---
title: "Quickstart guide"
output:
  rmarkdown::html_vignette:
    self_contained: true
vignette: >
  %\VignetteIndexEntry{Quickstart guide}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(varunayan)
```

## ERA5 data

ERA5 provides global climate reanalysis data. Requires [CDS API credentials](https://cds.climate.copernicus.eu/how-to-api).

```{r era5-setup, eval=FALSE}
# One-time setup
setup_cds_credentials(key = "your-personal-access-token")
```

### Bounding box

```{r era5-bbox, eval=FALSE}
df <- era5ify_bbox(
  request_id = "mumbai_temp",
  variables = c("2m_temperature", "total_precipitation"),
  start_date = "2024-01-01",
  end_date = "2024-01-31",
  north = 20, south = 18, east = 74, west = 72,
  frequency = "daily"
)
```

### GeoJSON region

```{r era5-geojson, eval=FALSE}
df <- era5ify_geojson(
  request_id = "india_weather",
  variables = c("2m_temperature"),
  start_date = "2024-01-01",
  end_date = "2024-01-07",
  json_file = "india.geojson",
  frequency = "daily"
)
```

### Point location

```{r era5-point, eval=FALSE}
df <- era5ify_point(
  request_id = "delhi_temp",
  variables = c("2m_temperature"),
  start_date = "2024-01-01",
  end_date = "2024-01-31",
  lat = 28.6139, lon = 77.2090,
  frequency = "daily"
)
```

## IMD data

IMD provides high-resolution gridded data for India. No credentials required.

### Rainfall

```{r imd-rainfall, eval=FALSE}
# 0.25 degree resolution rainfall
df <- imd_rainfall_bbox(
  request_id = "maharashtra_rain",
  start_year = 2023,
  end_year = 2023,
  north = 22, south = 16, east = 80, west = 73,
  resolution = 0.25,
  frequency = "monthly"
)
```

### Temperature

```{r imd-temperature, eval=FALSE}
# Maximum temperature
df <- imd_temperature_bbox(
  request_id = "delhi_tmax",
  start_year = 2023,
  end_year = 2023,
  north = 30, south = 27, east = 78, west = 76,
  var_type = "tmax"
)
```

### GeoJSON region

```{r imd-geojson, eval=FALSE}
df <- imd_rainfall_geojson(
  request_id = "kerala_rain",
  start_year = 2023,
  end_year = 2023,
  geojson_file = "kerala.geojson",
  resolution = 0.25
)
```

## Variable discovery

```{r variables, message=FALSE}
# Search variables
search_variable("temperature")

# Get descriptions
describe_variables(c("2m_temperature", "total_precipitation"))

# List all
head(list_available_variables("single"), 10)
```

## Cache management

```{r cache, message=FALSE}
# View cache
show_cache_info()
```