test_flex.Rmd

---
title: "Test Flex"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: scroll
runtime: shiny
---
  
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(rlang)
#library(DT)
library(vedar)
library(igraph)
library(networkD3)
library(readxl)
source("./src/graph_functions.R")
sn_h <- 600
sn_w <- 1000

```


```{r, include=FALSE}
#load data
demos_007_vdt <- read.csv("demos_007_vdt.csv")

```


Inputs {.sidebar}
-----------------------------------------------------------------------
  
```{r}


process_list <- sort(unique(demos_007_vdt$process_description))
selectInput("process_select", "Process", 
            selected = process_list[1],
            process_list, 
            multiple = F)

region_list <- sort(unique(demos_007_vdt$region))
selectInput("region_select", "Region",
            selected = region_list[2],
            region_list,
            multiple = F)

selectInput("order_select", "N connections", 
            seq(1,3))


```

This dashboard presents maps of the reference energy system for the demos_007 data. It enables the visualisation of the RES around a process ("node") for "N connection" steps around the process.


**Usage**

* Select a process and region from the dropdowns to render map and relevant data
* Select the number of connection steps to include in the map
* The maps are read from left to right. Processes are shown as nodes. The commodities that flow between the processes are identified by pop-up on the links between the processes. In some datasets, nodes with suffixes `_start_process`, `_end_process` appear. These do not represent a physical processes and are only required for visualisation/modelling purposes.
* An individual process may appear in several maps due to overlaps/
* The process nodes in maps can be rearranged in the vertical plane.



Row {data-height=800}
-----------------------------------------------------------------------
  
### Map
  
```{r}
#subset graph to sector of interest
g <- reactive({
  make_graph_from_veda_df(demos_007_vdt %>% 
                             filter(
                               region == 
                                 input$region_select),
                             input_data_type = "vdt")
  })

subgraph_select <- reactive({
  #make ego graph returns a list of the order connections from node
  g_in <-  make_ego_graph(g(), 
                 order = input$order_select, 
                 nodes = input$process_select, 
                 #to return the graph, take [[1]]
                 mode = "in")[[1]]
  
  g_out <-  make_ego_graph(g(), 
                 order = input$order_select, 
                 nodes = input$process_select, 
                 #to return the graph, take [[1]]
                 mode = "out")[[1]]
  combine_graphs(list(g_in, g_out))
})


renderSankeyNetwork({
  make_res_from_graph(subgraph_select(),
                      sankey_width = sn_w, 
                      sankey_height = sn_h)
})
```