New method to fetch data along a given trajectory

## Motivation
For some Argo data analysis it could be useful to be able to fetch data `around` some specific locations, eg:

- compare some float data with neighbor floats (any QC would do this, but also sensor dev. see eg from @matdever #168 )

- co-localise Argo float profiles with some Huricane path ([eg here]( http://arashi.geosci.msstate.edu/tropical/2021/Argo2021.html) from [Kim Wood](https://twitter.com/DrKimWood ) )

it could be useful to have an access point that directly fetch this.

## API for new access point
It could look like this:
```python
from argopy import DataFetcher as ArgoDataFetcher

# Default temporal distance is 'days' and radial distance unit is 'degree':
neighbor_fetcher = ArgoDataFetcher(ds='phy').around(wmo=[6903754], dt=365, dr=1) # All float trajectory
neighbor_fetcher = ArgoDataFetcher(ds='phy').around(wmo=[6903754], cyc=[12], dt=365, dr=1) # Single profile
neighbor_fetcher = ArgoDataFetcher(ds='phy').around(wmo=[6903754], cyc=[12,13,14], dt=365, dr=1) # Selected profiles

# Possibly distinguish zonal and meridional distances:
neighbor_fetcher = ArgoDataFetcher(ds='ref').around(wmo=[6903754], dt=30, dx=2, dy=1)

# Use option to change units:
neighbor_fetcher = ArgoDataFetcher(ds='ref').around(wmo=[6903754], dt=30, dx=100, dy=50, unit='km')

# Get data/index the classic way:
neighbor_ds = neighbor_fetcher.load().data

# argopy would add new variables to the fetched data, like distances to the requested reference profiles:
neighbor_ds['distance_time']
neighbor_ds['distance_radial']
neighbor_ds['distance_zonal']
neighbor_ds['distance_meridional']
```

This new access point, could in fact take a path or trajectory as input:
```python
from argopy import DataFetcher as ArgoDataFetcher

# [2021 Hurricane Larry](https://www.nhc.noaa.gov/data/tcr/index.php?season=2021&basin=atl)
traj = [[-26.00,12.00,'2021-09-01 12:00:00'],[-33.00,13.00,'2021-09-02 12:00:00'],[-40.00,14.00,'2021-09-03 12:00:00'],[-45.00,16.00,'2021-09-04 12:00:00'],[-49.00,19.00,'2021-09-05 12:00:00'],[-52.00,21.00,'2021-09-06 12:00:00'],[-55.00,24.00,'2021-09-07 12:00:00'],[-57.00,27.00,'2021-09-08 12:00:00'],[-61.00,31.00,'2021-09-09 12:00:00'],[-61.00,38.00,'2021-09-10 12:00:00'],[-49.00,52.00,'2021-09-11 12:00:00']]

neighbor_fetcher = ArgoDataFetcher(ds='phy').around(path=traj, dt=5, dr=50, unit='km')
```

## Further
Note this API could easily be plugged into the ``argo`` access point:
```python
from argopy import DataFetcher as ArgoDataFetcher

float_fetcher = ArgoDataFetcher(ds='phy').float(6903754)
float_ds = fetcher.load().data

neighbor_ds = float_ds.argo.around(dt=365, dr=1)
neighbor_ds = float_ds.argo.around(dt=365, dx=2, dy=1)
neighbor_ds = float_ds.argo.around(dt=365, dx=100, dy=50, unit='km')
neighbor_ds = float_ds.argo.around(dt=365, dr=1, ds='ref') # Fetch data from the Argo CTD reference
```

Start by tracing the DataFetcher entry point and its existing .float(), .load(), and .argo access points; the issue names no implementation files or tests. Compare the proposed .around() forms for wmo, cyc, and path with current fetcher behavior. Done means the examples work and returned data includes the requested distance variables.

Written by the indexing model from the issue text.