Open VincentYang147 opened 1 year ago
Use the data in Model1 ~ 8 instead of the default data in results
Do you mean the data in excle? Such as using Model1_dataDictionary to replace the dataDictionary
Use the data in Model1 ~ 8 instead of the default data in results
Do you mean the data in excle? Such as using Model1_dataDictionary to replace the dataDictionary
Use the data in Model1 ~ 8 instead of the default data in results
yes,include the control file
Do you mean the data in excle? Such as using Model1_dataDictionary to replace the dataDictionary
Use the data in Model1 ~ 8 instead of the default data in results
yes,include the control file Thank you very much! It worked!
Do you mean the data in excle? Such as using Model1_dataDictionary to replace the dataDictionary
Use the data in Model1 ~ 8 instead of the default data in results
yes,include the control file Thank you very much! It worked!
hello, please tell me more details about how to use Model1_dataDictionary to replace the dataDictionary, thank you very much!!!
Just copy and pasete all the file in Model1 file.
Just copy and pasete all the file in Model1 file.
ok, thank you so much! I have successfully solved this problem and ran the model.
Do you mean the data in excle? Such as using Model1_dataDictionary to replace the dataDictionary
Use the data in Model1 ~ 8 instead of the default data in results
yes,include the control file
When I use my own data, I recieved this: Error in calcDemtareaClass(sitedata$demtarea) (from calcDemtareaClass.R#30) : object 'demtarea.class' not found
Traceback: 11: calcDemtareaClass(sitedata$demtarea) 10: startModelRun(file.output.list, if_estimate, if_estimate_simulation, if_boot_estimate, if_boot_predict, enable_ShinyApp, filter_data1_conditions, data1, if_userModifyData, data_names, class.input.list, min.sites.list, if_validate, iseed, pvalidate, mapping.input.list, estimate.input.list, if_predict, biters, scenario.input.list, compare_models, modelComparison_name, if_spatialAutoCorr, add_vars, batch_mode, RSPARROW_errorOption) 9: executeRSPARROW(settingValues = lapply(settingsEnv, get), settingNames = settingsEnv, activeFile, envir = .GlobalEnv) 8: eval(ei, envir) 7: eval(ei, envir) 6: withVisible(eval(ei, envir)) 5: source(paste(path_master, "/R/runRsparrow.R", sep = "")) 4: eval(ei, envir) 3: eval(ei, envir) 2: withVisible(eval(ei, envir)) 1: source("E:/SPARROWyax/rsparrow-master/UserTutorial/results/sparrow_control.R")
RSPARROW SYSTEM ERROR OCCURRED To reset user options in R use options(backupOptions)
Can you give me some advice ,thanks!
does your data.csv file has demtarea column?
does your data.csv file has demtarea column?
Yes!And each subwatershed has a corresponding value. QAQ
Traceback: 23: complete.cases(x.neg, x.pos, y.neg, y.pos) 22: eval(substitute(expr), data, enclos = parent.frame()) 21: eval(substitute(expr), data, enclos = parent.frame()) 20: with.default(out, { good <- complete.cases(x.neg, x.pos, y.neg, y.pos) envelope(x.neg[good], x.pos[good], y.neg[good], y.pos[good], col = col.spread, alpha = alpha, border = border) }) 19: with(out, { good <- complete.cases(x.neg, x.pos, y.neg, y.pos) envelope(x.neg[good], x.pos[good], y.neg[good], y.pos[good], col = col.spread, alpha = alpha, border = border) }) 18: smoother(x[subs], y[subs], col = smoother.args$col[i], log.x = FALSE, log.y = FALSE, spread = spread, smoother.args = smoother.args) 17: lower.panel(...) 16: localLowerPanel(as.vector(x[, j]), as.vector(x[, i]), ...) 15: pairs.default(x, labels = var.labels, cex.axis = cex.axis, cex.main = cex.main, cex.labels = cex.labels, cex = cex, diag.panel = diag, row1attop = row1attop, panel = function(x, y, ...) { for (i in 1:n.groups) { subs <- groups == levels(groups)[i] if (plot.points) points(x[subs], y[subs], pch = pch[i], col = col[if (n.groups == 1) 1 else i], cex = cex) if (by.groups) { if (is.function(smoother)) smoother(x[subs], y[subs], col = smoother.args$col[i], log.x = FALSE, log.y = FALSE, spread = spread, smoother.args = smoother.args) if (is.function(reg.line)) regLine(reg.line(y[subs] ~ x[subs]), lty = lty, lwd = lwd, col = regLine.args$col[i]) if (ellipse) dataEllipse(x[subs], y[subs], plot.points = FALSE, ... 14: pairs(x, labels = var.labels, cex.axis = cex.axis, cex.main = cex.main, cex.labels = cex.labels, cex = cex, diag.panel = diag, row1attop = row1attop, panel = function(x, y, ...) { for (i in 1:n.groups) { subs <- groups == levels(groups)[i] if (plot.points) points(x[subs], y[subs], pch = pch[i], col = col[if (n.groups == 1) 1 else i], cex = cex) if (by.groups) { if (is.function(smoother)) smoother(x[subs], y[subs], col = smoother.args$col[i], log.x = FALSE, log.y = FALSE, spread = spread, smoother.args = smoother.args) if (is.function(reg.line)) regLine(reg.line(y[subs] ~ x[subs]), lty = lty, lwd = lwd, col = regLine.args$col[i]) if (ellipse) dataEllipse(x[subs], y[subs], plot.points = FALSE, ... 13: scatterplotMatrix.default(sdf, diagonal = "boxplot", reg.line = FALSE, use = "pairwise.complete.obs", spread = FALSE, smooth = TRUE) 12: scatterplotMatrix(sdf, diagonal = "boxplot", reg.line = FALSE, use = "pairwise.complete.obs", spread = FALSE, smooth = TRUE) 11: correlationMatrix(file.output.list, SelParmValues, subdata) 10: startModelRun(file.output.list, if_estimate, if_estimate_simulation, if_boot_estimate, if_boot_predict, enable_ShinyApp, filter_data1_conditions, data1, if_userModifyData, data_names, class.input.list, min.sites.list, if_validate, iseed, pvalidate, mapping.input.list, estimate.input.list, if_predict, biters, scenario.input.list, compare_models, modelComparison_name, if_spatialAutoCorr, add_vars, batch_mode, RSPARROW_errorOption) 9: executeRSPARROW(settingValues = lapply(settingsEnv, get), settingNames = settingsEnv, activeFile, envir = .GlobalEnv) 8: eval(ei, envir) 7: eval(ei, envir) 6: withVisible(eval(ei, envir)) 5: source(paste(path_master, "/R/runRsparrow.R", sep = "")) 4: eval(ei, envir) 3: eval(ei, envir) 2: withVisible(eval(ei, envir)) 1: source("E:/Coding/R/RSPARROW_UserTutorial/results/sparrow_control.R")