From 44f4280660701a8f245f46583b46dbc3ee26f152 Mon Sep 17 00:00:00 2001
From: AFg6K7h4fhy2 <127630341+AFg6K7h4fhy2@users.noreply.github.com>
Date: Thu, 5 Sep 2024 13:50:11 -0400
Subject: [PATCH] ignore extraneous comments

---
 model_comparison/compare.R             | 175 +++++++++++++++++++++++++
 pyrenew_flu_light/__init__.py          |   2 -
 pyrenew_flu_light/checks.py            |   6 +-
 pyrenew_flu_light/comp_inf.py          |   6 +-
 pyrenew_flu_light/comp_obs.py          |   4 +-
 pyrenew_flu_light/comp_tran.py         |  10 +-
 pyrenew_flu_light/compare.py           |   4 +-
 pyrenew_flu_light/filtered_data_NY     | 164 +++++++++++++++++++++++
 pyrenew_flu_light/model.py             |   6 +-
 pyrenew_flu_light/pad.py               |   2 -
 pyrenew_flu_light/plot.py              |   8 +-
 pyrenew_flu_light/post.py              |   2 -
 pyrenew_flu_light/pre.py               |   2 -
 pyrenew_flu_light/run.py               |   6 +-
 pyrenew_flu_light/tut_epim_port_msr.py |  44 +++----
 15 files changed, 377 insertions(+), 64 deletions(-)
 create mode 100644 model_comparison/compare.R
 create mode 100644 pyrenew_flu_light/filtered_data_NY

diff --git a/model_comparison/compare.R b/model_comparison/compare.R
new file mode 100644
index 0000000..ba91bad
--- /dev/null
+++ b/model_comparison/compare.R
@@ -0,0 +1,175 @@
+library(dplyr)
+library(tidyr)
+library(readr)
+library(lubridate)
+library(forecasttools)
+
+read_posterior_samples <- function(file_path) {
+  posterior_samples <- read_csv(file_path)
+  return(posterior_samples)
+}
+
+pivot_forecast_to_long <- function(
+  posterior_samples,
+  signal_name = "hosp",
+  time_name = "date"
+) {
+  draws_wide <- tibble::tibble(as.data.frame(posterior_samples))
+  names(draws_wide) <- posterior_samples$time
+  draws_long <- draws_wide %>%
+    dplyr::mutate(.draw = dplyr::row_number()) %>%
+    tidyr::pivot_longer(cols = -.draw, names_to = time_name, values_to = signal_name)
+  return(draws_long)
+}
+aggregate_to_epiweekly <- function(tidy_daily_trajectories) {
+  epiweekly_forecasts <- forecasttools::daily_to_epiweekly(
+    tidy_daily_trajectories,
+    value_col = "hosp",
+    id_cols = c(".draw"),
+    weekly_value_name = "weekly_hosp"
+  )
+  return(epiweekly_forecasts)
+}
+
+output_flusight_table <- function(
+  weekly_forecasts,
+  reference_date,
+  horizons,
+  output_path
+) {
+  formatted_output <- forecasttools::trajectories_to_quantiles(
+    weekly_forecasts,
+    timepoint_cols = c("epiweek", "epiyear"),
+    value_col = "weekly_hosp"
+  ) %>%
+    dplyr::mutate(
+      location = forecasttools::loc_abbr_to_flusight_code(state)
+    ) %>%
+    forecasttools::get_flusight_table(
+      reference_date,
+      horizons = horizons
+    )
+
+  readr::write_csv(formatted_output, output_path)
+  return(formatted_output)
+}
+
+generate_flusight_output <- function(file_paths, reference_date, horizons, output_path) {
+  for (file_path in file_paths) {
+    posterior_samples <- read_posterior_samples(file_path)
+    daily_forecasts <- pivot_forecast_to_long(posterior_samples)
+    weekly_forecasts <- aggregate_to_epiweekly(daily_forecasts)
+    formatted_output <- output_flusight_table(weekly_forecasts, reference_date, horizons, output_path)
+  }
+}
+
+
+file_paths <- c(
+  "posterior_predictive_forecasts_test_NY_2024-01-20.csv")
+reference_date <- "2024-01-20"
+horizons <- -1:3
+output_path <- "flusight_forecast_output_PFL_test_NY_2024-01-20.csv"
+
+generate_flusight_output(
+  file_paths,
+  reference_date,
+  horizons,
+  output_path)
+
+
+
+
+
+
+
+# library(forecasttools)
+# library(tibble)
+# library(dplyr)
+# library(readr)
+# library(lubridate)
+
+# pyrenew_flusight_forecast_from_csv <- function(
+#     spread_draws_csv,
+#     fitting_data_csv,
+#     output_path,
+#     reference_date,
+#     horizons = -1:3,
+#     seed = NULL
+# ) {
+#   set.seed(seed)
+#   # read data from pyrenew-flu-light run
+#   spread_draws <- read_csv(spread_draws_csv)
+#   fitting_data <- read_csv(fitting_data_csv)
+#   # retrieve locations from fitting data
+#   locations <- unique(fitting_data$location)
+#   # parse over and collect forecasts and fitting data
+#   state_daily_forecast_list <- list()
+#   for (loc in locations) {
+#     state_fitting_data <- fitting_data %>% filter(location == loc)
+#     state_forecast <- spread_draws %>% filter(negbinom_rv_dim_0_index == loc)
+#     # forecasttools convert spread draws tiddy
+#     state_forecast_long <- state_forecast %>%
+#       dplyr::mutate(.draw = draw) %>%
+#       dplyr::select(.draw, date = negbinom_rv_dim_0_index, hosp = negbinom_rv)
+#     # go to epiweekly from daily
+#     state_weekly_forecasts <- forecasttools::daily_to_epiweekly(
+#       tidy_daily_trajectories = state_forecast_long,
+#       value_col = "hosp",
+#       date_col = "date",
+#       id_cols = ".draw"
+#     )
+#     state_daily_forecast_list[[loc]] <- state_weekly_forecasts
+#   }
+#   cli::cli_inform("Formatting output for FluSight...")
+#   # flusight formatting
+#   state_flusight_tables <- list()
+#   full_table <- tibble::tibble()
+#   for (state in names(state_daily_forecast_list)) {
+#     state_flusight_table <- forecasttools::trajectories_to_quantiles(
+#       state_daily_forecast_list[[state]],
+#       timepoint_cols = c("epiweek", "epiyear"),
+#       value_col = "weekly_hosp"
+#     ) %>%
+#       dplyr::mutate(
+#         location = forecasttools::loc_abbr_to_flusight_code(state)
+#       ) %>%
+#       forecasttools:::get_flusight_table(
+#         reference_date,
+#         horizons = horizons
+#       )
+
+#     full_table <- dplyr::bind_rows(
+#       full_table,
+#       state_flusight_table
+#     )
+#   }
+#   full_table <- full_table %>%
+#     dplyr::arrange(
+#       location,
+#       reference_date,
+#       horizon,
+#       output_type,
+#       output_type_id
+#     )
+#   # save
+#   readr::write_csv(
+#     full_table,
+#     output_path
+#   )
+#   return(full_table)
+# }
+
+# spread_draws_csv <- "AL_2024-03-30_28_NegBinRv.csv"
+# fitting_data_csv <- "filtered_data_AL.csv"
+# output_path <- "flusight_output_AL.csv"
+# reference_date <- "2024-03-30"
+# horizons <- -1:3
+
+# run_forecast_with_csvs(
+#     spread_draws_csv,
+#     fitting_data_csv,
+#     output_path,
+#     reference_date,
+#     horizons,
+#     seed = 62352
+# )
diff --git a/pyrenew_flu_light/__init__.py b/pyrenew_flu_light/__init__.py
index 1e3a2c3..52a708b 100644
--- a/pyrenew_flu_light/__init__.py
+++ b/pyrenew_flu_light/__init__.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 from checks import (
     assert_historical_data_files_exist,
     check_file_path_valid,
diff --git a/pyrenew_flu_light/checks.py b/pyrenew_flu_light/checks.py
index e49f6b2..191facb 100644
--- a/pyrenew_flu_light/checks.py
+++ b/pyrenew_flu_light/checks.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 Methods to verify pathing and existence
 of certain files for use of pyrenew-flu-light.
@@ -62,7 +60,7 @@ def load_config(config_path: str) -> dict[str, any]:
     return config
 
 
-def ensure_output_directory(args: dict[str, any]):  # numpydoc ignore=GL08
+def ensure_output_directory(args: dict[str, any]):
     output_directory = "./output/"
     if not os.path.exists(output_directory):
         os.makedirs(output_directory)
@@ -79,7 +77,7 @@ def ensure_output_directory(args: dict[str, any]):  # numpydoc ignore=GL08
 
 def assert_historical_data_files_exist(
     reporting_date: str,
-):  # numpydoc ignore=GL08
+):
     data_directory = f"../model_comparison/data/{reporting_date}/"
     assert os.path.exists(
         data_directory
diff --git a/pyrenew_flu_light/comp_inf.py b/pyrenew_flu_light/comp_inf.py
index 3073f47..f04f91e 100644
--- a/pyrenew_flu_light/comp_inf.py
+++ b/pyrenew_flu_light/comp_inf.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 The infections process component in pyrenew-flu-light.
 """
@@ -36,7 +34,7 @@ def __init__(
         self,
         I0: ArrayLike,
         susceptibility_prior: numpyro.distributions,
-    ):  # numpydoc ignore=GL08
+    ):
         logging.info("Initializing CFAEPIM_Infections")
 
         self.I0 = I0
@@ -138,7 +136,7 @@ def sample(
         # calculate initial susceptible population S_{v-1}
         init_S = init_S_proportion * P
 
-        def update_infections(carry, Rt):  # numpydoc ignore=GL08
+        def update_infections(carry, Rt):
             S_t, I_recent = carry
 
             # compute raw infections
diff --git a/pyrenew_flu_light/comp_obs.py b/pyrenew_flu_light/comp_obs.py
index 26c6c70..59f1bae 100644
--- a/pyrenew_flu_light/comp_obs.py
+++ b/pyrenew_flu_light/comp_obs.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 The observation process component in pyrenew-flu-light.
 """
@@ -44,7 +42,7 @@ def __init__(
         alpha_prior_dist,
         coefficient_priors,
         nb_concentration_prior,
-    ):  # numpydoc ignore=GL08
+    ):
         logging.info("Initializing CFAEPIM_Observation")
 
         # CFAEPIM_Observation.validate(
diff --git a/pyrenew_flu_light/comp_tran.py b/pyrenew_flu_light/comp_tran.py
index 0069aa1..5d170b1 100644
--- a/pyrenew_flu_light/comp_tran.py
+++ b/pyrenew_flu_light/comp_tran.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 The transmission process (Rt) component in pyrenew-flu-light.
 """
@@ -18,14 +16,14 @@
 from pyrenew.randomvariable import DistributionalVariable, TransformedVariable
 
 
-class CFAEPIM_Rt(RandomVariable):  # numpydoc ignore=GL08
+class CFAEPIM_Rt(RandomVariable):
     def __init__(
         self,
         intercept_RW_prior: numpyro.distributions,
         max_rt: float,
         gamma_RW_prior_scale: float,
         week_indices: ArrayLike,
-    ):  # numpydoc ignore=GL08
+    ):
         """
         Initialize the CFAEPIM_Rt class.
 
@@ -55,7 +53,7 @@ def validate(
         max_rt: any,
         gamma_RW_prior_scale: any,
         week_indices: any,
-    ) -> None:  # numpydoc ignore=GL08
+    ) -> None:
         """
         Validate the parameters of the CFAEPIM_Rt class.
 
@@ -85,7 +83,7 @@ def validate(
                 f"week_indices must be an array-like structure; was type {type(week_indices)}"
             )
 
-    def sample(self, n_steps: int, **kwargs) -> tuple:  # numpydoc ignore=GL08
+    def sample(self, n_steps: int, **kwargs) -> tuple:
         """
         Sample the Rt values using a random walk process
         and broadcast them to daily values.
diff --git a/pyrenew_flu_light/compare.py b/pyrenew_flu_light/compare.py
index bc6e1de..3c1bb31 100644
--- a/pyrenew_flu_light/compare.py
+++ b/pyrenew_flu_light/compare.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 Comparisons made between posterior samples.
 """
@@ -18,7 +16,7 @@ def quantilize_forecasts(
     fitting_data,
     output_path,
     reference_date,
-):  # numpydoc ignore=GL08
+):
     pandas2ri.activate()
     forecasttools = importr("forecasttools")
     # dplyr = importr("dplyr")
diff --git a/pyrenew_flu_light/filtered_data_NY b/pyrenew_flu_light/filtered_data_NY
new file mode 100644
index 0000000..527a158
--- /dev/null
+++ b/pyrenew_flu_light/filtered_data_NY
@@ -0,0 +1,164 @@
+location,date,hosp,epiweek,epiyear,day_of_week,is_weekend,is_holiday,is_post_holiday,recency,week,location_code,population,first_week_hosp,nonobservation_period
+NY,2023-09-01,0,35,2023,Fri,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-02,0,35,2023,Sat,true,false,false,0,3,36,19835913,2,true
+NY,2023-09-03,0,36,2023,Sun,true,false,false,0,3,36,19835913,2,true
+NY,2023-09-04,0,36,2023,Mon,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-05,0,36,2023,Tue,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-06,0,36,2023,Wed,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-07,0,36,2023,Thu,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-08,0,36,2023,Fri,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-09,0,36,2023,Sat,true,false,false,0,3,36,19835913,2,true
+NY,2023-09-10,0,37,2023,Sun,true,false,false,0,3,36,19835913,2,true
+NY,2023-09-11,0,37,2023,Mon,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-12,0,37,2023,Tue,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-13,0,37,2023,Wed,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-14,0,37,2023,Thu,false,false,false,0,3,36,19835913,2,true
+NY,2023-09-15,1,37,2023,Fri,false,false,false,0,3,36,19835913,2,false
+NY,2023-09-16,1,37,2023,Sat,true,false,false,0,3,36,19835913,2,false
+NY,2023-09-17,2,38,2023,Sun,true,false,false,0,4,36,19835913,2,false
+NY,2023-09-18,2,38,2023,Mon,false,false,false,0,4,36,19835913,2,false
+NY,2023-09-19,2,38,2023,Tue,false,false,false,0,4,36,19835913,2,false
+NY,2023-09-20,4,38,2023,Wed,false,false,false,0,4,36,19835913,2,false
+NY,2023-09-21,4,38,2023,Thu,false,false,false,0,4,36,19835913,2,false
+NY,2023-09-22,2,38,2023,Fri,false,false,false,0,4,36,19835913,2,false
+NY,2023-09-23,3,38,2023,Sat,true,false,false,0,4,36,19835913,2,false
+NY,2023-09-24,9,39,2023,Sun,true,false,false,0,5,36,19835913,2,false
+NY,2023-09-25,4,39,2023,Mon,false,false,false,0,5,36,19835913,2,false
+NY,2023-09-26,5,39,2023,Tue,false,false,false,0,5,36,19835913,2,false
+NY,2023-09-27,7,39,2023,Wed,false,false,false,0,5,36,19835913,2,false
+NY,2023-09-28,10,39,2023,Thu,false,false,false,0,5,36,19835913,2,false
+NY,2023-09-29,7,39,2023,Fri,false,false,false,0,5,36,19835913,2,false
+NY,2023-09-30,6,39,2023,Sat,true,false,false,0,5,36,19835913,2,false
+NY,2023-10-01,1,40,2023,Sun,true,false,false,0,6,36,19835913,2,false
+NY,2023-10-02,5,40,2023,Mon,false,false,false,0,6,36,19835913,2,false
+NY,2023-10-03,8,40,2023,Tue,false,false,false,0,6,36,19835913,2,false
+NY,2023-10-04,4,40,2023,Wed,false,false,false,0,6,36,19835913,2,false
+NY,2023-10-05,8,40,2023,Thu,false,false,false,0,6,36,19835913,2,false
+NY,2023-10-06,4,40,2023,Fri,false,false,false,0,6,36,19835913,2,false
+NY,2023-10-07,7,40,2023,Sat,true,false,false,0,6,36,19835913,2,false
+NY,2023-10-08,6,41,2023,Sun,true,false,false,0,7,36,19835913,2,false
+NY,2023-10-09,4,41,2023,Mon,false,false,false,0,7,36,19835913,2,false
+NY,2023-10-10,2,41,2023,Tue,false,false,false,0,7,36,19835913,2,false
+NY,2023-10-11,5,41,2023,Wed,false,false,false,0,7,36,19835913,2,false
+NY,2023-10-12,2,41,2023,Thu,false,false,false,0,7,36,19835913,2,false
+NY,2023-10-13,4,41,2023,Fri,false,false,false,0,7,36,19835913,2,false
+NY,2023-10-14,3,41,2023,Sat,true,false,false,0,7,36,19835913,2,false
+NY,2023-10-15,4,42,2023,Sun,true,false,false,0,8,36,19835913,2,false
+NY,2023-10-16,3,42,2023,Mon,false,false,false,0,8,36,19835913,2,false
+NY,2023-10-17,5,42,2023,Tue,false,false,false,0,8,36,19835913,2,false
+NY,2023-10-18,8,42,2023,Wed,false,false,false,0,8,36,19835913,2,false
+NY,2023-10-19,8,42,2023,Thu,false,false,false,0,8,36,19835913,2,false
+NY,2023-10-20,5,42,2023,Fri,false,false,false,0,8,36,19835913,2,false
+NY,2023-10-21,4,42,2023,Sat,true,false,false,0,8,36,19835913,2,false
+NY,2023-10-22,7,43,2023,Sun,true,false,false,0,9,36,19835913,2,false
+NY,2023-10-23,3,43,2023,Mon,false,false,false,0,9,36,19835913,2,false
+NY,2023-10-24,9,43,2023,Tue,false,false,false,0,9,36,19835913,2,false
+NY,2023-10-25,6,43,2023,Wed,false,false,false,0,9,36,19835913,2,false
+NY,2023-10-26,6,43,2023,Thu,false,false,false,0,9,36,19835913,2,false
+NY,2023-10-27,9,43,2023,Fri,false,false,false,0,9,36,19835913,2,false
+NY,2023-10-28,8,43,2023,Sat,true,false,false,0,9,36,19835913,2,false
+NY,2023-10-29,6,44,2023,Sun,true,false,false,0,10,36,19835913,2,false
+NY,2023-10-30,9,44,2023,Mon,false,false,false,0,10,36,19835913,2,false
+NY,2023-10-31,6,44,2023,Tue,false,false,false,0,10,36,19835913,2,false
+NY,2023-11-01,10,44,2023,Wed,false,false,false,0,10,36,19835913,2,false
+NY,2023-11-02,12,44,2023,Thu,false,false,false,0,10,36,19835913,2,false
+NY,2023-11-03,9,44,2023,Fri,false,false,false,0,10,36,19835913,2,false
+NY,2023-11-04,5,44,2023,Sat,true,false,false,0,10,36,19835913,2,false
+NY,2023-11-05,14,45,2023,Sun,true,false,false,0,11,36,19835913,2,false
+NY,2023-11-06,10,45,2023,Mon,false,false,false,0,11,36,19835913,2,false
+NY,2023-11-07,14,45,2023,Tue,false,false,false,0,11,36,19835913,2,false
+NY,2023-11-08,15,45,2023,Wed,false,false,false,0,11,36,19835913,2,false
+NY,2023-11-09,11,45,2023,Thu,false,false,false,0,11,36,19835913,2,false
+NY,2023-11-10,14,45,2023,Fri,false,false,false,0,11,36,19835913,2,false
+NY,2023-11-11,10,45,2023,Sat,true,false,false,0,11,36,19835913,2,false
+NY,2023-11-12,9,46,2023,Sun,true,false,false,0,12,36,19835913,2,false
+NY,2023-11-13,9,46,2023,Mon,false,false,false,0,12,36,19835913,2,false
+NY,2023-11-14,23,46,2023,Tue,false,false,false,0,12,36,19835913,2,false
+NY,2023-11-15,21,46,2023,Wed,false,false,false,0,12,36,19835913,2,false
+NY,2023-11-16,22,46,2023,Thu,false,false,false,0,12,36,19835913,2,false
+NY,2023-11-17,22,46,2023,Fri,false,false,false,0,12,36,19835913,2,false
+NY,2023-11-18,17,46,2023,Sat,true,false,false,0,12,36,19835913,2,false
+NY,2023-11-19,20,47,2023,Sun,true,false,false,0,13,36,19835913,2,false
+NY,2023-11-20,25,47,2023,Mon,false,false,false,0,13,36,19835913,2,false
+NY,2023-11-21,20,47,2023,Tue,false,false,false,0,13,36,19835913,2,false
+NY,2023-11-22,24,47,2023,Wed,false,false,false,0,13,36,19835913,2,false
+NY,2023-11-23,18,47,2023,Thu,false,true,false,0,13,36,19835913,2,false
+NY,2023-11-24,27,47,2023,Fri,false,false,true,0,13,36,19835913,2,false
+NY,2023-11-25,44,47,2023,Sat,true,false,false,0,13,36,19835913,2,false
+NY,2023-11-26,39,48,2023,Sun,true,false,false,0,14,36,19835913,2,false
+NY,2023-11-27,36,48,2023,Mon,false,false,false,0,14,36,19835913,2,false
+NY,2023-11-28,54,48,2023,Tue,false,false,false,0,14,36,19835913,2,false
+NY,2023-11-29,56,48,2023,Wed,false,false,false,0,14,36,19835913,2,false
+NY,2023-11-30,55,48,2023,Thu,false,false,false,0,14,36,19835913,2,false
+NY,2023-12-01,57,48,2023,Fri,false,false,false,0,14,36,19835913,2,false
+NY,2023-12-02,48,48,2023,Sat,true,false,false,0,14,36,19835913,2,false
+NY,2023-12-03,58,49,2023,Sun,true,false,false,0,15,36,19835913,2,false
+NY,2023-12-04,57,49,2023,Mon,false,false,false,0,15,36,19835913,2,false
+NY,2023-12-05,78,49,2023,Tue,false,false,false,0,15,36,19835913,2,false
+NY,2023-12-06,76,49,2023,Wed,false,false,false,0,15,36,19835913,2,false
+NY,2023-12-07,71,49,2023,Thu,false,false,false,0,15,36,19835913,2,false
+NY,2023-12-08,84,49,2023,Fri,false,false,false,0,15,36,19835913,2,false
+NY,2023-12-09,85,49,2023,Sat,true,false,false,0,15,36,19835913,2,false
+NY,2023-12-10,92,50,2023,Sun,true,false,false,0,16,36,19835913,2,false
+NY,2023-12-11,98,50,2023,Mon,false,false,false,0,16,36,19835913,2,false
+NY,2023-12-12,101,50,2023,Tue,false,false,false,0,16,36,19835913,2,false
+NY,2023-12-13,117,50,2023,Wed,false,false,false,0,16,36,19835913,2,false
+NY,2023-12-14,116,50,2023,Thu,false,false,false,0,16,36,19835913,2,false
+NY,2023-12-15,132,50,2023,Fri,false,false,false,0,16,36,19835913,2,false
+NY,2023-12-16,88,50,2023,Sat,true,false,false,0,16,36,19835913,2,false
+NY,2023-12-17,105,51,2023,Sun,true,false,false,0,17,36,19835913,2,false
+NY,2023-12-18,134,51,2023,Mon,false,false,false,0,17,36,19835913,2,false
+NY,2023-12-19,153,51,2023,Tue,false,false,false,0,17,36,19835913,2,false
+NY,2023-12-20,143,51,2023,Wed,false,false,false,0,17,36,19835913,2,false
+NY,2023-12-21,144,51,2023,Thu,false,false,false,0,17,36,19835913,2,false
+NY,2023-12-22,131,51,2023,Fri,false,false,false,0,17,36,19835913,2,false
+NY,2023-12-23,125,51,2023,Sat,true,false,false,0,17,36,19835913,2,false
+NY,2023-12-24,147,52,2023,Sun,true,false,false,0,18,36,19835913,2,false
+NY,2023-12-25,142,52,2023,Mon,false,true,false,0,18,36,19835913,2,false
+NY,2023-12-26,161,52,2023,Tue,false,false,true,0,18,36,19835913,2,false
+NY,2023-12-27,217,52,2023,Wed,false,false,false,0,18,36,19835913,2,false
+NY,2023-12-28,211,52,2023,Thu,false,false,false,0,18,36,19835913,2,false
+NY,2023-12-29,237,52,2023,Fri,false,false,false,0,18,36,19835913,2,false
+NY,2023-12-30,230,52,2023,Sat,true,false,false,0,18,36,19835913,2,false
+NY,2023-12-31,195,1,2024,Sun,true,true,false,0,19,36,19835913,2,false
+NY,2024-01-01,186,1,2024,Mon,false,true,false,0,19,36,19835913,2,false
+NY,2024-01-02,191,1,2024,Tue,false,false,true,0,19,36,19835913,2,false
+NY,2024-01-03,211,1,2024,Wed,false,false,false,0,19,36,19835913,2,false
+NY,2024-01-04,191,1,2024,Thu,false,false,false,0,19,36,19835913,2,false
+NY,2024-01-05,146,1,2024,Fri,false,false,false,0,19,36,19835913,2,false
+NY,2024-01-06,129,1,2024,Sat,true,false,false,0,19,36,19835913,2,false
+NY,2024-01-07,120,2,2024,Sun,true,false,false,0,20,36,19835913,2,false
+NY,2024-01-08,124,2,2024,Mon,false,false,false,0,20,36,19835913,2,false
+NY,2024-01-09,167,2,2024,Tue,false,false,false,0,20,36,19835913,2,false
+NY,2024-01-10,140,2,2024,Wed,false,false,false,0,20,36,19835913,2,false
+NY,2024-01-11,137,2,2024,Thu,false,false,false,0,20,36,19835913,2,false
+NY,2024-01-12,135,2,2024,Fri,false,false,false,1,20,36,19835913,2,false
+NY,2024-01-13,112,2,2024,Sat,true,false,false,2,20,36,19835913,2,false
+NY,2024-01-14,-9999,3,2024,Sun,true,false,false,0,21,36,19835913,2,false
+NY,2024-01-15,-9999,3,2024,Mon,false,false,false,0,21,36,19835913,2,false
+NY,2024-01-16,-9999,3,2024,Tue,false,false,false,0,21,36,19835913,2,false
+NY,2024-01-17,-9999,3,2024,Wed,false,false,false,0,21,36,19835913,2,false
+NY,2024-01-18,-9999,3,2024,Thu,false,false,false,0,21,36,19835913,2,false
+NY,2024-01-19,-9999,3,2024,Fri,false,false,false,0,21,36,19835913,2,false
+NY,2024-01-20,-9999,3,2024,Sat,true,false,false,0,21,36,19835913,2,false
+NY,2024-01-21,-9999,4,2024,Sun,true,false,false,0,22,36,19835913,2,false
+NY,2024-01-22,-9999,4,2024,Mon,false,false,false,0,22,36,19835913,2,false
+NY,2024-01-23,-9999,4,2024,Tue,false,false,false,0,22,36,19835913,2,false
+NY,2024-01-24,-9999,4,2024,Wed,false,false,false,0,22,36,19835913,2,false
+NY,2024-01-25,-9999,4,2024,Thu,false,false,false,0,22,36,19835913,2,false
+NY,2024-01-26,-9999,4,2024,Fri,false,false,false,0,22,36,19835913,2,false
+NY,2024-01-27,-9999,4,2024,Sat,true,false,false,0,22,36,19835913,2,false
+NY,2024-01-28,-9999,5,2024,Sun,true,false,false,0,23,36,19835913,2,false
+NY,2024-01-29,-9999,5,2024,Mon,false,false,false,0,23,36,19835913,2,false
+NY,2024-01-30,-9999,5,2024,Tue,false,false,false,0,23,36,19835913,2,false
+NY,2024-01-31,-9999,5,2024,Wed,false,false,false,0,23,36,19835913,2,false
+NY,2024-02-01,-9999,5,2024,Thu,false,false,false,0,23,36,19835913,2,false
+NY,2024-02-02,-9999,5,2024,Fri,false,false,false,0,23,36,19835913,2,false
+NY,2024-02-03,-9999,5,2024,Sat,true,false,false,0,23,36,19835913,2,false
+NY,2024-02-04,-9999,6,2024,Sun,true,false,false,0,24,36,19835913,2,false
+NY,2024-02-05,-9999,6,2024,Mon,false,false,false,0,24,36,19835913,2,false
+NY,2024-02-06,-9999,6,2024,Tue,false,false,false,0,24,36,19835913,2,false
+NY,2024-02-07,-9999,6,2024,Wed,false,false,false,0,24,36,19835913,2,false
+NY,2024-02-08,-9999,6,2024,Thu,false,false,false,0,24,36,19835913,2,false
+NY,2024-02-09,-9999,6,2024,Fri,false,false,false,0,24,36,19835913,2,false
+NY,2024-02-10,-9999,6,2024,Sat,true,false,false,0,24,36,19835913,2,false
diff --git a/pyrenew_flu_light/model.py b/pyrenew_flu_light/model.py
index 99a94ca..464a6e2 100644
--- a/pyrenew_flu_light/model.py
+++ b/pyrenew_flu_light/model.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 The re-instantiated cfaepim model, with
 transmission, observation, and infection
@@ -28,7 +26,7 @@
 )
 
 
-class CFAEPIM_Model_Sample(NamedTuple):  # numpydoc ignore=GL08
+class CFAEPIM_Model_Sample(NamedTuple):
     Rts: SampledValue | None = None
     latent_infections: SampledValue | None = None
     susceptibles: SampledValue | None = None
@@ -76,7 +74,7 @@ def __init__(
         week_indices: ArrayLike,
         first_week_hosp: int,
         predictors: list[int],
-    ):  # numpydoc ignore=GL08
+    ):
         self.population = population
         self.week_indices = week_indices
         self.first_week_hosp = first_week_hosp
diff --git a/pyrenew_flu_light/pad.py b/pyrenew_flu_light/pad.py
index 9bc79a2..158c502 100644
--- a/pyrenew_flu_light/pad.py
+++ b/pyrenew_flu_light/pad.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 from datetime import datetime, timedelta
 
 import polars as pl
diff --git a/pyrenew_flu_light/plot.py b/pyrenew_flu_light/plot.py
index bec4c6e..0e996e9 100644
--- a/pyrenew_flu_light/plot.py
+++ b/pyrenew_flu_light/plot.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 Plotting utilities for using pyrenew-flu-light.
 """
@@ -8,7 +6,7 @@
 import matplotlib.pyplot as plt
 
 
-def plot_lm_arviz_fit(idata):  # numpydoc ignore=GL08
+def plot_lm_arviz_fit(idata):
     fig, ax = plt.subplots()
     az.plot_lm(
         "negbinom_rv",
@@ -24,14 +22,14 @@ def plot_lm_arviz_fit(idata):  # numpydoc ignore=GL08
     plt.show()
 
 
-def compute_eti(dataset, eti_prob):  # numpydoc ignore=GL08
+def compute_eti(dataset, eti_prob):
     eti_bdry = dataset.quantile(
         ((1 - eti_prob) / 2, 1 / 2 + eti_prob / 2), dim=("chain", "draw")
     )
     return eti_bdry.values.T
 
 
-def plot_hdi_arviz_for(idata, forecast_days):  # numpydoc ignore=GL08
+def plot_hdi_arviz_for(idata, forecast_days):
     x_data = idata.posterior_predictive["negbinom_rv_dim_0"] + forecast_days
     y_data = idata.posterior_predictive["negbinom_rv"]
     fig, axes = plt.subplots(figsize=(6, 5))
diff --git a/pyrenew_flu_light/post.py b/pyrenew_flu_light/post.py
index 42a1d84..6db6228 100644
--- a/pyrenew_flu_light/post.py
+++ b/pyrenew_flu_light/post.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 Save information regarding model performance
 and nature of model input and output.
diff --git a/pyrenew_flu_light/pre.py b/pyrenew_flu_light/pre.py
index 5e0874d..443e9b8 100644
--- a/pyrenew_flu_light/pre.py
+++ b/pyrenew_flu_light/pre.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 ETL system for pyrenew-flu-light.
 """
diff --git a/pyrenew_flu_light/run.py b/pyrenew_flu_light/run.py
index a59244c..9807e5a 100644
--- a/pyrenew_flu_light/run.py
+++ b/pyrenew_flu_light/run.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 import argparse
 import logging
 import os
@@ -12,7 +10,7 @@
 import pyrenew_flu_light
 
 
-def process_jurisdictions(value):  # numpydoc ignore=GL08
+def process_jurisdictions(value):
     if value.lower() == "all":
         return pyrenew_flu_light.JURISDICTIONS
     elif value.lower().startswith("not:"):
@@ -304,7 +302,7 @@ def spread_draws(
     return df
 
 
-def main(args):  # numpydoc ignore=GL08
+def main(args):
     """
     pyrenew-flu-light; to run:
 
diff --git a/pyrenew_flu_light/tut_epim_port_msr.py b/pyrenew_flu_light/tut_epim_port_msr.py
index 8dadf8c..b91099d 100644
--- a/pyrenew_flu_light/tut_epim_port_msr.py
+++ b/pyrenew_flu_light/tut_epim_port_msr.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-
 """
 Porting `cfa-forecast-renewal-epidemia`
 over to MSR. Validated on NHSN influenza
@@ -272,7 +270,7 @@ def load_config(config_path: str) -> dict[str, any]:
     return config
 
 
-def ensure_output_directory(args: dict[str, any]):  # numpydoc ignore=GL08
+def ensure_output_directory(args: dict[str, any]):
     output_directory = "./output/"
     if not os.path.exists(output_directory):
         os.makedirs(output_directory)
@@ -289,7 +287,7 @@ def ensure_output_directory(args: dict[str, any]):  # numpydoc ignore=GL08
 
 def assert_historical_data_files_exist(
     reporting_date: str,
-):  # numpydoc ignore=GL08
+):
     data_directory = f"../data/{reporting_date}/"
     assert os.path.exists(
         data_directory
@@ -318,7 +316,7 @@ def plot_utils(
     filename: str = "delete_me",
     save_as_img: bool = False,
     save_to_pdf: bool = False,
-) -> None | plt.Figure:  # numpydoc ignore=GL08
+) -> None | plt.Figure:
     if use_legend:
         axes.legend(loc="best")
     if use_log:
@@ -537,7 +535,7 @@ def __init__(
         self,
         I0: ArrayLike,
         susceptibility_prior: numpyro.distributions,
-    ):  # numpydoc ignore=GL08
+    ):
         logging.info("Initializing CFAEPIM_Infections")
 
         self.I0 = I0
@@ -639,7 +637,7 @@ def sample(
         # calculate initial susceptible population S_{v-1}
         init_S = init_S_proportion * P
 
-        def update_infections(carry, Rt):  # numpydoc ignore=GL08
+        def update_infections(carry, Rt):
             S_t, I_recent = carry
 
             # compute raw infections
@@ -699,7 +697,7 @@ def __init__(
         alpha_prior_dist,
         coefficient_priors,
         nb_concentration_prior,
-    ):  # numpydoc ignore=GL08
+    ):
         logging.info("Initializing CFAEPIM_Observation")
 
         # CFAEPIM_Observation.validate(
@@ -825,14 +823,14 @@ def sample(
         return alpha_samples, expected_hosp
 
 
-class CFAEPIM_Rt(RandomVariable):  # numpydoc ignore=GL08
+class CFAEPIM_Rt(RandomVariable):
     def __init__(
         self,
         intercept_RW_prior: numpyro.distributions,
         max_rt: float,
         gamma_RW_prior_scale: float,
         week_indices: ArrayLike,
-    ):  # numpydoc ignore=GL08
+    ):
         """
         Initialize the CFAEPIM_Rt class.
 
@@ -862,7 +860,7 @@ def validate(
         max_rt: any,
         gamma_RW_prior_scale: any,
         week_indices: any,
-    ) -> None:  # numpydoc ignore=GL08
+    ) -> None:
         """
         Validate the parameters of the CFAEPIM_Rt class.
 
@@ -892,7 +890,7 @@ def validate(
                 f"week_indices must be an array-like structure; was type {type(week_indices)}"
             )
 
-    def sample(self, n_steps: int, **kwargs) -> tuple:  # numpydoc ignore=GL08
+    def sample(self, n_steps: int, **kwargs) -> tuple:
         """
         Sample the Rt values using a random walk process
         and broadcast them to daily values.
@@ -940,7 +938,7 @@ def sample(self, n_steps: int, **kwargs) -> tuple:  # numpydoc ignore=GL08
         return broadcasted_rt_samples
 
 
-class CFAEPIM_Model_Sample(NamedTuple):  # numpydoc ignore=GL08
+class CFAEPIM_Model_Sample(NamedTuple):
     Rts: SampledValue | None = None
     latent_infections: SampledValue | None = None
     susceptibles: SampledValue | None = None
@@ -988,7 +986,7 @@ def __init__(
         week_indices: ArrayLike,
         first_week_hosp: int,
         predictors: list[int],
-    ):  # numpydoc ignore=GL08
+    ):
         self.population = population
         self.week_indices = week_indices
         self.first_week_hosp = first_week_hosp
@@ -1351,7 +1349,7 @@ def add_pre_observation_period(
     return merged_data
 
 
-def process_jurisdictions(value):  # numpydoc ignore=GL08
+def process_jurisdictions(value):
     if value.lower() == "all":
         return JURISDICTIONS
     elif value.lower().startswith("not:"):
@@ -1367,7 +1365,7 @@ def process_jurisdictions(value):  # numpydoc ignore=GL08
 #     config: dict[str, any],
 #     forecasting: bool = False,
 #     n_post_observation_days: int = 0,
-# ):  # numpydoc ignore=GL08
+# ):
 #     """
 #     Originally separated to support `model_render`;
 #     possibly reintegrated w/ `run_single_jurisdiction`.
@@ -1585,7 +1583,7 @@ def save_numpyro_model(
     config: dict[str, any],
     forecasting: bool = False,
     n_post_observation_days: int = 0,
-):  # numpydoc ignore=GL08
+):
     # check if the file exists
     if os.path.exists(save_path):
         pass
@@ -1604,7 +1602,7 @@ def save_numpyro_model(
 
 def template_save_file(
     title: str, save_path: str, figure_and_descriptions: list[tuple[str, str]]
-):  # numpydoc ignore=GL08
+):
     header_p1 = f"""
     ---
     title: "{title}"
@@ -1623,7 +1621,7 @@ def template_save_file(
             f.close()
 
 
-def convert_markdown_output_files_to_pdf():  # numpydoc ignore=GL08
+def convert_markdown_output_files_to_pdf():
     markdown_files = glob.glob("*.md")
     print(markdown_files)
     pass
@@ -1636,7 +1634,7 @@ def save_inference_content():
     pass
 
 
-def plot_lm_arviz_fit(idata):  # numpydoc ignore=GL08
+def plot_lm_arviz_fit(idata):
     fig, ax = plt.subplots()
     az.plot_lm(
         "negbinom_rv",
@@ -1652,14 +1650,14 @@ def plot_lm_arviz_fit(idata):  # numpydoc ignore=GL08
     plt.show()
 
 
-def compute_eti(dataset, eti_prob):  # numpydoc ignore=GL08
+def compute_eti(dataset, eti_prob):
     eti_bdry = dataset.quantile(
         ((1 - eti_prob) / 2, 1 / 2 + eti_prob / 2), dim=("chain", "draw")
     )
     return eti_bdry.values.T
 
 
-def plot_hdi_arviz_for(idata, forecast_days):  # numpydoc ignore=GL08
+def plot_hdi_arviz_for(idata, forecast_days):
     x_data = idata.posterior_predictive["negbinom_rv_dim_0"] + forecast_days
     y_data = idata.posterior_predictive["negbinom_rv"]
     fig, axes = plt.subplots(figsize=(6, 5))
@@ -1699,7 +1697,7 @@ def plot_hdi_arviz_for(idata, forecast_days):  # numpydoc ignore=GL08
     plt.show()
 
 
-def main(args):  # numpydoc ignore=GL08
+def main(args):
     """
     The `cfaepim` model required a configuration
     file and a dataset. The configuration file must