Minor changes to the network analysis

%% Cell type:code id: tags:

``` R

library(dplyr)

library(glatos)

library(stringr)

library(plotly)

```

%% Cell type:code id: tags:

``` R

det_file <- system.file("extdata", "walleye_detections.csv",

                         package = "glatos")

detections <- read_glatos_detections(det_file)

detections <- glatos::false_detections(detections, tf = 3600)

filtered_detections <- detections %>% filter(passed_filter != FALSE)

detection_events <- glatos::detection_events(filtered_detections, location_col = 'station')

```

%% Cell type:code id: tags:

``` R

detection_events %>%

arrange(first_detection) %>%

group_by(individual) %>%

mutate(to = lead(location)) %>%

mutate(to_latitude = lead(mean_latitude)) %>%

mutate(to_longitude = lead(mean_longitude)) %>%

group_by(location, to) %>%

summarise(moves = n(),

          latitude = mean(mean_latitude),

          longitude=mean(mean_longitude),

          to_latitude=mean(to_latitude),

          to_longitude=mean(to_longitude)

          to_longitude=mean(to_longitude),

          res_time_seconds = mean(res_time_sec)

         ) %>%

rename(from=location) %>%

na.omit() -> network_analysis_data

receivers <- network_analysis_data %>%

                group_by(from) %>%

                summarise(

                  latitude = mean(latitude),

                  longitude = mean(longitude),

                    n = sum(moves)

                    visits = sum(moves),

                    res_time_seconds = mean(res_time_seconds)

                 )

```

%% Cell type:code id: tags:

``` R

geo <- list(

    projection = list(type = 'azimuthal equal area'),

    showland = TRUE,

    showland = TRUE,

    landcolor = toRGB("gray95"),

    countrycolor = toRGB("gray80"),

    showlakes =TRUE,

    lakecolor = toRGB("#A0AAB4"),

    resolution = 50,

    center = list(lat = ~median(latitude),

                lon = ~median(longitude)),

    lonaxis = list(range=c(~min(longitude)-1, ~max(longitude)+1)),

    lataxis = list(range=c(~min(latitude)-1, ~max(latitude)+1))

)

network <- network_analysis_data %>%

    plot_geo(height=800) %>%

    add_segments(

        x = ~longitude, xend = ~to_longitude,

        y = ~latitude, yend = ~to_latitude,

        alpha = 0.4, size = I(1.5), hoverinfo = "none", color=I("red")

      ) %>%

      add_markers(

        data=receivers,

        x = ~longitude, y = ~latitude, text = ~paste(from, ":", n),

        size = ~n, hoverinfo = "text", alpha = 0.9, color=~n

        x = ~longitude, y = ~latitude, text = ~paste(from, ":", visits, ' visits & ', res_time_seconds, ' seconds of residence time on average'),

        size = ~res_time_seconds, hoverinfo = "text", alpha = 0.5, color=~visits

      ) %>%

      layout(

        title = 'Walleye Salmon Network Plot',

        geo = geo, showlegend = FALSE

      )

```

%% Cell type:code id: tags:

``` R

embed_notebook(network)

```

%% Cell type:code id: tags:

``` R

library(cowsay)

cowsay::say("Any questions?",by="shark",)

```

%% Cell type:code id: tags:

``` R

```