better website

README.Rmd

@@ -35,7 +35,7 @@ requireNamespace("bench", quietly = TRUE)
 
 The `tidyhydro` package provides a set of commonly used metrics in hydrology (such as _NSE_, _KGE_, _pBIAS_) for use within a [`tidymodels`](https://www.tidymodels.org/) infrastructure. Originally inspired by the [`yardstick`](https://github.com/tidymodels/yardstick/tree/main) and [`hydroGOF`](https://github.com/hzambran/hydroGOF) packages, this library is mainly written in C++ and provides a very quick estimation of desired goodness-of-fit criteria.
 
-Additionally, you'll find here a C++ implementation of lesser-known yet powerful metrics and descriptive statistics recommended in the United States Geological Survey (USGS) and the National Environmental Monitoring Standards (NEMS) guidelines. Examples include _PRESS_ (Prediction Error Sum of Squares), _SFE_ (Standard Factorial Error), _MSPE_ (Model Standard Percentage Error) and others. Based on the equations from _Helsel et al._ ([2020](https://pubs.usgs.gov/publication/tm4A3)), _Rasmunsen et al._ ([2008](https://pubs.usgs.gov/tm/tm3c4/)), _Hicks et al._ ([2020](https://www.nems.org.nz/documents/suspended-sediment)) and etc. (see documentation for details).
+Additionally, you'll find here a C++ implementation of lesser-known yet powerful metrics and descriptive statistics recommended in the United States Geological Survey (USGS) and the New Zealand National Environmental Monitoring Standards (NEMS) guidelines. Examples include _PRESS_ (Prediction Error Sum of Squares), _SFE_ (Standard Factorial Error), _MSPE_ (Model Standard Percentage Error) and others. Based on the equations from _Helsel et al._ ([2020](https://pubs.usgs.gov/publication/tm4A3)), _Rasmunsen et al._ ([2008](https://pubs.usgs.gov/tm/tm3c4/)), _Hicks et al._ ([2020](https://www.nems.org.nz/documents/suspended-sediment)) and etc. (see documentation for details).
 
 ## Performance metrics
 The `tidyhydro` package follows the philosophy of [`yardstick`](https://github.com/tidymodels/yardstick/tree/main) and provides S3 class methods for vectors and data frames. For example, one can estimate `KGE`, `NSE` or `pBIAS` for a data frame like this:

README.md

@@ -30,11 +30,11 @@ desired goodness-of-fit criteria.
 
 Additionally, you’ll find here a C++ implementation of lesser-known yet
 powerful metrics and descriptive statistics recommended in the United
-States Geological Survey (USGS) and the National Environmental
-Monitoring Standards (NEMS) guidelines. Examples include *PRESS*
-(Prediction Error Sum of Squares), *SFE* (Standard Factorial Error),
-*MSPE* (Model Standard Percentage Error) and others. Based on the
-equations from *Helsel et al.*
+States Geological Survey (USGS) and the New Zealand National
+Environmental Monitoring Standards (NEMS) guidelines. Examples include
+*PRESS* (Prediction Error Sum of Squares), *SFE* (Standard Factorial
+Error), *MSPE* (Model Standard Percentage Error) and others. Based on
+the equations from *Helsel et al.*
 ([2020](https://pubs.usgs.gov/publication/tm4A3)), *Rasmunsen et al.*
 ([2008](https://pubs.usgs.gov/tm/tm3c4/)), *Hicks et al.*
 ([2020](https://www.nems.org.nz/documents/suspended-sediment)) and etc.
@@ -153,9 +153,9 @@ bench::mark(
 #> # A tibble: 3 × 6
 #>   expression   min median `itr/sec` mem_alloc `gc/sec`
 #>   <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>
-#> 1 tidyhydro   1      1        13.3        NaN      NaN
-#> 2 hydroGOF    9.69   8.63      1          Inf      Inf
-#> 3 baseR       5.80   5.54      2.27       Inf      Inf
+#> 1 tidyhydro   1      1        16.5        NaN      NaN
+#> 2 hydroGOF    9.74  11.5       1          Inf      Inf
+#> 3 baseR       6.40   7.92      2.09       Inf      Inf
 ```
 
 ## Code of Conduct

paper/src/.gitignore

@@ -0,0 +1 @@
+/.quarto/

vignettes/articles/available_metrics.qmd

@@ -0,0 +1,26 @@
+---
+title: "Available metrics"
+format:
+  html:
+    toc: false
+knitr:
+  opts_chunk:
+    collapse: true
+    comment: '#>'
+    message: false
+---
+
+# Goodness-of-fit criteria
+
+| Name | Abbr. | Function calls | Reference |
+|----------------|--------|--------|-------------|
+| Kling-Gupta Efficiency | $KGE$ | `kge` | <span style="font-size: 0.8em;">Gupta, H.V.; Kling, H.; Yilmaz, K.K.; Martinez, G.F. (2009). *Journal of Hydrology*, 377(1–2), 80–91.</span> |
+| Modified Kling-Gupta Efficiency | $KGE'$ | `kge2012` | <span style="font-size: 0.8em;">Kling, H., Fuchs, M., & Paulin, M. (2012). *Journal of Hydrology*, 424–425, 264–277.</span> |
+| Log-transformed Kling-Gupta Efficiency | $KGE_{log}$ | `kgelog`, `kgelog_low`, `kgelog_hi` | <span style="font-size: 0.8em;">Kling, J. (2023). *Journal of Hydrology*, 620, 129414.</span> |
+| Nash-Sutcliffe Efficiency | $NSE$ | `nse` | <span style="font-size: 0.8em;">Nash, J. E., & Sutcliffe, J. V. (1970). *Journal of Hydrology*, 10(3), 282–290.</span> |
+| Mean Squared Error | $MSE$ | `mse` | <span style="font-size: 0.8em;">Clark, M. P., Vogel, R. M., Lamontagne, J. R., Mizukami, N., Knoben, W. J. M., Tang, G., Gharari, S., Freer, J. E., Whitfield, P. H., Shook, K. R., & Papalexiou, S. M. (2021). The Abuse of Popular Performance Metrics in Hydrologic Modeling. Water Resources Research, 57(9), e2020WR029001.</span> |
+| Percent BIAS | $pBIAS$ | `pbias` | <span style="font-size: 0.8em;">Gupta, H. V., S. Sorooshian, and P. O. Yapo. (1999). Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration. J. Hydrologic Eng. 4(2): 135-143 </span> |
+| PRediction Error Sum of Squares | $PRESS$ | `press` | <span style="font-size: 0.8em;"> Rasmussen, P. P., Gray, J. R., Glysson, G. D. & Ziegler, A. C. Guidelines and procedures for computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data. in U.S. Geological Survey Techniques and Methods book 3, chap. C4 53 (2009)</span> |
+| Standard Factorial Error | $SFE$ | `sfe` | <span style="font-size: 0.8em;"> Herschy, R.W. 1978: Accuracy. Chapter 10 In: Herschy, R.W. (ed.) Hydrometry - principles and practices. John Wiley and Sons, Chichester, 511 p.</span> |
+
+: Metrics currently implemented in `tidyhydro` v`r packageVersion("tidyhydro")`

vignettes/articles/benchmarks.qmd

@@ -9,6 +9,8 @@ knitr:
 
 Since `tidyhydro` uses C++ under the hood, it performs slightly faster than similar R packages (like `hydroGOF`). The results are particularly noticeable in large datasets with $N$ observations exceeding 1000.
 
+Below are benchmarking results ran during CI process. See machine specs [below](#machine-specs).
+
 ```{r}
 #| label: setup
 library(tidyhydro)
@@ -79,4 +81,11 @@ bench::mark(
   filter_gc = FALSE
 )
 
+```
+
+# Machine specs
+
+```{r}
+system("lscpu | grep -v '^Flags'")
+system("lsmem")
 ```

vignettes/articles/tidyhydro.qmd

@@ -21,25 +21,7 @@ theme_set(
 )
 ```
 
-# Available metrics
-
-In `tidyhydro` v`r packageVersion("tidyhydro")`, `r length(getNamespaceExports("tidyhydro"))/2` metrics are implemented.
-
-| Name | Abbr. | Function calls | Reference |
-|----------------|--------|--------|-------------|
-| Kling-Gupta Efficiency | $KGE$ | `kge`, `kge_vec` | <span style="font-size: 0.8em;">Gupta, H.V.; Kling, H.; Yilmaz, K.K.; Martinez, G.F. (2009). *Journal of Hydrology*, 377(1–2), 80–91.</span> |
-| Modified Kling-Gupta Efficiency | $KGE'$ | `kge2012`, `kge_vec` | <span style="font-size: 0.8em;">Kling, H., Fuchs, M., & Paulin, M. (2012). *Journal of Hydrology*, 424–425, 264–277.</span> |
-| Nash-Sutcliffe Efficiency | $NSE$ | `nse`, `nse_vec` | <span style="font-size: 0.8em;">Nash, J. E., & Sutcliffe, J. V. (1970). *Journal of Hydrology*, 10(3), 282–290.</span> |
-| Mean Squared Error | $MSE$ | `mse`, `mse_vec` | <span style="font-size: 0.8em;">Clark, M. P., Vogel, R. M., Lamontagne, J. R., Mizukami, N., Knoben, W. J. M., Tang, G., Gharari, S., Freer, J. E., Whitfield, P. H., Shook, K. R., & Papalexiou, S. M. (2021). The Abuse of Popular Performance Metrics in Hydrologic Modeling. Water Resources Research, 57(9), e2020WR029001.</span> |
-| Percent BIAS | $pBIAS$ | `pbias`, `pbias_vec` | <span style="font-size: 0.8em;">Gupta, H. V., S. Sorooshian, and P. O. Yapo. (1999). Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration. J. Hydrologic Eng. 4(2): 135-143 </span> |
-| PRediction Error Sum of Squares | $PRESS$ | `press`, `press_vec` | <span style="font-size: 0.8em;"> Rasmussen, P. P., Gray, J. R., Glysson, G. D. & Ziegler, A. C. Guidelines and procedures for computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data. in U.S. Geological Survey Techniques and Methods book 3, chap. C4 53 (2009)</span> |
-| Standard Factorial Error | $SFE$ | `sfe`, `sfe_vec` | <span style="font-size: 0.8em;"> Herschy, R.W. 1978: Accuracy. Chapter 10 In: Herschy, R.W. (ed.) Hydrometry - principles and practices. John Wiley and Sons, Chichester, 511 p.</span> |
-
-: Metrics currently implemented in `tidyhydro` v`r packageVersion("tidyhydro")`
-
-# `avacha` dataset
-
-The package includes the mean daily water discharge values (`obs` in m³/s) measured at the state gauging station Avacha River — Elizovo City (site No. 2090). Alongside the measured water discharge, the mean water discharge in the last 24 hours derived from the [GloFAS-ERA5 v4.0](https://confluence.ecmwf.int/display/CEMS/GloFAS+v4.0) reanalysis is provided (`sim`).
+The package includes the mean daily water discharge values (`obs` in m³/s) measured at the state gauging station [Avacha River — Elizovo City](https://www.openstreetmap.org/#map=18/53.183111/158.393269) (site No. 2090). Alongside the measured water discharge, the mean water discharge in the last 24 hours derived from the [GloFAS-ERA5 v4.0](https://confluence.ecmwf.int/display/CEMS/GloFAS+v4.0) reanalysis is provided (`sim`).
 
 ```{r}
 #| fig-cap: Avacha River - Elizovo City hydrograph