tests/testthat/_snaps/revision-latency-functions.md

In cmu-delphi/epiprocess: Tools for basic signal processing in epidemiology

revision_summary works for dummy datasets

Code
  dummy_ex %>% revision_summary() %>% print(n = 10, width = 300)
Message
  Min lag (time to first version):
Output
       min median     mean    max
    0 days 1 days 1.6 days 4 days
Message
  Fraction of epi_key+time_values with
  No revisions:
  * 3 out of 7 (42.86%)
  Quick revisions (last revision within 3 days of the `time_value`):
  * 4 out of 7 (57.14%)
  Few revisions (At most 3 revisions for that `time_value`):
  * 6 out of 7 (85.71%)
  Fraction of revised epi_key+time_values which have:
  Less than 0.1 spread in relative value:
  * 1 out of 4 (25%)
  Spread of more than 5.1 in actual value (when revised):
  * 3 out of 4 (75%)
  Days until within 20% of the latest value:
Output
       min median     mean     max
    0 days 3 days 6.9 days 19 days
  # A tibble: 7 x 11
    time_value geo_value n_revisions min_lag max_lag lag_near_latest spread
    <date>     <chr>           <dbl> <drtn>  <drtn>  <drtn>           <dbl>
  1 2020-01-01 ak                  4 2 days  19 days 19 days            101
  2 2020-01-02 ak                  1 4 days   5 days  4 days              9
  3 2020-01-03 ak                  0 3 days   3 days  3 days              0
  4 2020-01-01 al                  1 0 days  19 days 19 days             99
  5 2020-01-02 al                  0 0 days   0 days  0 days              0
  6 2020-01-03 al                  1 1 days   2 days  2 days              3
  7 2020-01-04 al                  0 1 days   1 days  1 days              0
    rel_spread min_value max_value median_value
         <dbl>     <dbl>     <dbl>        <dbl>
  1      0.990         1       102          6  
  2      0.09         91       100         95.5
  3    NaN             0         0          0  
  4      0.99          1       100         50.5
  5      0             1         1          1  
  6      0.75          1         4          2.5
  7      0             9         9          9

Code
  dummy_ex %>% revision_summary(drop_nas = FALSE) %>% print(n = 10, width = 300)
Message
  Min lag (time to first version):
Output
       min median     mean    max
    0 days 1 days 1.4 days 4 days
Message
  Fraction of all versions that are `NA`:
  * 2 out of 19 (10.53%)
  Fraction of epi_key+time_values with
  No revisions:
  * 2 out of 7 (28.57%)
  Quick revisions (last revision within 3 days of the `time_value`):
  * 4 out of 7 (57.14%)
  Few revisions (At most 3 revisions for that `time_value`):
  * 6 out of 7 (85.71%)
  Fraction of revised epi_key+time_values which have:
  Less than 0.1 spread in relative value:
  * 2 out of 5 (40%)
  Spread of more than 5.1 in actual value (when revised):
  * 3 out of 5 (60%)
  Days until within 20% of the latest value:
Output
       min median     mean     max
    0 days 3 days 6.9 days 19 days
  # A tibble: 7 x 11
    time_value geo_value n_revisions min_lag max_lag lag_near_latest spread
    <date>     <chr>           <dbl> <drtn>  <drtn>  <drtn>           <dbl>
  1 2020-01-01 ak                  6 2 days  19 days 19 days            101
  2 2020-01-02 ak                  1 4 days   5 days  4 days              9
  3 2020-01-03 ak                  0 3 days   3 days  3 days              0
  4 2020-01-01 al                  1 0 days  19 days 19 days             99
  5 2020-01-02 al                  0 0 days   0 days  0 days              0
  6 2020-01-03 al                  1 1 days   2 days  2 days              3
  7 2020-01-04 al                  1 0 days   1 days  1 days              0
    rel_spread min_value max_value median_value
         <dbl>     <dbl>     <dbl>        <dbl>
  1      0.990         1       102          5.5
  2      0.09         91       100         95.5
  3    NaN             0         0          0  
  4      0.99          1       100         50.5
  5      0             1         1          1  
  6      0.75          1         4          2.5
  7      0             9         9          9

Code
  dummy_ex_weekly %>% revision_summary(drop_nas = FALSE) %>% print(n = 10, width = 300)
Message
  Min lag (time to first version):
Output
        min  median      mean     max
    0 weeks 1 weeks 1.4 weeks 4 weeks
Message
  Fraction of all versions that are `NA`:
  * 2 out of 19 (10.53%)
  Fraction of epi_key+time_values with
  No revisions:
  * 2 out of 7 (28.57%)
  Quick revisions (last revision within 1 week of the `time_value`):
  * 2 out of 7 (28.57%)
  Few revisions (At most 3 revisions for that `time_value`):
  * 6 out of 7 (85.71%)
  Fraction of revised epi_key+time_values which have:
  Less than 0.1 spread in relative value:
  * 2 out of 5 (40%)
  Spread of more than 5.1 in actual value (when revised):
  * 3 out of 5 (60%)
  Weeks until within 20% of the latest value:
Output
        min  median      mean      max
    0 weeks 3 weeks 6.9 weeks 19 weeks
  # A tibble: 7 x 11
    time_value geo_value n_revisions min_lag max_lag  lag_near_latest spread
    <date>     <chr>           <dbl> <drtn>  <drtn>   <drtn>           <dbl>
  1 2020-01-01 ak                  6 2 weeks 19 weeks 19 weeks           101
  2 2020-01-08 ak                  1 4 weeks  5 weeks  4 weeks             9
  3 2020-01-15 ak                  0 3 weeks  3 weeks  3 weeks             0
  4 2020-01-01 al                  1 0 weeks 19 weeks 19 weeks            99
  5 2020-01-08 al                  0 0 weeks  0 weeks  0 weeks             0
  6 2020-01-15 al                  1 1 weeks  2 weeks  2 weeks             3
  7 2020-01-22 al                  1 0 weeks  1 weeks  1 weeks             0
    rel_spread min_value max_value median_value
         <dbl>     <dbl>     <dbl>        <dbl>
  1      0.990         1       102          5.5
  2      0.09         91       100         95.5
  3    NaN             0         0          0  
  4      0.99          1       100         50.5
  5      0             1         1          1  
  6      0.75          1         4          2.5
  7      0             9         9          9

Code
  dummy_ex_yearmonthly %>% revision_summary(drop_nas = FALSE) %>% print(n = 10,
    width = 300)
Message
  Min lag (time to first version):
Output
    min median mean max
      0      1  1.4   4
Message
  Fraction of all versions that are `NA`:
  * 2 out of 19 (10.53%)
  Fraction of epi_key+time_values with
  No revisions:
  * 2 out of 7 (28.57%)
  Quick revisions (last revision within 1 month of the `time_value`):
  * 2 out of 7 (28.57%)
  Few revisions (At most 3 revisions for that `time_value`):
  * 6 out of 7 (85.71%)
  Fraction of revised epi_key+time_values which have:
  Less than 0.1 spread in relative value:
  * 2 out of 5 (40%)
  Spread of more than 5.1 in actual value (when revised):
  * 3 out of 5 (60%)
  Months until within 20% of the latest value:
Output
    min median mean max
      0      3  6.9  19
  # A tibble: 7 x 11
    time_value geo_value n_revisions min_lag max_lag lag_near_latest spread
         <mth> <chr>           <dbl>   <dbl>   <dbl>           <dbl>  <dbl>
  1   2020 Jan ak                  6       2      19              19    101
  2   2020 Feb ak                  1       4       5               4      9
  3   2020 Mar ak                  0       3       3               3      0
  4   2020 Jan al                  1       0      19              19     99
  5   2020 Feb al                  0       0       0               0      0
  6   2020 Mar al                  1       1       2               2      3
  7   2020 Apr al                  1       0       1               1      0
    rel_spread min_value max_value median_value
         <dbl>     <dbl>     <dbl>        <dbl>
  1      0.990         1       102          5.5
  2      0.09         91       100         95.5
  3    NaN             0         0          0  
  4      0.99          1       100         50.5
  5      0             1         1          1  
  6      0.75          1         4          2.5
  7      0             9         9          9

Code
  dummy_ex_integerly %>% revision_summary(min_waiting_period = 60,
    quick_revision = 3, drop_nas = FALSE) %>% print(n = 10, width = 300)
Message
  Min lag (time to first version):
Output
    min median mean max
      0      1  1.4   4
Message
  Fraction of all versions that are `NA`:
  * 2 out of 19 (10.53%)
  Fraction of epi_key+time_values with
  No revisions:
  * 2 out of 7 (28.57%)
  Quick revisions (last revision within 3 time steps of the `time_value`):
  * 4 out of 7 (57.14%)
  Few revisions (At most 3 revisions for that `time_value`):
  * 6 out of 7 (85.71%)
  Fraction of revised epi_key+time_values which have:
  Less than 0.1 spread in relative value:
  * 2 out of 5 (40%)
  Spread of more than 5.1 in actual value (when revised):
  * 3 out of 5 (60%)
  Time Steps until within 20% of the latest value:
Output
    min median mean max
      0      3  6.9  19
  # A tibble: 7 x 11
    time_value geo_value n_revisions min_lag max_lag lag_near_latest spread
         <dbl> <chr>           <dbl>   <dbl>   <dbl>           <dbl>  <dbl>
  1          1 ak                  6       2      19              19    101
  2          2 ak                  1       4       5               4      9
  3          3 ak                  0       3       3               3      0
  4          1 al                  1       0      19              19     99
  5          2 al                  0       0       0               0      0
  6          3 al                  1       1       2               2      3
  7          4 al                  1       0       1               1      0
    rel_spread min_value max_value median_value
         <dbl>     <dbl>     <dbl>        <dbl>
  1      0.990         1       102          5.5
  2      0.09         91       100         95.5
  3    NaN             0         0          0  
  4      0.99          1       100         50.5
  5      0             1         1          1  
  6      0.75          1         4          2.5
  7      0             9         9          9

cmu-delphi/epiprocess documentation built on Feb. 22, 2025, 9:26 a.m.