "png")
}
- 我得到的**
我想要的
1条答案
按热度按时间dbf7pr2w1#
只需先调用
x11()
来创建一个绘图窗口,将其缩放到正确的大小,例如全屏&然后使用dev.size()
来获得width
和height
的大小,或者在导出时使用width
和height
的好值来使其看起来不错(全屏可能不是一个好主意,因为全屏取决于人们的系统)。就像我对你的问题的其他回答一样,我使用了我的导出包,因为这样你也可以轻松地导出到其他格式(例如:Powerpoint或pdf
或svg
,所以矢量格式,比位图png
质量更好),它也适用于基本R或点阵图。负载数据:
生成绘图并导出: