Brandon Hurr

@bhive01.bsky.social

146 Followers 192 Following

Postharvest Physiology, #rstats, computer vision and datavis junkie, Fan of KC Sports. @bhive01@mastodon.social

A birds nest in the eve of a home. The nest is of an eastern Phoebe and has four eggs in it. One of which is clearly a cow bird egg.
Screen shot from a phone using the Merlin app that identifies bird calls. It found evidence of a Ring-billed Gull, American Robin, Purple Martin, Bank Swallow, Northern Cardinal, House Sparrow, and Red-winged Blackbird.
Photo of a small brown rabbit inside a house basking in the sunlight coming through a large sliding glass door. Bunny is fully relaxed and soaking it up.
Me drinking a beer. Man in black coat, dark green tshirt, glass in hand tipping a golden ale into his mouth. RIP
Ben Affleck outside a black door in a posh neighborhood. He's just taken a drag of a cigarette and has that look on his face of having just dealt with some real shit and needed the nicotine to calm down.
#day 3 library(tidyverse) process_mul_expressions <- function(mul_list) { mul_list |> map(~ str_extract_all(.x, "\\d+") |> unlist() |> as.numeric() |> reduce(`*`)) |> reduce(sum) } process_mul <- function(expression_list) { counting <- logical(length(expression_list)) current_state <- TRUE for (i in seq_along(expression_list)) { if (expression_list[i] == "don't()") { current_state <- FALSE } else if (expression_list[i] == "do()") { current_state <- TRUE } else { counting[i] <- current_state } } expression_list[counting & str_detect(expression_list, "^mul\\(")] |> process_mul_expressions() } #solution_1 tibble(input = readLines("~/Downloads/input_d3.txt")) |> mutate( mul_pull = stringr::str_extract_all(input, "mul\\(\\d+,\\d+\\)"), mul_sum = map_int(mul_pull, process_mul_expressions) ) |> pull(mul_sum) |> sum() # solution_2 tibble(input = readLines("~/Downloads/input_d3.txt")) |> mutate( mul_pull = stringr::str_extract_all(input, "mul\\(\\d+,\\d+\\)|do\\(\\)|don't\\(\\)") ) |> pull(mul_pull) |> unlist() |> process_mul() |> sum()
# day 2 library(tidyverse) test_safety <- function(df_test){ df_test |> mutate( lag_vec = map(num_vec, ~diff(.x)), unsafe_dec = map_lgl(lag_vec, ~any(.x < -3)), unsafe_asc = map_lgl(lag_vec, ~any(.x > 3)), unsafe_flat = map_lgl(lag_vec, ~any(.x == 0)), unsafe_sign = map_lgl(lag_vec, ~any(diff(sign(.x)) != 0)), safe = pmap_lgl(list(unsafe_dec, unsafe_asc, unsafe_flat, unsafe_sign), ~!(..1 || ..2 || ..3 || ..4)) ) } test_one_less_array <- function(array) { tibble(num = 1:length(array)) |> mutate( num_vec = map(num, ~array[-.x])) |> test_safety() } df <- tibble(str_vec = read_lines("~/Downloads/input_d2.txt")) |> mutate( num_vec = map(str_vec, ~as.integer(unlist(str_split(.x, " "))))) |> test_safety() solution_1 <- df |> pull(safe) |> sum() solution_1 solution_2 <- filter(df, !safe) |> mutate( one_less = map(num_vec, test_one_less_array), damp_safe = map_lgl(one_less, ~any(pull(.x, safe))) ) |> pull(damp_safe) |> sum() solution_1 + solution_2
# Day 1 df <- read_fwf("~/Downloads/input.txt", col_types = "nn") df |> mutate(across(everything(), ~sort(.x)), diff = abs(X1-X2)) |> pull(diff) |> sum() x2 <- pull(df, X2) df |> mutate( count = map_int(X1, ~sum(.x == x2)), mult = X1 * count ) |> pull(mult) |> sum()
Screen shot of the following R code: read_fwf("~/Downloads/input.txt", col_types = "nn") |> mutate(across(everything(), ~sort(.x)), diff = abs(X1-X2)) |> pull(diff) |> sum()
My desk according to ChatGPT. "a focused, professional workspace that highlights your dedication to plant science research, teaching preparation, and mentorship. " Shows a computer on a desk with plants in pots near a window and a flat of plantlets along with some test tubes and processed flavors. Lots of books and botanical themed things all over and me reading over a manuscript of some sort.