Requires a data.frame as produced by [datsteps()] or a number as DAT_df_steps. Calculates the value with which the y-axis of a density graph should be multiplied by in order to be visible in the corresponding histogram.
Arguments
- DAT_df_steps
a data.frame as returned by [datsteps()]. (Will also work with a single number and a vector.)
- binwidth
the bandwidth to use for the density function and histogram. Should equal the stepsize used to create the data.frame. If a data.frame as returned by [datsteps()] is given, stepsize can be automatically assigned using the corresponding attribute (`binwidth = "stepsize"`)
Value
the value with which to scale the density curve to a histogram plot so that both will be visible
Examples
data("Inscr_Bithynia")
DAT_df <- Inscr_Bithynia[, c("ID", "Location", "DAT_min", "DAT_max")]
DAT_df_steps <- datsteps(DAT_df, stepsize = 25)
#> Using 'weight'-calculation (see https://doi.org/10.1017/aap.2021.8).
#> Warning: 1554 rows with NA-values in the dating columns will be omitted.
#> DAT_min and DAT_max at Index: 57, 68, 120, 173, 187, 238, 299, 300, 311, 312, 588, 590, 599, 679, 794, 798, 799, 828, 831, 833, 834, 837, 841, 878, 879, 908, 909, 914, 915, 931, 932, 933, 937, 938, 941, 942, 997, 1051, 1064, 1067, 1130, 1307, 1308, 1310, 1322, 1323, 1324 have the same value! Is this correct? If unsure, check your data for possible errors.
#> Warning: stepsize is larger than the range of the closest dated object at Index = 6, 12, 13, 17, 18, 19, 20, 21, 38, 39, 40, 43, 44, 57, 67, 68, 69, 70, 72, 75, 98, 101, 102, 106, 107, 112, 113, 114, 120, 122, 123, 129, 136, 137, 138, 142, 143, 146, 148, 149, 150, 168, 170, 172, 173, 175, 177, 178, 179, 180, 181, 182, 186, 187, 189, 190, 195, 203, 204, 205, 206, 207, 208, 209, 210, 212, 214, 215, 216, 217, 218, 234, 238, 240, 241, 242, 245, 261, 262, 292, 293, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 543, 546, 547, 548, 549, 581, 582, 583, 584, 585, 586, 588, 590, 591, 592, 593, 594, 595, 596, 597, 599, 602, 606, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 827, 828, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 866, 867, 870, 871, 872, 873, 874, 875, 878, 879, 880, 890, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 957, 958, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 989, 990, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1029, 1030, 1031, 1035, 1036, 1051, 1053, 1054, 1055, 1062, 1064, 1065, 1066, 1067, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1122, 1124, 1125, 1126, 1127, 1129, 1130, 1133, 1225, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1290, 1297, 1302, 1306, 1307, 1308, 1310, 1311, 1315, 1322, 1323, 1324). This is not recommended. For information see documentation of get.step.sequence().
get.histogramscale(DAT_df_steps)
#> [1] 298000
get.histogramscale(DAT_df_steps$DAT_step, binwidth = 20)
#> [1] 238400
get.histogramscale(500, binwidth = 20)
#> [1] 10000