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minor bug fix
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@buddekai
buddekai committed Aug 25, 2022
1 parent ef96ef2 commit 9a33d30
Showing 1 changed file with 82 additions and 67 deletions.
149 changes: 82 additions & 67 deletions R/plotWaveforms.R
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
#' the function generator pulse (for GATE TTL))
#' @param voltage_limits_of_plot A number (value of min (negativ of the value)
#' and max values to be shown on y axis)
#' @param plot_waveforms A character (shows if all, none, or one waveform shall be plotted)
#' @param filter_stim_off A boolean (indicates whether measurements while
#' stim==off are to be filtered)
#' @param epsilon_for_filtering A number (min. distance for mean from 0 needed for filtering out the signal generator)
Expand All @@ -24,10 +25,12 @@
# Created: 2022/04/21
# Last changed: 2022/04/21

plotWaveforms <- function(input_data = NULL, output_dir = NULL,
plotWaveforms <- function(input_data = NULL,
output_dir = NULL,
show_time_in_us = FALSE,
channel_function_generator = "CHAN1",
channel_stimulation_pulse = "CHAN2",
plot_waveforms = "all",
voltage_limits_of_plot = NULL,
filter_stim_off = TRUE,
epsilon_for_filtering = 1,
Expand Down Expand Up @@ -127,77 +130,89 @@ plotWaveforms <- function(input_data = NULL, output_dir = NULL,
}

# Plot each waveform recording in a separate image #######################
if(plot_waveforms == "all"){
waveforms <- unique(input_data$ID)
}else if(plot_waveforms == "one"){
waveforms <- unique(input_data$ID)[
floor(length(unique(input_data$ID))/2)]
}else{
waveforms <- NA
}

for(i in unique(input_data$ID)){

input_data_filtered <- input_data %>%
dplyr::filter(ID == i)

# Get max and min (smoothed) of all stimulation pulses #################
lower_bound <- (max(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]) -
mean(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]))/2
upper_bound <- (min(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]) -
mean(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]))/2

max_value <- as.numeric(quantile(input_data_filtered$U[
input_data_filtered$Channel == channel_stimulation_pulse & input_data_filtered$U > lower_bound],
0.95, na.rm = TRUE))
min_value <- as.numeric(quantile(input_data_filtered$U[
input_data_filtered$Channel == channel_stimulation_pulse & input_data_filtered$U < upper_bound],
0.05, na.rm = TRUE))

p2p_value <- abs(max_value) + abs(min_value)
if(is.na(p2p_value)){
p2p_value <- 0
}
p2p_value <- format(round(p2p_value, digits = 2), nsmall = 2)
p2p_value <- paste("V_p2p=", p2p_value, "V", sep="")

# Calculate mean value of stimulation pulses ###########################

if(start_point_function_generator_pulse == end_point_function_generator_pulse){
df_dummy <- input_data_filtered %>%
dplyr::filter(Channel == channel_stimulation_pulse)

mean_value <- mean(df_dummy$U)
}else{
df_dummy <- input_data_filtered %>%
dplyr::filter(Channel == channel_stimulation_pulse) %>%
dplyr::filter(time >= start_point_function_generator_pulse &
time < end_point_function_generator_pulse)

mean_value <- mean(df_dummy$U)
if(!is.na(waveforms)){
for(i in waveforms){

input_data_filtered <- input_data %>%
dplyr::filter(ID == i)

# Get max and min (smoothed) of all stimulation pulses #################
lower_bound <- (max(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]) -
mean(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]))/2
upper_bound <- (min(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]) -
mean(input_data_filtered$U[input_data_filtered$Channel == channel_stimulation_pulse]))/2

max_value <- as.numeric(quantile(input_data_filtered$U[
input_data_filtered$Channel == channel_stimulation_pulse & input_data_filtered$U > lower_bound],
0.95, na.rm = TRUE))
min_value <- as.numeric(quantile(input_data_filtered$U[
input_data_filtered$Channel == channel_stimulation_pulse & input_data_filtered$U < upper_bound],
0.05, na.rm = TRUE))

p2p_value <- abs(max_value) + abs(min_value)
if(is.na(p2p_value)){
p2p_value <- 0
}
p2p_value <- format(round(p2p_value, digits = 2), nsmall = 2)
p2p_value <- paste("V_p2p=", p2p_value, "V", sep="")

# Calculate mean value of stimulation pulses ###########################

if(start_point_function_generator_pulse == end_point_function_generator_pulse){
df_dummy <- input_data_filtered %>%
dplyr::filter(Channel == channel_stimulation_pulse)

mean_value <- mean(df_dummy$U)
}else{
df_dummy <- input_data_filtered %>%
dplyr::filter(Channel == channel_stimulation_pulse) %>%
dplyr::filter(time >= start_point_function_generator_pulse &
time < end_point_function_generator_pulse)

mean_value <- mean(df_dummy$U)
}


# Plot complete data from YAML file ####################################
plot_annotation_x <- 0.05*max(input_data_filtered$time)
xaxis_lab <- ifelse(test = show_time_in_us,yes = "time/\U00B5s", no = "time/s")

plot_waveform <- ggplot2::ggplot(data = input_data_filtered,
aes(x = time, y = U, color=Channel)) +
geom_line() +
geom_hline(yintercept=max_value, linetype="dashed", color = "darkgray", size=1) +
geom_hline(yintercept=min_value, linetype="dashed", color = "darkgray", size=1) +
geom_hline(yintercept=mean_value, linetype="dotdash", color = "darkgray", size=1) +
annotate("text", x=plot_annotation_x, y=(voltage_limits_of_plot-2), label=p2p_value) +
coord_cartesian(ylim = c(-voltage_limits_of_plot, voltage_limits_of_plot)) +
labs(title=paste(plot_title, input_data_filtered$date_time[1], sep=" "),
x = xaxis_lab, y = "U/V") +
theme_bw() +
theme(axis.text.x = element_text(angle=90, vjust = 0.5),
plot.title = element_text(hjust = 0.5))

# Date and time as writable string
date_time_measurement <- input_data_filtered$date_time[1]
date_time_measurement <- gsub(pattern = " ", replacement = "_", x = date_time_measurement)
date_time_measurement <- gsub(pattern = ":", replacement = "", x = date_time_measurement)

# Save files
file_path <- file.path(output_dir, paste0(date_time_measurement, ".png"))
ggsave(plot = plot_waveform, filename = file_path, device = "png", width = 19.2, height = 10.8, units = "cm")
}

rm(i)

# Plot complete data from YAML file ####################################
plot_annotation_x <- 0.05*max(input_data_filtered$time)
xaxis_lab <- ifelse(test = show_time_in_us,yes = "time/\U00B5s", no = "time/s")

plot_waveform <- ggplot2::ggplot(data = input_data_filtered,
aes(x = time, y = U, color=Channel)) +
geom_line() +
geom_hline(yintercept=max_value, linetype="dashed", color = "darkgray", size=1) +
geom_hline(yintercept=min_value, linetype="dashed", color = "darkgray", size=1) +
geom_hline(yintercept=mean_value, linetype="dotdash", color = "darkgray", size=1) +
annotate("text", x=plot_annotation_x, y=(voltage_limits_of_plot-2), label=p2p_value) +
coord_cartesian(ylim = c(-voltage_limits_of_plot, voltage_limits_of_plot)) +
labs(title=paste(plot_title, input_data_filtered$date_time[1], sep=" "),
x = xaxis_lab, y = "U/V") +
theme_bw() +
theme(axis.text.x = element_text(angle=90, vjust = 0.5),
plot.title = element_text(hjust = 0.5))

# Date and time as writable string
date_time_measurement <- input_data_filtered$date_time[1]
date_time_measurement <- gsub(pattern = " ", replacement = "_", x = date_time_measurement)
date_time_measurement <- gsub(pattern = ":", replacement = "", x = date_time_measurement)

# Save files
file_path <- file.path(output_dir, paste0(date_time_measurement, ".png"))
ggsave(plot = plot_waveform, filename = file_path, device = "png", width = 19.2, height = 10.8, units = "cm")
}
rm(i)

# Plot all waveforms in one image ########################################

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