Analysis of cant estimates

workflowr

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Last updated: 2021-04-13

Checks: 7 0

Knit directory: emlr_obs_v_XXX/

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Rmd	beaec17	jens-daniel-mueller	2021-04-13	included model data
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Rmd	36eab46	jens-daniel-mueller	2021-04-07	included model data

---

1 Data sources

Cant estimates from this sensitivity case:

• Mean and SD per grid cell (lat, lon, depth)
• Zonal mean and SD (basin, lat, depth)
• Inventories (lat, lon)

cant_3d <-
  read_csv(paste(path_version_data,
                 "cant_3d.csv",
                 sep = ""))

cant_3d_mod_truth <-
  read_csv(paste(path_version_data,
                 "cant_3d_mod_truth.csv",
                 sep = ""))

cant_3d <- bind_rows(cant_3d,
                     cant_3d_mod_truth)

Cleaned GLODAPv2_2020 file as used in this sensitivity case

GLODAP <-
  read_csv(paste(
    path_version_data,
    "GLODAPv2.2020_MLR_fitting_ready.csv",
    sep = ""
  ))

cant_gamma_maps <- m_cant_slab_data_source(cant_3d)

cant_gamma_maps <- cant_gamma_maps %>% 
  arrange(gamma_slab, data_source)

2 Cant - positive

In a first series of plots we explore the distribution of Cant, taking only positive estimates into account (positive here refers to the mean cant estimate across MLR model predictions available for each grid cell). Negative values were set to zero before calculating mean sections and inventories.

Mean of positive cant within each horizontal grid cell (lon x lat) per isoneutral slab.

Please note that:

• density slabs covering values >28.1 occur by definition only either in the Atlantic or Indo-Pacific basin
• gaps in the maps represent areas where (thin) density layers fit between discrete depth levels used for mapping

cant_gamma_maps %>%
  group_split(gamma_slab, data_source) %>%
  map(
    ~ p_map_cant_slab(
    df = .x,
    subtitle_text = paste("data_source:", unique(.x$data_source),
                          "| Neutral density:", unique(.x$gamma_slab))
  ))

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9f31fe3	jens-daniel-mueller	2021-04-13
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i_gamma_slab <- unique(cant_3d$gamma_slab)[2]
i_data_source <- unique(cant_3d$data_source)[2]

map +
  geom_contour_filled(
    data = cant_gamma_maps %>%
      filter(data_source == i_data_source,
             gamma_slab == i_gamma_slab),
    aes(lon, lat, z = cant)
  ) +
  scale_fill_viridis_d()

3 Cant - all

In a second series of plots we explore the distribution of all Cant, taking positive and negative estimates into account.

Mean of all Cant within each horizontal grid cell (lon x lat) per isoneutral slab.

Please note that:

• density slabs covering values >28.1 occur by definition only either in the Atlantic or Indo-Pacific basin
• gaps in the maps represent areas where (thin) density layers fit between discrete depth levels used for mapping

cant_gamma_maps %>%
  group_split(gamma_slab, data_source) %>%
  map(
    ~ p_map_cant_slab(
    df = .x,
    var = "cant",
    col = "divergent",
    subtitle_text = paste("data_source:", unique(.x$data_source),
                          "| Neutral density:", unique(.x$gamma_slab))
  ))

[[1]]

Past versions of cant_all_gamma_slab_maps-1.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
488c4c1	jens-daniel-mueller	2021-04-07

[[2]]

Past versions of cant_all_gamma_slab_maps-2.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[3]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[4]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[5]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[6]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[7]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[8]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
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488c4c1	jens-daniel-mueller	2021-04-07

[[9]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
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488c4c1	jens-daniel-mueller	2021-04-07

[[10]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
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488c4c1	jens-daniel-mueller	2021-04-07

[[11]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
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488c4c1	jens-daniel-mueller	2021-04-07

[[12]]

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9f31fe3	jens-daniel-mueller	2021-04-13
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338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
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9f31fe3	jens-daniel-mueller	2021-04-13
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9f31fe3	jens-daniel-mueller	2021-04-13
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338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
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ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
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488c4c1	jens-daniel-mueller	2021-04-07

[[16]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[17]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
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488c4c1	jens-daniel-mueller	2021-04-07

[[18]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
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488c4c1	jens-daniel-mueller	2021-04-07

[[19]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
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488c4c1	jens-daniel-mueller	2021-04-07

[[20]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[21]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[22]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[23]]

Past versions of cant_all_gamma_slab_maps-23.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[24]]

Past versions of cant_all_gamma_slab_maps-24.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[25]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
e06bfa6	jens-daniel-mueller	2021-04-07
488c4c1	jens-daniel-mueller	2021-04-07

[[26]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
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488c4c1	jens-daniel-mueller	2021-04-07

[[27]]

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Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
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[[28]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
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488c4c1	jens-daniel-mueller	2021-04-07

[[29]]

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9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
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[[30]]

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[[31]]

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[[32]]

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[[34]]

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[[39]]

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[[40]]

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[[41]]

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9f31fe3	jens-daniel-mueller	2021-04-13
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[[42]]

Past versions of cant_all_gamma_slab_maps-42.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13

4 Slab inventories

cant_slab_inv <- m_cant_slab_inv_data_source(cant_3d)

cant_slab_inv %>% 
  ggplot(aes(data_source, cant_pos_total, fill = gamma_slab)) +
  geom_col() +
  scale_fill_viridis_d(direction = -1) +
  facet_wrap(~ basin_AIP)

Past versions of calc_slab_inventory-1.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13

cant_slab_inv %>% 
  ggplot(aes(data_source, cant_total, fill = gamma_slab)) +
  geom_col() +
  scale_fill_viridis_d(direction = -1) +
  facet_wrap(~ basin_AIP)

Past versions of calc_slab_inventory-2.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13

cant_slab_bias <- cant_slab_inv %>%
  filter(data_source %in% c("mod", "mod_truth")) %>%
  select(basin_AIP, data_source, gamma_slab, cant_pos_total) %>%
  pivot_wider(names_from = data_source,
              values_from = cant_pos_total) %>%
  mutate(cant_pos_bias = mod - mod_truth)

cant_slab_bias %>% 
  ggplot(aes(gamma_slab, cant_pos_bias, fill = basin_AIP)) +
  geom_col() +
  scale_fill_brewer(palette = "Dark2") +
  coord_flip()

Past versions of calc_slab_inventory-3.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13

cant_slab_bias <- cant_slab_inv %>%
  filter(data_source %in% c("mod", "mod_truth")) %>%
  select(basin_AIP, data_source, gamma_slab, cant_total) %>%
  pivot_wider(names_from = data_source,
              values_from = cant_total) %>%
  mutate(cant_bias = mod - mod_truth)

cant_slab_bias %>% 
  ggplot(aes(gamma_slab, cant_bias, fill = basin_AIP)) +
  geom_col() +
  scale_fill_brewer(palette = "Dark2") +
  coord_flip()

Past versions of calc_slab_inventory-4.png

Version	Author	Date
9f31fe3	jens-daniel-mueller	2021-04-13
ce38853	jens-daniel-mueller	2021-04-13

5 Slab boundary depth

# gamma field in Atl
predictors_gamma_Atl <- cant_3d %>%
  select(data_source, basin_AIP, lat, lon, depth, gamma) %>% 
  filter(basin_AIP == "Atlantic") %>% 
  distinct()

# filter grid cells with at least two depth layers
predictors_gamma_Atl <- predictors_gamma_Atl %>%
  group_by(data_source, lat, lon) %>%
  mutate(n = n()) %>%
  ungroup() %>% 
  filter(n > 1) %>% 
  select(-n)

# 3D grid with Atl slab boundaries
slabs_Atl <- expand_grid(predictors_gamma_Atl %>% distinct(data_source, lat, lon),
                         gamma = params_local$slabs_Atl) %>% 
  mutate(basin_AIP = "flag")

# join slab boundary grid with gamma field
slabs_Atl_int <- full_join(slabs_Atl,
                           predictors_gamma_Atl) %>%
  arrange(lat, lon, gamma)

# interpolate depth to slab boundary
slabs_Atl_int <- slabs_Atl_int %>% 
  group_by(data_source, lat, lon) %>% 
  mutate(depth = approxfun(gamma, depth, rule = 1)(gamma)) %>% 
  ungroup()

# filter interpolated depths
slabs_Atl_int <- slabs_Atl_int %>% 
  filter(basin_AIP == "flag",
         !is.na(depth))

#### Indo-Pacific

# gamma field in Pac
predictors_gamma_Ind_Pac <- cant_3d %>%
  select(data_source, basin_AIP, lat, lon, depth, gamma) %>% 
  filter(basin_AIP %in% c("Indian", "Pacific")) %>% 
  distinct()

# filter grid cells with at least two depth layers
predictors_gamma_Ind_Pac <- predictors_gamma_Ind_Pac %>%
  group_by(data_source, lat, lon) %>%
  mutate(n = n()) %>%
  ungroup() %>% 
  filter(n > 1) %>% 
  select(-n)

# 3D grid with Pac slab boundaries
slabs_Ind_Pac <- expand_grid(predictors_gamma_Ind_Pac %>% distinct(data_source, lat, lon),
                         gamma = params_local$slabs_Ind_Pac) %>% 
  mutate(basin_AIP = "flag")

# join slab boundary grid with gamma field
slabs_Ind_Pac_int <- full_join(slabs_Ind_Pac,
                           predictors_gamma_Ind_Pac) %>%
  arrange(lat, lon, gamma)

# interpolate depth to slab boundary
slabs_Ind_Pac_int <- slabs_Ind_Pac_int %>% 
  group_by(data_source, lat, lon) %>% 
  mutate(depth = approxfun(gamma, depth, rule = 1)(gamma)) %>% 
  ungroup()

# filter interpolated depths
slabs_Ind_Pac_int <- slabs_Ind_Pac_int %>% 
  filter(basin_AIP == "flag",
         !is.na(depth))


# join interpolated gamma depth
slabs <- bind_rows(slabs_Atl_int,
                   slabs_Ind_Pac_int) %>%
  select(-basin_AIP)

slabs <- inner_join(
  basinmask %>% select(lat, lon, basin_AIP) %>% distinct(),
  slabs)


map + 
  geom_raster(data = slabs,
              aes(lon, lat, fill = depth)) +
  facet_grid(gamma ~ data_source) +
  scale_fill_viridis_c(direction = -1)

Past versions of gamma_slab_boundary_depth-1.png

Version	Author	Date
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
488c4c1	jens-daniel-mueller	2021-04-07

rm(slabs_Atl, slabs_Atl_int, slabs_Ind_Pac, slabs_Ind_Pac_int)

# slabs_ex <- slabs %>% 
#   filter(lat == 0.5,
#          lon == 250.5)

slabs <- slabs %>% 
  group_by(data_source, lat, lon) %>% 
  arrange(depth) %>% 
  mutate(depth_lower_bound = depth,
         depth_upper_bound = lag(depth, default = 0),
         slab_thickness = depth_lower_bound - depth_upper_bound,
         gamma_in_slab = gamma - 0.01) %>% 
  ungroup()

slabs <- m_cut_gamma(slabs, "gamma_in_slab")

map + 
  geom_raster(data = slabs,
              aes(lon, lat, fill = slab_thickness)) +
  facet_grid(gamma_slab ~ data_source) +
  scale_fill_viridis_c(direction = -1)

Past versions of calculate_slab_thickness-1.png

Version	Author	Date
ce38853	jens-daniel-mueller	2021-04-13
338dd3c	jens-daniel-mueller	2021-04-09
a79ca2c	jens-daniel-mueller	2021-04-09
20b26d4	jens-daniel-mueller	2021-04-08
488c4c1	jens-daniel-mueller	2021-04-07

rm(slabs)

Session information

sessionInfo()

R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.2

Matrix products: default
BLAS:   /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] gt_0.2.2         kableExtra_1.3.1 marelac_2.1.10   shape_1.4.5     
 [5] scales_1.1.1     metR_0.9.0       scico_1.2.0      patchwork_1.1.1 
 [9] collapse_1.5.0   forcats_0.5.0    stringr_1.4.0    dplyr_1.0.5     
[13] purrr_0.3.4      readr_1.4.0      tidyr_1.1.2      tibble_3.0.4    
[17] ggplot2_3.3.3    tidyverse_1.3.0  workflowr_1.6.2 

loaded via a namespace (and not attached):
 [1] fs_1.5.0                 lubridate_1.7.9          gsw_1.0-5               
 [4] RColorBrewer_1.1-2       webshot_0.5.2            httr_1.4.2              
 [7] rprojroot_2.0.2          tools_4.0.3              backports_1.1.10        
[10] R6_2.5.0                 DBI_1.1.0                colorspace_1.4-1        
[13] withr_2.3.0              tidyselect_1.1.0         compiler_4.0.3          
[16] git2r_0.27.1             cli_2.1.0                rvest_0.3.6             
[19] xml2_1.3.2               labeling_0.4.2           checkmate_2.0.0         
[22] digest_0.6.27            rmarkdown_2.5            oce_1.2-0               
[25] pkgconfig_2.0.3          htmltools_0.5.0          dbplyr_1.4.4            
[28] rlang_0.4.10             readxl_1.3.1             rstudioapi_0.13         
[31] generics_0.0.2           farver_2.0.3             jsonlite_1.7.1          
[34] magrittr_1.5             Matrix_1.2-18            Rcpp_1.0.5              
[37] munsell_0.5.0            fansi_0.4.1              lifecycle_1.0.0         
[40] stringi_1.5.3            whisker_0.4              yaml_2.2.1              
[43] grid_4.0.3               blob_1.2.1               parallel_4.0.3          
[46] promises_1.1.1           crayon_1.3.4             lattice_0.20-41         
[49] haven_2.3.1              hms_0.5.3                seacarb_3.2.14          
[52] knitr_1.30               pillar_1.4.7             reprex_0.3.0            
[55] glue_1.4.2               evaluate_0.14            RcppArmadillo_0.10.1.2.0
[58] data.table_1.13.2        modelr_0.1.8             vctrs_0.3.5             
[61] httpuv_1.5.4             testthat_2.3.2           cellranger_1.1.0        
[64] gtable_0.3.0             assertthat_0.2.1         xfun_0.18               
[67] broom_0.7.5              RcppEigen_0.3.3.7.0      later_1.1.0.1           
[70] viridisLite_0.3.0        ellipsis_0.3.1           here_0.1