utils.py

# Some utitilties to read/convert data for EUMETSAT satellite archive
# In the future all data readers will be moved here 
import numpy as np # Import the Numpy package
from matplotlib.offsetbox import AnchoredText
from scipy.ndimage import interpolation

def chunks(l, n):
    """Yield successive n-sized chunks from l."""
    for i in range(0, len(l), n):
        yield l[i:i + n]

def brigthness_temp(var):
    """ Compute the brightness temperature given input data, which should be 
        relative to the infrared channels of SEVIRI. The channel number is read
        from the NETCDF variable name, so that the correct coefficients for the
        conversions are used. 
        
        TO-DO. Check before if the value is masked. This should be a problem if
        the domain extends somehwere outside the satellite POV."""
    
    
    channels = {
        'ch4':{'nu_c':2569.094, 'A':0.9959, 'B':3.471},
        'ch5':{'nu_c':1598.566, 'A':0.9963, 'B':2.219},
        'ch6':{'nu_c':1362.142, 'A':0.9991, 'B':0.485},
        'ch7':{'nu_c':1149.083, 'A':0.9996, 'B':0.181},
        'ch8':{'nu_c':1034.345, 'A':0.9999, 'B':0.060},
        'ch9':{'nu_c':930.659 , 'A':0.9983, 'B':0.627},
        'ch10':{'nu_c':839.661, 'A':0.9988, 'B':0.627},
        'ch11':{'nu_c':752.381, 'A':0.9981, 'B':0.576}
             }
    
    # these are universal
    C1 = 1.19104E-5
    C2 = 1.43877
    
    nu_c = channels[var.name]['nu_c']
    A = channels[var.name]['A']
    B = channels[var.name]['B']
    
    temp_b = ( (C2*nu_c)/(A*np.ma.log((C1*nu_c**3/var[:])+1)) ) - (B/A)
    
    temp_b = temp_b - 273.15
    
    return(temp_b)

def annotation(ax, text, loc='upper right',fontsize=8):
    """Put a general annotation in the plot."""
    at = AnchoredText('%s'% text, prop=dict(size=fontsize), frameon=True, loc=loc)
    at.patch.set_boxstyle("round,pad=0.,rounding_size=0.1")
    at.zorder = 10
    ax.add_artist(at)
    return(at)

def create_coord_hrv(lats, lons):
    """Create dummy coordinates for HRV channel by enlarging lats and lons
    to match the dimension of the HRV channel and filling by spline interpolation.
    This is of course not the best method but it works pretty well. The
    coefficients for the zoom are chosen by trial & error, unfortunately the
    'perfect' aspect ratio works only for x but not for the y coordinate.
    No idea why"""
    
    lons_hrv = interpolation.zoom(lons,[3,2.992])
    lats_hrv = interpolation.zoom(lats,[3,2.992])
    
    return lats_hrv, lons_hrv