Description Usage Arguments Examples
Plot hot and cold patches returned from get_patches
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | plot_patches(
df,
patches,
bg_poly = NULL,
bg_colour = "grey",
facet_cols = NULL,
facet_rows = NULL,
plot_distribution = TRUE,
print_plot = TRUE,
save_plot = FALSE,
return_plot = FALSE,
out_dir = NULL,
file_name = NULL,
file_ext = "png",
fig_width = 8,
fig_height = 9,
fig_units = "cm",
lab_size = 8,
text_size = 6,
outline_size = 0.7,
val_pal = c("black", "#050155", "#120172", "#3b008e", "#7200a9", "#8f00a0",
"#ba187f", "#d9365b", "#ed5930", "#f76323", "#fa8600", "#f6a704", "#fad61e",
"#fad61e"),
hatching = FALSE,
hatch_density = c(1, 2),
hatch_angle = c(45, 135),
hatch_size = 0.5,
fill_breaks = waiver(),
patch_cols = c("mistyrose", "cornflowerblue"),
patch_labs = c("Hot spots", "Cold spots"),
val_lab = NULL
)
|
df |
A dataframe returned from |
patches |
A SpatialPolygonsDataFrame returned from |
bg_poly |
An optional background polygon. Can be a SpatialPolygonsDataFrame
or fortified dataframe (see |
bg_colour |
Colour of the background polygon. |
facet_cols |
Number of facet columns. Defaults to NULL. |
facet_rows |
Number of facet rows. Defaults to NULL. |
plot_distribution |
Should a histogram be plotted? Defaults to TRUE. |
print_plot |
Should the resulting plots be printed? Defaults to FALSE. |
save_plot |
Should the resulting plots be saved? Defaults to TRUE. |
return_plot |
Should the resulting plots be returned? Defaults to FALSE. |
out_dir |
Path to directory where plots should be saved (if applicable). |
file_name |
Prefix for plot filenames (if applicable). If none specified, uses generic names 'distribution' and 'patches'. |
file_ext |
File extension. Defaults to '.png'. |
fig_width |
Figure width (if saved). Defaults to 8. |
fig_height |
Figure height (if saved). Defaults to 9. |
fig_units |
Figure dimension units (if saved). Defaults to "cm". |
lab_size |
Size of axis labels. Defaults to 8. |
text_size |
Size of axis text and legend text. Defaults to 6. |
outline_size |
Size of the outline. Defaults to 0.7. |
val_pal |
Colour palette to use for raster. Defaults to palette
derived from a FLIR jpeg: |
hatching |
Option to add hatching to patch polygons. Defaults to FALSE |
hatch_density |
Option to specify density of hatching (hot spot value
followed by cold spot value). Defaults to: |
hatch_angle |
Option to specify angle of hatching (hot spot value
followed by cold spot value). Defaults to: |
hatch_size |
Line thickness of hatching. Defaults to 0.5 |
fill_breaks |
Option to manually specify breaks in colourbar. Defaults
to |
patch_cols |
Colours for the patch borders (hot spot colour followed by
cold spot colour). Defaults to: |
patch_labs |
Labels to use in patch outline legend. Defaults to 'Hot spots' and 'Cold spots'. |
val_lab |
Label to describe the variable of interest - corresponds to the x axis of the histogram, and the fill legend of the raster plot. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | # FLIR temperature matrix ---------------------------------------------------
# Find hot and cold patches
flir_results <-
get_patches(img = flir11835$flir_matrix,
id = flir11835$photo_no)
# Look at the results for individual pixels
head(flir_results$df)
# Look at the patch statistics for hot and cold patches
flir_results$pstats
# Plot the patches
sp::plot(flir_results$patches)
# Plot using ThermStats::plot_patches with hatching
plot_patches(df = flir_results$df,
patches = flir_results$patches,
hatching = TRUE,
print_plot = TRUE,
save_plot = FALSE)
# Plot using ThermStats::plot_patches without hatching
plot_patches(df = flir_results$df,
patches = flir_results$patches,
hatching = FALSE,
print_plot = TRUE,
save_plot = FALSE)
## Not run:
# FLIR facets --------------------------------------------------------------
# Load raw data
raw_dat <- flir_raw$raw_dat
camera_params <- flir_raw$camera_params
metadata <- flir_metadata
# Batch convert
img_list <- batch_convert(raw_dat, write_results = FALSE)
# Get patches
patch_stats <-
stats_by_group(img_list = img_list,
metadata = metadata,
idvar = "photo_no",
style = "C",
grouping_var = "rep_id",
round_val = 0.5,
sum_stats = c("mean", "max", "min"))
# Plot
plot_patches(df = patch_stats$df,
patches = patch_stats$patches,
print_plot = TRUE,
save_plot = FALSE)
# Worldclim2 temperature raster ---------------------------------------------
# Dataset 'sulawesi_temp' represents mean January temperature for the
# island of Sulawesi
# Define projection and extent
img_proj <- raster::projection(sulawesi_temp)
img_extent <- raster::extent(sulawesi_temp)
# Find hot and cold patches
worldclim_results <-
get_patches(img = sulawesi_temp,
id = "sulawesi",
style = "C",
img_proj = img_proj,
img_extent = img_extent)
# Look at the results for individual pixels
head(worldclim_results$df)
# Look at the patch statistics for hot and cold patches
worldclim_results$pstats
# Plot the patches
sp::plot(worldclim_results$patches)
# Plot using ThermStats::plot_patches
plot_patches(df = worldclim_results$df,
patches = worldclim_results$patches,
bg_poly = sulawesi_bg,
bg_colour = "grey",
print_plot = TRUE,
save_plot = FALSE)
## End(Not run)
|
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