sdata.frame. chemosensors 0.7.6

Description

Method sdata.frame converts a concetration matrix and (optionally) a sensor data matrix into a data frame.

Details

The input parameters are an object, e.g. SensorArray, a concentration matrix, and (optionally) a sensor data matrix. The output data frame has the following columns:

`S1`, `S2`, ...	Sensor signals.
`A`, `B`, ...	Gas concentrations (column names equal to gas names of the object).
`glab`	Gas labels, e.g. `A` or `Air`.
`lab`	Gas+Concetratoin labels, e.g. `A 0.01`.

Examples

set.seed(1)

### 1) a concentration matrix of three gases (tunit 4)
sa <- SensorArray(tunit = 4)

set <- c("A 0.1", "B 0.1", "C 1")
sc <- Scenario(set, tunit = 4)
conc <- getConc(sc)

head(conc)

    A B C
1 0.0 0 0
2 0.0 0 0
3 0.0 0 0
4 0.0 0 0
5 0.1 0 0
6 0.1 0 0


sdata <- predict(sa, conc)

p1 <- plotSignal(sa, conc = conc, sdata = sdata)
p1



# get a data.frame of features
df.transient <- sdata.frame(sa, conc = conc, sdata = sdata, feature = "transient")

df.ss <- sdata.frame(sa, conc = conc, sdata = sdata, feature = "steady-state")

df.step <- sdata.frame(sa, conc = conc, sdata = sdata, feature = "step")

# plot
p2 <- ggplot(df.transient, aes(x = 1:length(S1))) +
  geom_line(aes(y = S1, color = "S1")) +
  geom_line(aes(y = S2, color = "S2")) +
  labs(title = "feature: transient")
p2



df <- rbind(data.frame(df.ss, feature = "steady-state"),
  data.frame(df.step, feature = "step"))
  
p3 <- ggplot(df, aes(lab, S1, fill = feature)) + geom_bar(stat = "identity", position = "dodge")
p3