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SpatLyu merged 2 commits into from
Jan 23, 2025
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update vigenette #15

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904c809
update vignette
SpatLyu Jan 23, 2025
fd73928
rebuild vignette
SpatLyu Jan 23, 2025
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204 changes: 57 additions & 147 deletions vignettes/cisp.rmd
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Expand Up @@ -21,166 +21,76 @@ library(cisp)

## Spatial pattern correlation

Using the same data as [the gdverse idsa vignette](https://stscl.github.io/gdverse/articles/idsa.html):
Using the same data as [the gdverse opgd vignette](https://stscl.github.io/gdverse/articles/opgd.html). Since the `spc` function in CISP requires all input variables to be continuous, only continuous variables are retained in the data:


``` r
depression = system.file('extdata/Depression.csv',package = 'gdverse') |>
readr::read_csv() |>
sf::st_as_sf(coords = c('X','Y'), crs = 4326)
## Rows: 1072 Columns: 13
## ── Column specification ───────────────────────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (13): X, Y, Depression_prevelence, PopulationDensity, Population65, NoHealthInsurance, Neig...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
depression
## Simple feature collection with 1072 features and 11 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: -83.1795 ymin: 32.11464 xmax: -78.6023 ymax: 35.17354
## Geodetic CRS: WGS 84
## # A tibble: 1,072 × 12
## Depression_prevelence PopulationDensity Population65 NoHealthInsurance Neighbor_Disadvantage
## * <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 23.1 61.5 22.5 7.98 -0.0525
## 2 22.8 58.3 16.8 11.0 -0.254
## 3 23.2 35.9 24.5 9.31 -0.0540
## 4 21.8 76.1 21.8 13.2 0.0731
## 5 20.7 47.3 22.0 11 0.763
## 6 21.3 32.5 19.2 13.0 0.422
## 7 22 36.9 19.2 10.8 0.113
## 8 21.2 61.5 15.9 8.57 -0.154
## 9 22.7 67.2 15.7 17.8 -0.320
## 10 20.6 254. 11.3 12.7 0.457
## # ℹ 1,062 more rows
## # ℹ 7 more variables: Beer <dbl>, MentalHealthPati <dbl>, NatureParks <dbl>, Casinos <dbl>,
## # DrinkingPlaces <dbl>, X.HouseRent <dbl>, geometry <POINT [°]>
ndvi = gdverse::ndvi
ndvi
## # A tibble: 713 × 7
## NDVIchange Climatezone Mining Tempchange Precipitation GDP Popdensity
## <dbl> <chr> <fct> <dbl> <dbl> <dbl> <dbl>
## 1 0.116 Bwk low 0.256 237. 12.6 1.45
## 2 0.0178 Bwk low 0.273 214. 2.69 0.801
## 3 0.138 Bsk low 0.302 449. 20.1 11.5
## 4 0.00439 Bwk low 0.383 213. 0 0.0462
## 5 0.00316 Bwk low 0.357 205. 0 0.0748
## 6 0.00838 Bwk low 0.338 201. 0 0.549
## 7 0.0335 Bwk low 0.296 210. 11.9 1.63
## 8 0.0387 Bwk low 0.230 236. 30.2 4.99
## 9 0.0882 Bsk low 0.214 342. 241 20.0
## 10 0.0690 Bsk low 0.245 379. 42.0 7.50
## # ℹ 703 more rows
ndvi = dplyr::select(ndvi,-c(Climatezone,Mining))
ndvi
## # A tibble: 713 × 5
## NDVIchange Tempchange Precipitation GDP Popdensity
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0.116 0.256 237. 12.6 1.45
## 2 0.0178 0.273 214. 2.69 0.801
## 3 0.138 0.302 449. 20.1 11.5
## 4 0.00439 0.383 213. 0 0.0462
## 5 0.00316 0.357 205. 0 0.0748
## 6 0.00838 0.338 201. 0 0.549
## 7 0.0335 0.296 210. 11.9 1.63
## 8 0.0387 0.230 236. 30.2 4.99
## 9 0.0882 0.214 342. 241 20.0
## 10 0.0690 0.245 379. 42.0 7.50
## # ℹ 703 more rows
```


``` r
system.time({
g = cisp::spc(depression,cores = 12)
g = cisp::spc(ndvi,cores = 6)
})
## user system elapsed
## 6.07 0.86 2018.65
## 1.14 0.30 23.16
g
## *** Spatial Pattern Correlation
##
## | xv | yv | correlation |
## |:---------------------:|:---------------------:|:-----------:|
## | PopulationDensity | Depression_prevelence | 0.04614 |
## | Population65 | Depression_prevelence | 0.04150 |
## | Neighbor_Disadvantage | Depression_prevelence | 0.03924 |
## | DrinkingPlaces | Depression_prevelence | 0.01485 |
## | NoHealthInsurance | Depression_prevelence | 0.01384 |
## | NatureParks | Depression_prevelence | 0.01239 |
## | MentalHealthPati | Depression_prevelence | 0.01042 |
## | X.HouseRent | Depression_prevelence | 0.00777 |
## | Beer | Depression_prevelence | 0.00191 |
## | Casinos | Depression_prevelence | -0.00708 |
## | X.HouseRent | PopulationDensity | 0.07832 |
## | MentalHealthPati | PopulationDensity | 0.01587 |
## | DrinkingPlaces | PopulationDensity | 0.01484 |
## | Population65 | PopulationDensity | 0.01037 |
## | NoHealthInsurance | PopulationDensity | 0.00619 |
## | NatureParks | PopulationDensity | 0.00528 |
## | Beer | PopulationDensity | 0.00115 |
## | Casinos | PopulationDensity | 0.00108 |
## | Neighbor_Disadvantage | PopulationDensity | -0.00529 |
## | Depression_prevelence | PopulationDensity | -0.07737 |
## | X.HouseRent | Population65 | 0.08942 |
## | Neighbor_Disadvantage | Population65 | 0.04196 |
## | PopulationDensity | Population65 | 0.02396 |
## | Depression_prevelence | Population65 | 0.02231 |
## | MentalHealthPati | Population65 | 0.00562 |
## | DrinkingPlaces | Population65 | 0.00349 |
## | NoHealthInsurance | Population65 | 0.00346 |
## | Beer | Population65 | -0.00529 |
## | NatureParks | Population65 | -0.00766 |
## | Casinos | Population65 | -0.00976 |
## | Neighbor_Disadvantage | NoHealthInsurance | 0.11050 |
## | X.HouseRent | NoHealthInsurance | 0.06270 |
## | Population65 | NoHealthInsurance | 0.02928 |
## | PopulationDensity | NoHealthInsurance | 0.02298 |
## | DrinkingPlaces | NoHealthInsurance | 0.01302 |
## | Casinos | NoHealthInsurance | 0.00775 |
## | MentalHealthPati | NoHealthInsurance | 0.00657 |
## | Beer | NoHealthInsurance | 0.00434 |
## | NatureParks | NoHealthInsurance | 0.00197 |
## | Depression_prevelence | NoHealthInsurance | -0.00779 |
## | DrinkingPlaces | Neighbor_Disadvantage | 0.09369 |
## | NoHealthInsurance | Neighbor_Disadvantage | 0.06840 |
## | X.HouseRent | Neighbor_Disadvantage | 0.06004 |
## | NatureParks | Neighbor_Disadvantage | 0.01924 |
## | Population65 | Neighbor_Disadvantage | 0.01867 |
## | MentalHealthPati | Neighbor_Disadvantage | 0.01157 |
## | Casinos | Neighbor_Disadvantage | 0.00541 |
## | PopulationDensity | Neighbor_Disadvantage | -0.00357 |
## | Depression_prevelence | Neighbor_Disadvantage | -0.00665 |
## | Beer | Neighbor_Disadvantage | -0.00989 |
## | Casinos | Beer | 0.04989 |
## | Population65 | Beer | 0.01780 |
## | DrinkingPlaces | Beer | 0.01469 |
## | NatureParks | Beer | 0.01295 |
## | Neighbor_Disadvantage | Beer | 0.00331 |
## | PopulationDensity | Beer | 0.00211 |
## | MentalHealthPati | Beer | 0.00161 |
## | X.HouseRent | Beer | -0.00016 |
## | NoHealthInsurance | Beer | -0.00306 |
## | Depression_prevelence | Beer | -0.03499 |
## | DrinkingPlaces | MentalHealthPati | 0.07590 |
## | PopulationDensity | MentalHealthPati | 0.03785 |
## | NatureParks | MentalHealthPati | 0.03208 |
## | Neighbor_Disadvantage | MentalHealthPati | 0.02471 |
## | Casinos | MentalHealthPati | 0.02460 |
## | Beer | MentalHealthPati | 0.01057 |
## | Population65 | MentalHealthPati | 0.00982 |
## | X.HouseRent | MentalHealthPati | 0.00799 |
## | Depression_prevelence | MentalHealthPati | -0.01049 |
## | NoHealthInsurance | MentalHealthPati | -0.01681 |
## | DrinkingPlaces | NatureParks | 0.07349 |
## | MentalHealthPati | NatureParks | 0.03486 |
## | X.HouseRent | NatureParks | 0.02807 |
## | Neighbor_Disadvantage | NatureParks | 0.02704 |
## | PopulationDensity | NatureParks | 0.01846 |
## | NoHealthInsurance | NatureParks | 0.01689 |
## | Beer | NatureParks | 0.01029 |
## | Casinos | NatureParks | 0.00842 |
## | Population65 | NatureParks | -0.01961 |
## | Depression_prevelence | NatureParks | -0.06237 |
## | DrinkingPlaces | Casinos | 0.05319 |
## | Population65 | Casinos | 0.03494 |
## | Beer | Casinos | 0.02488 |
## | NatureParks | Casinos | 0.01989 |
## | MentalHealthPati | Casinos | 0.01854 |
## | Neighbor_Disadvantage | Casinos | 0.00293 |
## | NoHealthInsurance | Casinos | 0.00009 |
## | PopulationDensity | Casinos | -0.00207 |
## | X.HouseRent | Casinos | -0.00864 |
## | Depression_prevelence | Casinos | -0.01344 |
## | NatureParks | DrinkingPlaces | 0.10000 |
## | MentalHealthPati | DrinkingPlaces | 0.04482 |
## | PopulationDensity | DrinkingPlaces | 0.03366 |
## | Casinos | DrinkingPlaces | 0.02222 |
## | Beer | DrinkingPlaces | 0.01330 |
## | NoHealthInsurance | DrinkingPlaces | 0.00258 |
## | X.HouseRent | DrinkingPlaces | 0.00185 |
## | Neighbor_Disadvantage | DrinkingPlaces | -0.00400 |
## | Depression_prevelence | DrinkingPlaces | -0.01162 |
## | Population65 | DrinkingPlaces | -0.03072 |
## | PopulationDensity | X.HouseRent | 0.12494 |
## | Neighbor_Disadvantage | X.HouseRent | 0.08995 |
## | Population65 | X.HouseRent | 0.04227 |
## | NoHealthInsurance | X.HouseRent | 0.01481 |
## | DrinkingPlaces | X.HouseRent | 0.00667 |
## | MentalHealthPati | X.HouseRent | -0.00175 |
## | Casinos | X.HouseRent | -0.00581 |
## | Depression_prevelence | X.HouseRent | -0.00587 |
## | Beer | X.HouseRent | -0.00692 |
## | NatureParks | X.HouseRent | -0.01047 |
## | xv | yv | correlation |
## |:-------------:|:-------------:|:-----------:|
## | Precipitation | NDVIchange | 0.39517 |
## | Tempchange | NDVIchange | 0.01905 |
## | Popdensity | NDVIchange | 0.00483 |
## | GDP | NDVIchange | -0.02158 |
## | Precipitation | Tempchange | 0.07679 |
## | NDVIchange | Tempchange | 0.04977 |
## | Popdensity | Tempchange | 0.01516 |
## | GDP | Tempchange | -0.01466 |
## | NDVIchange | Precipitation | 0.35303 |
## | Popdensity | Precipitation | 0.01140 |
## | Tempchange | Precipitation | -0.00265 |
## | GDP | Precipitation | -0.02745 |
## | Popdensity | GDP | 0.29824 |
## | Tempchange | GDP | 0.09282 |
## | NDVIchange | GDP | 0.08061 |
## | Precipitation | GDP | 0.04213 |
## | GDP | Popdensity | 0.15481 |
## | Tempchange | Popdensity | 0.04483 |
## | NDVIchange | Popdensity | 0.00442 |
## | Precipitation | Popdensity | -0.07190 |
```

The results are visualized in a default network graph style:
Expand Down
18 changes: 9 additions & 9 deletions vignettes/cisp.rmd.orig
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ vignette: >
knitr::opts_chunk$set(
collapse = TRUE,
fig.path = "man/figures/cisp/",
fig.dpi = 150
fig.dpi = 100
)
```

Expand All @@ -27,30 +27,30 @@ library(cisp)

## Spatial pattern correlation

Using the same data as [the gdverse idsa vignette](https://stscl.github.io/gdverse/articles/idsa.html):
Using the same data as [the gdverse opgd vignette](https://stscl.github.io/gdverse/articles/opgd.html). Since the `spc` function in CISP requires all input variables to be continuous, only continuous variables are retained in the data:

```{r load_data}
depression = system.file('extdata/Depression.csv',package = 'gdverse') |>
readr::read_csv() |>
sf::st_as_sf(coords = c('X','Y'), crs = 4326)
depression
ndvi = gdverse::ndvi
ndvi
ndvi = dplyr::select(ndvi,-c(Climatezone,Mining))
ndvi
```

```{r run_g}
system.time({
g = cisp::spc(depression,cores = 12)
g = cisp::spc(ndvi,cores = 6)
})
g
```

The results are visualized in a default network graph style:

```{r plot_g1,fig.width=8.05,fig.height=4.05,fig.cap=knitr::asis_output("**Figure 1**. Spatial Pattern Correlation Network Visualization Results")}
```{r plot_g1,fig.width=5,fig.height=3.55,fig.cap=knitr::asis_output("**Figure 1**. Spatial Pattern Correlation Network Visualization Results")}
plot(g)
```

But the results can also be plotted using the classic correlation coefficient matrix visualization style:

```{r plot_g2,fig.width=8.05,fig.height=7.55,fig.cap=knitr::asis_output("**Figure 2**. Spatial Pattern Correlation Matrix Visualization Results")}
```{r plot_g2,fig.width=5,fig.height=3.55,fig.cap=knitr::asis_output("**Figure 2**. Spatial Pattern Correlation Matrix Visualization Results")}
plot(g,style = "matrix")
```
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