In danichusfu/RouteIdentification: Route and cluster assignment for NFL tracking data from NextGenStats

# devtools::install_github(repo = "danichusfu/RouteIdentification")
# 
# library(RouteIdentification)
# library(tidyverse)
# 
# cluster_controls <- generate_random_cluster_controls(number_of_clusters = 3)
# 
# nested_trajectory_data <-
#   generate_sample_data(cluster_controls, number_of_curves = 20) %>%
#   select(curve_i, x, y, cluster = cluster_num)
# 
# 
# em_results <-
#   nested_trajectory_data %>%
#   unnest(cols = c(x, y)) %>%
#   cluster_trajectory_data(K = 3)
# 
# 
# cluster_means <-
#   extract_cluster_means(em_results)
# 
# nested_trajectory_data %>%
#   bind_cols(as_tibble(em_results$Pik)) %>%
#   mutate(curve_i = row_number()) %>%
#   pivot_longer(names_to = "pred_cluster", values_to = "prob", matches("\\d")) %>%
#   mutate(pred_cluster = parse_number(pred_cluster)) %>%
#   group_by(curve_i) %>%
#   filter(prob == max(prob)) %>%
#   ungroup() %>%
#   count(cluster, pred_cluster)
# 
# nested_trajectory_data %>%
#   bind_cols(as_tibble(em_results$Pik)) %>%
#   mutate(curve_i = row_number()) %>%
#   pivot_longer(names_to = "pred_cluster", values_to = "prob", matches("\\d")) %>%
#   mutate(pred_cluster = parse_number(pred_cluster)) %>%
#   group_by(curve_i) %>%
#   filter(prob == max(prob)) %>%
#   unnest(cols = c(x, y)) %>%
# ggplot(aes(x = x, y = y, group = curve_i, colour = factor(cluster))) +
#   geom_path() +
#   facet_wrap(~ pred_cluster)
# 
# 
# ggplot(cluster_means, aes(x = V1, y = V2, colour = factor(cluster))) +
#   geom_path()+
#   facet_wrap(~ cluster)
# 
# new_nested_trajectory_data <-
#   generate_sample_data(cluster_controls) %>%
#   select(curve_i, x, y, cluster = cluster_num)
# 
# 
# new_trajectory_data <- new_nested_trajectory_data %>% unnest(cols = c(x, y))
# 
# new_data_fit <- fit_new_data(new_trajectory_data, em_results)
# 
# new_data_fit %>%
#   count(cluster, cluster_assigned)

danichusfu/RouteIdentification documentation built on March 22, 2021, 9:01 p.m.