| group | R Documentation |
This function iterates over all unique values of the first metadata column (excluding 'QEUNIT' and 'ENA_UNIT') in the ENA set and adds each group as a set of points to the ENA plot. This is useful for quickly visualizing all groups in a categorical variable on the same plot.
group(x, wh = NULL)
x |
An 'ENAplot' object (as returned by 'plot.ena.set'). |
wh |
(Ignored) Included for compatibility with other plotting functions. |
The function finds the first metadata column in the ENA set (excluding 'QEUNIT' and 'ENA_UNIT'), and for each unique value in that column, calls ‘add_points()' to add the group’s points to the plot.
The modified 'ENAplot' object with all groups added as points.
# Load test data
data(RS.data);
# Define codenames for the test
codenames <- c("Data", "Technical.Constraints", "Performance.Parameters",
"Client.and.Consultant.Requests", "Design.Reasoning", "Collaboration");
# Standard ENA accumulation
accum <- rENA:::ena.accumulate.data.file(
RS.data, units.by = c("UserName", "Condition"),
conversations.by = c("ActivityNumber", "GroupName"),
codes = codenames
);
# Create a standard ENA set
newset <- ena.make.set(accum);
# Simple plot for a set of points, and their mean
newplot <- plot(newset) |>
add_points(Condition$FirstGame, mean = TRUE, colors = "blue") |>
add_network();
# Plot a single unit's point and it's line.weights
plot(newset) |>
add_points(UserName$`steven z`) |>
add_network();
# Trajectory accumulation and plotting
trajectory_accumulation <- rENA:::ena.accumulate.data.file(
RS.data, units.by = c("UserName", "Condition"),
conversations.by = c("ActivityNumber", "GroupName"),
codes = codenames,
model = "A"
);
trajectory_model <- ena.make.set(trajectory_accumulation);
newplot3 <- plot(trajectory_model) |>
add_trajectory(Condition$FirstGame);
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