rm(list=ls())
library(ggplot2)
counts <- read.csv("../instance_1-30year/output/counts.csv")
dim(counts)
## [1] 10951 317
nrow(counts)/365
## [1] 30.00274
sort(colnames(counts))
## [1] "asm_deaths"
## [2] "casual_edge_count"
## [3] "casual_sex_acts"
## [4] "casual_sex_with_condom_oral"
## [5] "casual_sex_without_condom_oral"
## [6] "cd4m_deaths"
## [7] "entries"
## [8] "hiv_positives_infected_with_syphilis"
## [9] "incarcerated"
## [10] "incarcerated_recidivist"
## [11] "infected_at_entry"
## [12] "infected_at_entry_18"
## [13] "infected_at_entry_19"
## [14] "infected_at_entry_20"
## [15] "infected_at_entry_21"
## [16] "infected_at_entry_22"
## [17] "infected_at_entry_23"
## [18] "infected_at_entry_24"
## [19] "infected_at_entry_25"
## [20] "infected_at_entry_26"
## [21] "infected_at_entry_27"
## [22] "infected_at_entry_28"
## [23] "infected_at_entry_29"
## [24] "infected_at_entry_30"
## [25] "infected_at_entry_31"
## [26] "infected_at_entry_32"
## [27] "infected_at_entry_33"
## [28] "infected_at_entry_34"
## [29] "infected_at_entry_35"
## [30] "infected_at_entry_36"
## [31] "infected_at_entry_37"
## [32] "infected_at_entry_38"
## [33] "infected_at_entry_39"
## [34] "infected_at_entry_40"
## [35] "infected_at_entry_41"
## [36] "infected_at_entry_42"
## [37] "infected_at_entry_43"
## [38] "infected_at_entry_44"
## [39] "infected_at_entry_45"
## [40] "infected_at_entry_46"
## [41] "infected_at_entry_47"
## [42] "infected_at_entry_48"
## [43] "infected_at_entry_49"
## [44] "infected_at_entry_50"
## [45] "infected_at_entry_51"
## [46] "infected_at_entry_52"
## [47] "infected_at_entry_53"
## [48] "infected_at_entry_54"
## [49] "infected_at_entry_55"
## [50] "infected_at_entry_56"
## [51] "infected_at_entry_57"
## [52] "infected_at_entry_58"
## [53] "infected_at_entry_59"
## [54] "infected_at_entry_60"
## [55] "infected_at_entry_61"
## [56] "infected_at_entry_62"
## [57] "infected_at_entry_63"
## [58] "infected_at_entry_64"
## [59] "infected_at_entry_65"
## [60] "infected_at_incarceration"
## [61] "infected_at_release"
## [62] "infected_ever_jailed"
## [63] "infected_external_18"
## [64] "infected_external_19"
## [65] "infected_external_20"
## [66] "infected_external_21"
## [67] "infected_external_22"
## [68] "infected_external_23"
## [69] "infected_external_24"
## [70] "infected_external_25"
## [71] "infected_external_26"
## [72] "infected_external_27"
## [73] "infected_external_28"
## [74] "infected_external_29"
## [75] "infected_external_30"
## [76] "infected_external_31"
## [77] "infected_external_32"
## [78] "infected_external_33"
## [79] "infected_external_34"
## [80] "infected_external_35"
## [81] "infected_external_36"
## [82] "infected_external_37"
## [83] "infected_external_38"
## [84] "infected_external_39"
## [85] "infected_external_40"
## [86] "infected_external_41"
## [87] "infected_external_42"
## [88] "infected_external_43"
## [89] "infected_external_44"
## [90] "infected_external_45"
## [91] "infected_external_46"
## [92] "infected_external_47"
## [93] "infected_external_48"
## [94] "infected_external_49"
## [95] "infected_external_50"
## [96] "infected_external_51"
## [97] "infected_external_52"
## [98] "infected_external_53"
## [99] "infected_external_54"
## [100] "infected_external_55"
## [101] "infected_external_56"
## [102] "infected_external_57"
## [103] "infected_external_58"
## [104] "infected_external_59"
## [105] "infected_external_60"
## [106] "infected_external_61"
## [107] "infected_external_62"
## [108] "infected_external_63"
## [109] "infected_external_64"
## [110] "infected_external_65"
## [111] "infected_externally"
## [112] "infected_inside_jail"
## [113] "infected_jail_pop"
## [114] "infected_never_jailed"
## [115] "infected_partners_at_incarceration"
## [116] "infected_via_transmission"
## [117] "infected_via_transmission_18"
## [118] "infected_via_transmission_19"
## [119] "infected_via_transmission_20"
## [120] "infected_via_transmission_21"
## [121] "infected_via_transmission_22"
## [122] "infected_via_transmission_23"
## [123] "infected_via_transmission_24"
## [124] "infected_via_transmission_25"
## [125] "infected_via_transmission_26"
## [126] "infected_via_transmission_27"
## [127] "infected_via_transmission_28"
## [128] "infected_via_transmission_29"
## [129] "infected_via_transmission_30"
## [130] "infected_via_transmission_31"
## [131] "infected_via_transmission_32"
## [132] "infected_via_transmission_33"
## [133] "infected_via_transmission_34"
## [134] "infected_via_transmission_35"
## [135] "infected_via_transmission_36"
## [136] "infected_via_transmission_37"
## [137] "infected_via_transmission_38"
## [138] "infected_via_transmission_39"
## [139] "infected_via_transmission_40"
## [140] "infected_via_transmission_41"
## [141] "infected_via_transmission_42"
## [142] "infected_via_transmission_43"
## [143] "infected_via_transmission_44"
## [144] "infected_via_transmission_45"
## [145] "infected_via_transmission_46"
## [146] "infected_via_transmission_47"
## [147] "infected_via_transmission_48"
## [148] "infected_via_transmission_49"
## [149] "infected_via_transmission_50"
## [150] "infected_via_transmission_51"
## [151] "infected_via_transmission_52"
## [152] "infected_via_transmission_53"
## [153] "infected_via_transmission_54"
## [154] "infected_via_transmission_55"
## [155] "infected_via_transmission_56"
## [156] "infected_via_transmission_57"
## [157] "infected_via_transmission_58"
## [158] "infected_via_transmission_59"
## [159] "infected_via_transmission_60"
## [160] "infected_via_transmission_61"
## [161] "infected_via_transmission_62"
## [162] "infected_via_transmission_63"
## [163] "infected_via_transmission_64"
## [164] "infected_via_transmission_65"
## [165] "infection_deaths"
## [166] "jail_pop"
## [167] "max_age_exits"
## [168] "newly_infected_black_hrh"
## [169] "newly_infected_black_msm"
## [170] "newly_infected_black_tgw"
## [171] "newly_infected_latinx_hrh"
## [172] "newly_infected_latinx_msm"
## [173] "newly_infected_latinx_tgw"
## [174] "newly_infected_white_msm"
## [175] "on_art"
## [176] "on_prep"
## [177] "overlaps"
## [178] "pop"
## [179] "sc_casual_sex_with_condom"
## [180] "sc_casual_sex_without_condom"
## [181] "sc_steady_sex_with_condom"
## [182] "sc_steady_sex_without_condom"
## [183] "sd_casual_sex_with_condom"
## [184] "sd_casual_sex_without_condom"
## [185] "sd_steady_sex_with_condom"
## [186] "sd_steady_sex_without_condom"
## [187] "sex_acts"
## [188] "steady_edge_count"
## [189] "steady_sex_acts"
## [190] "steady_sex_with_condom_oral"
## [191] "steady_sex_without_condom_oral"
## [192] "syphilis_infected"
## [193] "syphilis_infected_via_transmission"
## [194] "syphilis_positives_infected_with_hiv"
## [195] "syphilis_tests"
## [196] "syphilis_treatments"
## [197] "syphilis_uninfected"
## [198] "tick"
## [199] "total_infected_black_hrh"
## [200] "total_infected_black_msm"
## [201] "total_infected_black_tgw"
## [202] "total_infected_latinx_hrh"
## [203] "total_infected_latinx_msm"
## [204] "total_infected_latinx_tgw"
## [205] "total_infected_white_msm"
## [206] "total_uninfected_black_msm"
## [207] "total_uninfected_black_tgw"
## [208] "total_uninfected_latinx_hrh"
## [209] "total_uninfected_latinx_msm"
## [210] "total_uninfected_latinx_tgw"
## [211] "total_uninfected_white_msm"
## [212] "totla_uninfected_black_hrh"
## [213] "uninfected"
## [214] "uninfected_18"
## [215] "uninfected_19"
## [216] "uninfected_20"
## [217] "uninfected_21"
## [218] "uninfected_22"
## [219] "uninfected_23"
## [220] "uninfected_24"
## [221] "uninfected_25"
## [222] "uninfected_26"
## [223] "uninfected_27"
## [224] "uninfected_28"
## [225] "uninfected_29"
## [226] "uninfected_30"
## [227] "uninfected_31"
## [228] "uninfected_32"
## [229] "uninfected_33"
## [230] "uninfected_34"
## [231] "uninfected_35"
## [232] "uninfected_36"
## [233] "uninfected_37"
## [234] "uninfected_38"
## [235] "uninfected_39"
## [236] "uninfected_40"
## [237] "uninfected_41"
## [238] "uninfected_42"
## [239] "uninfected_43"
## [240] "uninfected_44"
## [241] "uninfected_45"
## [242] "uninfected_46"
## [243] "uninfected_47"
## [244] "uninfected_48"
## [245] "uninfected_49"
## [246] "uninfected_50"
## [247] "uninfected_51"
## [248] "uninfected_52"
## [249] "uninfected_53"
## [250] "uninfected_54"
## [251] "uninfected_55"
## [252] "uninfected_56"
## [253] "uninfected_57"
## [254] "uninfected_58"
## [255] "uninfected_59"
## [256] "uninfected_60"
## [257] "uninfected_61"
## [258] "uninfected_62"
## [259] "uninfected_63"
## [260] "uninfected_64"
## [261] "uninfected_65"
## [262] "uninfected_ever_jailed"
## [263] "uninfected_jail_pop"
## [264] "uninfected_never_jailed"
## [265] "vertex_count"
## [266] "vertex_count_18"
## [267] "vertex_count_19"
## [268] "vertex_count_20"
## [269] "vertex_count_21"
## [270] "vertex_count_22"
## [271] "vertex_count_23"
## [272] "vertex_count_24"
## [273] "vertex_count_25"
## [274] "vertex_count_26"
## [275] "vertex_count_27"
## [276] "vertex_count_28"
## [277] "vertex_count_29"
## [278] "vertex_count_30"
## [279] "vertex_count_31"
## [280] "vertex_count_32"
## [281] "vertex_count_33"
## [282] "vertex_count_34"
## [283] "vertex_count_35"
## [284] "vertex_count_36"
## [285] "vertex_count_37"
## [286] "vertex_count_38"
## [287] "vertex_count_39"
## [288] "vertex_count_40"
## [289] "vertex_count_41"
## [290] "vertex_count_42"
## [291] "vertex_count_43"
## [292] "vertex_count_44"
## [293] "vertex_count_45"
## [294] "vertex_count_46"
## [295] "vertex_count_47"
## [296] "vertex_count_48"
## [297] "vertex_count_49"
## [298] "vertex_count_50"
## [299] "vertex_count_51"
## [300] "vertex_count_52"
## [301] "vertex_count_53"
## [302] "vertex_count_54"
## [303] "vertex_count_55"
## [304] "vertex_count_56"
## [305] "vertex_count_57"
## [306] "vertex_count_58"
## [307] "vertex_count_59"
## [308] "vertex_count_60"
## [309] "vertex_count_61"
## [310] "vertex_count_62"
## [311] "vertex_count_63"
## [312] "vertex_count_64"
## [313] "vertex_count_65"
## [314] "vertex_count_ever_jailed"
## [315] "vertex_count_never_jailed"
## [316] "vl_supp_per_diagnosed"
## [317] "vl_supp_per_positives"
# population size
ggplot()+
theme_bw()+
geom_line(data = counts,
aes(x=tick, y=vertex_count)
)
# syphilis infections
ggplot()+
theme_bw()+
geom_line(data = counts,
aes(x=tick, y=syphilis_infected)
)
# syphilis infections
ggplot()+
theme_bw()+
geom_line(data = counts,
aes(x=tick, y=syphilis_tests)
)
ggplot()+
theme_bw()+
geom_line(data = counts,
aes(x=tick, y=syphilis_treatments)
)
ggplot()+
theme_bw()+
geom_line(data = counts,
aes(x=tick, y=syphilis_positives_infected_with_hiv)
)
ggplot()+
theme_bw()+
geom_line(data = counts,
aes(x=tick, y=hiv_positives_infected_with_syphilis)
)
ggplot(data = counts)+
theme_bw()+
geom_line(aes(x=tick, y=casual_sex_acts))+
geom_line(aes(x=tick, y=casual_sex_with_condom_oral))+
geom_line(aes(x=tick, y=casual_sex_without_condom_oral))
ggplot(data = counts)+
theme_bw()+
geom_line(aes(x=tick, y=steady_sex_acts))+
geom_line(aes(x=tick, y=steady_sex_with_condom_oral))+
geom_line(aes(x=tick, y=steady_sex_without_condom_oral))
