## 3. Open binary datasets

---
### Introduction
The most important part of [xgrads](https://github.com/miniufo/xgrads) is to load the binary data (**NOT** all of them but the portion that is needed right now) into memory as [xarray](https://docs.xarray.dev/en/stable/).  This is built on correctly parsing the CTL files.

---
### Loading binary data
#### Single CTL file
The loading of CTL dataset does not require an explicit parsing of CTL file.  So the reading is pretty simple:
```python
from xgrads import open_CtlDataset

dset = open_CtlDataset('test10.ctl')
print(dset)
```

The output is in the view of [xarray](https://docs.xarray.dev/en/stable/):
```python
>>> print(dset)
<xarray.Dataset>
Dimensions:    (time: 1, x: 360, y: 320)
Coordinates:
  * time       (time) datetime64[ns] 2019-01-01
  * y          (y) float64 0.0 1.5e+04 3e+04 ... 4.755e+06 4.77e+06 4.785e+06
  * x          (x) float64 0.0 1.5e+04 3e+04 ... 5.355e+06 5.37e+06 5.385e+06
Data variables:
    emi_index  (time, y, x) float32 dask.array<chunksize=(1, 320, 360), meta=np.ndarray>
Attributes:
    comment:  pm u2/m3
    storage:  99
    title:    CUACE_emi_index
    undef:    -9999.0
    pdef:     lcc
```

Note that the parsing of CTL file is implicitly done within `open_CtlDataset()`.  So if one wants both the `dset` and `ctl`, adding a kwarg `returnctl=True` will be OK:
```python
from xgrads import open_CtlDataset

dset, ctl = open_CtlDataset('test10.ctl', returnctl=True)

print(dset)
print(ctl)
```

#### Multiple CTL files
If there are multiple CTL files describing similar spatial datasets of different time steps, one can also load them into a single dataset using `open_mfdataset()`.  This is similar to [xarray](https://docs.xarray.dev/en/stable/)'s `open_mfdataset()`.  Usually, this should be done with the [`template`](http://cola.gmu.edu/grads/gadoc/templates.html) functionality of CTL.  But simutaneously open multiple CTL datasets is also easy because of the combining of the multiple dataset is easy by making use of [xarray](https://docs.xarray.dev/en/stable/)'s `concat()` API.
```python
from xgrads import open_mfdataset

dset = open_mfdataset('./test8_*.ctl', parallel=True)

print(ctl)
```