This function create word clouds and topic figures
Usage
topicsPlot(
model = NULL,
ngrams = NULL,
test = NULL,
p_alpha = 0.05,
p_adjust_method = "none",
ngrams_max = 30,
ngram_select = "prevalence",
color_scheme = "default",
highlight_topic_words = NULL,
scale_size = FALSE,
plot_topics_idx = NULL,
allowed_word_overlap = NULL,
plot_n_most_prevalent_topics = NULL,
save_dir = NULL,
figure_format = "svg",
width = 6,
height = 5,
max_size = 10,
seed = 42,
scatter_legend_dot_size = 15,
scatter_legend_bg_dot_size = 9,
scatter_legend_n = c(1, 1, 1, 1, 0, 1, 1, 1, 1),
scatter_legend_method = c("mean"),
scatter_legend_specified_topics = NULL,
scatter_legend_topic_n = FALSE,
scatter_show_axis_values = TRUE,
grid_legend_title = "legend_title",
grid_legend_title_size = 5,
grid_legend_title_color = "black",
grid_legend_x_axes_label = "legend_x_axes_label",
grid_legend_y_axes_label = "legend_y_axes_label",
grid_legend_number_color = "black",
grid_legend_number_size = 5
)Arguments
- model
(list) A trained topics model, e.g., from topicsModel(). Should be NULL if plotting ngrams.
- ngrams
(list) The output from the the topicsGram() function. Should be NULL if plotting topics. Note 1: it is not possible to plot tags like <place>; so the < are replaced with underscore. Note 2: it is not possible to plot dash - alone, it is replaced with `_-_`.
- test
(list) The test results; if plotting according to dimension(s) include the object from topicsTest() function.
- p_alpha
(integer) The p-value threshold to use for significance testing.
- p_adjust_method
(character) Method to adjust/correct p-values for multiple comparisons (default = "none"; see also "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr").
- ngrams_max
(integer) The maximum number of n-grams to plot.
- ngram_select
(character) Method to select ngrams_max, when using both ngram and test use "prevalence" or "estimate"; if you only use ngrams use "pmi", "frequency", or "proportion".
- color_scheme
(string 'default' or vector) The color scheme.
For plots not including a test, the color_scheme should in clude 2 colours (1 gradient pair), such as:
c("lightgray", "darkblue)
For 1 dimensional plots of n-grams it should contain 4 colours (2 gradient pairs), such as:
c( "#EAEAEA", "darkred", # negative ngrams colors
"#EAEAEA", "darkgreen" # positve ngrams colors)
For 1-dimension plots of topics, it should contain 6 colours (3 gradient pairs), such as
c( "#EAEAEA", "darkred", # negative topics colors
"#EAEAEA", "darkgray", # colours of topics not significantly associated
"#EAEAEA", "darkgreen" # positve topics colors)
For 2-dimensional plots of topics, the color scheme should contain 18 colours (9 gradient pairs), such as:
c( "lightgray", "#398CF9", # quadrant 1 (upper left corner)
"lightgray", "#60A1F7", # quadrant 2
"lightgray", "#5dc688", # quadrant 3 (upper right corner)
"lightgray", "#e07f6a", # quadrant 4
"lightgray", "darkgray", # quadrant 5 (middle square)
"lightgray", "#40DD52", # quadrant 6
"lightgray", "#FF0000", # quadrant 7 (bottom left corner)
"lightgray", "#EA7467", # quadrant 8
"lightgray", "#85DB8E") # quadrant 9 (bottom right corner).
- highlight_topic_words
(named vector) Words to highlight in topics (e.g., negative words). The values of the vector determine the color: highlight_topic_words = c(not = "#2d00ff", never = "#2d00ff"); note that it needs to be hexa codes, so color naming such as "blue" does not work. The default value is NULL.
- scale_size
(logical) Whether to scale the size of the words.
- plot_topics_idx
(vector) The index or indices of the topics to plot (look in the model-object for the indices). They can, for example, be c(1, 3:5) to plot topic t_1, t_3, t_4 and t_5) (optional).
- allowed_word_overlap
(numeric) A filter function determining the maximum number of identical words in the topics to be plotted. This filter removes topics within each "color group" and also include removing topics from the distribution and grid legends; (Note that the adjustment for multiple comparison is taking place before these are removed; i.e., the adjusted p-values are not affected by this filter).
- plot_n_most_prevalent_topics
(numeric) Plots the n most prevalent topics in a given model.
- save_dir
(string) The directory to save the plots.
- figure_format
(string) Set the figure format, e.g., ".svg", or ".png".
- width
(integer) The width of the topic (units = "in").
- height
(integer) The width of the topic (units = "in").
- max_size
(integer) The maximum size of the words.
- seed
(integer) The seed to set for reproducibility.
- scatter_legend_dot_size
(integer) The size of dots in the scatter legend.
- scatter_legend_bg_dot_size
(integer) The size of background dots in the scatter legend.
- scatter_legend_n
(numeric or vector) A vector determining the number of dots to emphasize in each quadrant of the scatter legend. For example: c(1,1,1,1,0,1,1,1,1) result in one dot in each quadrant except for the middle quadrant.
- scatter_legend_method
(string) The method to filter topics to be emphasized in the scatter legend; either "mean", "max_x", or "max_y".
- scatter_legend_specified_topics
(vector) Specify which topic(s) to emphasize in the scatter legend. For example, c("t_1", "t_2"). If set, scatter_legend_method will have no effect.
- scatter_legend_topic_n
(boolean) If TRUE, the topic numbers are shown in the scatter legend.
- scatter_show_axis_values
(boolean) If TRUE, the estimate values are shown on the distribution plot axes.
- grid_legend_title
Title of the grid topic plot.
- grid_legend_title_size
Title size of the grid topic plot.
- grid_legend_title_color
Legend title color of the grid topic plot.
- grid_legend_x_axes_label
x-axis label of the grid topic plot.
- grid_legend_y_axes_label
y-axis label of the grid topic plot.
- grid_legend_number_color
Text color in the legend boxes of the grid topic plot.
- grid_legend_number_size
Text size in the legend boxes.
