341 lines
14 KiB
Plaintext
341 lines
14 KiB
Plaintext
require(dplyr)
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require(ggplot2)
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require(reshape2)
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require(stringr)
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require(datetime)
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ggplotRegression <- function (fit) {
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ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
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geom_point() +
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stat_smooth(method = "lm", col = "black", linetype=3, se = F) +
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labs(subtitle = paste("R^2 =",signif(summary(fit)$adj.r.squared, 5),
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"\nIntercept =",signif(fit$coef[[1]],5 ),
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"\nSlope =",signif(fit$coef[[2]], 5)))+
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theme_classic()
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}
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calc_z_comp <- function(t, tref, len, coeff) {
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-1*(t-tref)*coeff*len*1000
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}
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datafiles <- list.files(pattern = ".csv")
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extract_meta_item <- function(item, meta) {
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line_string = meta[which(str_detect(meta,paste0("^# ",item)))]
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value = str_split(line_string, pattern = "=",simplify = T)[2]
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return(value)
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}
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for(file in datafiles) {
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lines = readLines(con = file(file))
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meta = lines[str_detect(lines, "#")]
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frame_z = as.numeric(extract_meta_item("frame_z_length",meta))/1000
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user = extract_meta_item("id",meta)
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dataset_id = extract_meta_item("timestamp",meta)
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printer_id = extract_meta_item("printer",meta)
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measure_meth = extract_meta_item("measure_type",meta)
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step_dist = as.numeric(extract_meta_item("step_dist", meta))
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hot_dur = as.numeric(extract_meta_item("hot_duration",meta))*60
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cool_dur = as.numeric(extract_meta_item("cool_duration",meta))*60
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frame_coeff = as.numeric(extract_meta_item("coeff", meta))*1E-6
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root = paste0(user,"/",dataset_id)
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dir.create(root,recursive = TRUE)
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data_raw = read.csv(file, comment.char = "#")
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standard_columns = c(
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"sample",
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"time",
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"mcu_pos_z",
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"frame_t",
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"bed_t",
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"bed_target",
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"he_t",
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"he_target"
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)
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extra_columns <- colnames(data_raw)[!colnames(data_raw) %in% standard_columns]
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bed_off_idx <- which.max(data_raw$bed_target == 0)
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data <- data_raw[c(standard_columns, extra_columns)] %>%
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mutate("delta_z" = (mcu_pos_z - mcu_pos_z[1])*step_dist,
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"time" = as.POSIXct(time, format="%Y/%m/%d-%H:%M:%S"),
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"elapsed_time" = as.numeric(difftime(time,min(time),units = 'min',))
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) %>%
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filter(delta_z < 2) %>%
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select(-ends_with("target"))
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data_mean_wide <- data %>%
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select(-time) %>%
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group_by(sample) %>%
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summarise_all(.funs=list(mean))
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data_mean <- data_mean_wide %>%
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melt(id.vars = "elapsed_time") %>%
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mutate(variable=factor(variable,labels = c(
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"Sample",
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"MCU Position",
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"Frame",
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"Bed",
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"Hotend",
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extra_columns,
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"Delta Endstop"
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))) %>%
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rename(mean=value)
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data_sd_wide = data %>%
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select(-time) %>%
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group_by(sample) %>%
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summarise_all(.funs=list(sd))
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data_sd <- data_sd_wide %>%
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melt(id.vars = "elapsed_time") %>%
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mutate(variable=factor(variable,labels = c(
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"Sample",
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"MCU Position",
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"Frame",
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"Bed",
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"Hotend",
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extra_columns,
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"Delta Endstop"
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)),
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elapsed_time = data_mean$elapsed_time) %>%
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rename(sd=value)
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data_all <- left_join(data_mean,data_sd, by = c("elapsed_time", "variable"))
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##############################
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# Overview plot
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data_all_overview <- data_all
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data_all_overview[data_all$variable == "Delta Endstop", "mean"] = data_all[data_all$variable=="Delta Endstop","mean"]*500
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data_all_overview[data_all$variable == "Delta Endstop", "sd"] = data_all[data_all$variable=="Delta Endstop","sd"]*500
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ggplot(data=filter(data_all_overview, !variable %in% c("Sample", "MCU Position")),
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aes(elapsed_time, mean, colour=variable)) +
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geom_hline(yintercept = 0, linetype=2) +
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geom_line() +
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geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd), color="black", width=0) +
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scale_y_continuous(sec.axis = sec_axis(~./500,name = expression(Delta*"Endstop Position [mm]"),
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breaks = seq(-5,5,0.02)),
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breaks=seq(-400,400,10), labels = c(rep("",40),seq(0,400,10))) +
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scale_x_continuous(breaks = seq(0,1000,15))+
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scale_colour_brewer(type = "qual", palette = 6,direction = -1) +
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labs(x = expression("Elapsed Time [min]"),
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y = expression("Temperature ["*degree*"C]", colour="")) +
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# title = "Frame Expansion Measurement", subtitle = file) +
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theme_classic() +
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theme(panel.grid.major = element_line(colour = gray(0.9)),
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legend.position = "bottom",#c(0.8, 0.3),
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legend.background = element_rect(colour = "black"),
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legend.title = element_blank(),
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# aspect.ratio = 1,
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5))
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ggsave(paste0(root,"/overview.png"),device = "png", width = 9, height = 5,
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units = "in", dpi=300)
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##############################
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# Overview plot, facetted
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ggplot(data=filter(data_all, !variable %in% c("Sample", "Hotend","Bed", "MCU Position")),
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aes(elapsed_time, mean, colour=variable)) +
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# geom_hline(yintercept = 0, linetype=2) +
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geom_line() +
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geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd), color="black", width=0) +
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# scale_y_continuous(sec.axis = sec_axis(~./500,name = expression(Delta*"Endstop Position [mm]"),
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# breaks = seq(-5,5,0.025)),
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# breaks=seq(-200,400,10), labels = c(rep("",20),seq(0,400,10))) +
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# scale_x_continuous(breaks = seq(0,1000,30))+
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scale_colour_brewer(type = "qual", palette = 6,direction = -1) +
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labs(x = expression("Elapsed Time [min]"),
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y = expression("Temperature ["*degree*"C]", colour=""),
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title = "Frame Expansion Measurement", subtitle = file) +
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theme_classic() +
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theme(panel.grid.major = element_line(colour = gray(0.9)),
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legend.position = "None",
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legend.background = element_rect(colour = "black"),
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legend.title = element_blank(),
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aspect.ratio = 1,
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5)) +
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facet_wrap(~variable, nrow = 1, scales = "free")
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ggsave(paste0(root,"/overview_facetted.png"),device = "png", width = 8, height = 5,
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units = "in", dpi=300)
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##############################
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# Adjust delta Z for fitting
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data_filtered <- data %>%
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filter(20 < elapsed_time,
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elapsed_time < hot_dur-5)
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# filter(frame_t < max(frame_t)-0.3)
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fit_t_vs_z_poly = lm(frame_t~poly(data_filtered$delta_z,3), data_filtered[c("frame_t", "delta_z")])
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fit_t_vs_z_lin = lm(frame_t~poly(data_filtered$delta_z,1), data_filtered[c("frame_t", "delta_z")])
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data_fitted <- data_filtered %>%
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mutate(t_fit_lin = fitted(fit_t_vs_z_lin),
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t_fit_poly = fitted(fit_t_vs_z_poly),
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t_fit_poly_resid = residuals(fit_t_vs_z_poly)
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# t_fit_logis = fitted(fit_t_vs_z_logis)
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)
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#png(paste0(root,"/residuals.png"))
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#plot(fitted(fit_t_vs_z_poly), residuals(fit_t_vs_z_poly),
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# xlab = "Frame Temp",
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# ylab = "Residual",
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# main = "Polynomial (3) Fit")
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#abline(h=0,lty="dashed")
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#dev.off()
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ggplot(data = data_fitted,
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aes(x=delta_z, y=frame_t,fill=frame_t)) +
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geom_line(aes(y=t_fit_poly, color='Fit(Poly)'), linetype=1, size=rel(1)) +
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geom_line(aes(y=t_fit_lin, color='Fit(Linear)'), linetype=2, size=rel(1)) +
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# geom_line(aes(y=t_fit_logis, color='Fit(Logis)'), linetype=3, size=rel(1.5)) +
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geom_point(aes(color='Measured'),shape=21) +
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labs(x=expression(Delta*" Endstop Position [mm]"),
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y=expression("Frame Temperature "*"["*degree*C*"]"),
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colour="Data Type",
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fill="Frame Temperature",
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title = "Expansion Fitting", subtitle = file)+
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scale_colour_brewer(type = "qual", palette = 6,direction = 1) +
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scale_fill_gradient2(low="red", mid = "yellow",
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midpoint = min(data_fitted$frame_t) + (max(data_fitted$frame_t)-min(data_fitted$frame_t))/2,
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high="blue") +
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theme_classic() +
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theme(panel.grid.major = element_line(colour = gray(0.9)),
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legend.position = c(0.8, 0.8),
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legend.background = element_rect(colour = "black"),
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# legend.title = element_blank(),
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aspect.ratio = 1,
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5))
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#ggsave(paste0(root,"/curve_fitting.png"),device = "png", width = 6, height = 6,
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# units = "in", dpi=300)
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##############################################################################
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# plot(data_filtered$frame_t, data_filtered$delta_z,xlab = "Frame Temperature [degC]",ylab = "Endstop Drift [mm]")
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# lines(fitted(fit_t_vs_z_poly), data_filtered$delta_z, col="blue", lw=3)
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# lines(fitted(fit_t_vs_z_lin), data_filtered$delta_z, col="Red", lw=1,lty=2)
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# legend("topright",c("Poly(3)", "Linear"), col=c("blue","red"), lty=c(1,2), inset = c(0.1,0.1))
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theoretical <- data.frame(frame_t = data_filtered$frame_t) %>%
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mutate(comp_z = calc_z_comp(frame_t, frame_t[1], frame_z, frame_coeff),
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delta_z = data_filtered$delta_z,
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deviation = comp_z-delta_z,
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elapsed_time = data_filtered$elapsed_time)
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ggplot(theoretical, aes(x=frame_t, y=deviation, colour=elapsed_time)) +
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geom_point() +
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geom_hline(yintercept = 0, linetype=2) +
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scale_color_gradient2(low="red", mid = "yellow",
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midpoint = max(theoretical$elapsed_time/2),
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high="blue") +
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labs(x=expression("Frame Temperature "*"["*degree*C*"]"),
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y="Compensation Error (Theoretical-Measured) [mm]",
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color="Elapsed Time [min]") +
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theme_classic() +
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theme(panel.grid.major = element_line(colour=grey(0.5,0.2)),
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legend.position = "bottom",)
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#ggsave(paste0(root,"/comp_error.png"),device = "png", width = 6, height = 5,
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# units = "in", dpi=300)
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##############################################################################
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fit = lm(theoretical$delta_z~theoretical$comp_z)
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fit_poly = lm(theoretical$delta_z~poly(theoretical$comp_z,3))
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ggplotRegression(fit) +
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geom_point(data=theoretical, aes(x=comp_z, y=delta_z, colour=frame_t)) +
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# scale_color_gradient(low = "black", high = "red",guide = "colourbar") +
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scale_color_gradient2(low="blue", mid = "yellow",
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midpoint = min(theoretical$frame_t) + (max(theoretical$frame_t)-min(theoretical$frame_t))/2,
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high="red") +
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geom_abline(slope=1, intercept = 0, linetype=2, colour=gray(0.5)) +
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# geom_point(aes(x=fitted(fit_poly)))+
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# coord_equal() +
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# scale_x_continuous(breaks=seq(-2,2,0.02))+
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# scale_y_continuous(breaks=seq(-2,2,0.02))+
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labs(x="Z Frame Comp Correction [mm]\ngantry_factor=1; 6005A-T5 Alu Alloy",
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y="Measured Endstop Drift [mm]",
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color = expression("Frame Temperature "*"["*degree*C*"]"),
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title = "Measured v. Theoretical") +
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theme(panel.grid.major = element_line(colour=grey(0.5,0.2)),
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legend.position = "bottom",
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plot.title = element_text(hjust = 0),)
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ggsave(paste0(root,"/measured_v_comp.png"),device = "png",
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width = 6,
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height = 6,
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units = "in",
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dpi=300)
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##############################################################################
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# overview with theoretical corrected Z height
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home_time <- 30
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idx_home_ref <- which.max(data_mean_wide$elapsed_time > home_time)
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data_all_wide <- left_join(data_mean_wide, data_sd_wide, by="sample",suffix = c("_mean", "_sd")) %>%
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mutate(
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delta_z_mean_homed = delta_z_mean-delta_z_mean[idx_home_ref],
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z_corr_theoretical = delta_z_mean_homed - calc_z_comp(frame_t_mean,
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frame_t_mean[idx_home_ref],
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frame_z,
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frame_coeff),
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z_corr_meas_adjust = delta_z_mean_homed - calc_z_comp(frame_t_mean,
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frame_t_mean[idx_home_ref],
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frame_z,
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frame_coeff)*fit$coefficients[2]
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) %>%
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filter(elapsed_time_mean < hot_dur)
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ggplot(data=filter(data_all_wide, elapsed_time_mean >= home_time-10),
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aes(elapsed_time_mean, alpha=(elapsed_time_mean >= home_time))) +
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geom_hline(yintercept = 0, linetype=2) +
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geom_line(aes(y=z_corr_meas_adjust, color=paste0("Fit-Adjusted Compensation\ngantry_factor=", round(fit$coefficients[2],2)))) +
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geom_line(aes(y=z_corr_theoretical, color="Frame Expansion\nCompensation")) +
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geom_line(aes(y=delta_z_mean_homed, color="Uncorrected")) +
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geom_vline(xintercept = home_time, linetype=2) +
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geom_errorbar(aes(ymin=z_corr_meas_adjust-delta_z_sd,
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ymax=z_corr_meas_adjust+delta_z_sd),
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color="black", width=0) +
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geom_errorbar(aes(ymin=delta_z_mean_homed-delta_z_sd,
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ymax=delta_z_mean_homed+delta_z_sd),
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color="black", width=0) +
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geom_errorbar(aes(ymin=z_corr_theoretical-delta_z_sd,
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ymax=z_corr_theoretical+delta_z_sd),
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color="black", width=0) +
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geom_label(aes(x=home_time, y=0.05, label="<-Print Start"),
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hjust=0, nudge_x = 5,) +
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scale_y_continuous(breaks=seq(-5,5,0.01)) +
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scale_x_continuous(limits = c(home_time-10,
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max(data_all_wide$elapsed_time_mean)),
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breaks = seq(0,1000,15))+
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scale_colour_brewer(type = "qual", palette = 6,direction = -1) +
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scale_alpha_discrete(guide=FALSE) +
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labs(x = expression("Elapsed Time [min]"),
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y = expression(Delta*"Endstop Position [mm]", colour=""),
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title = "Theoretical Correction",
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subtitle = paste0(user,"(",dataset_id,")",'\n',printer_id,"(",measure_meth,")")) +
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# title = "Frame Expansion Measurement", subtitle = file) +
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theme_classic() +
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theme(panel.grid.major = element_line(colour = gray(0.9)),
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legend.position = "bottom",
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legend.background = element_rect(colour = "black"),
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legend.title = element_blank(),
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aspect.ratio = 1,
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5))
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ggsave(paste0(root,"/z_corrected_timeseries.png"),device = "png", width = 6, height = 5,
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units = "in", dpi=300)
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}
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