dennissergeev

dennissergeev

dennissergeev

import pandas as pd
import matplotlib.pyplot as plt

url = 'http://svo2.cab.inta-csic.es/theory/newov/ssap.php?model=bt-settl&fid=752&format=ascii'

df = pd.read_csv(url, skiprows=9, names=['wavelength', 'flux'], sep='\t', index_col=False,
                 skipfooter=1, engine='python', dtype={'wavelength': float, 'flux': float})
df['wavelength'] *= 1e-4

fig, ax = plt.subplots()

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def roll_cube_e2w(cube_in, inplace=False):
    """Takes a cube which goes longitude 0-360 back to -180-180."""
    if inplace:
        cube = cube_in
    else:
        cube = cube_in.copy()
    lon = cube.coord('longitude')
    if (lon.points >= 0.).all():
        if (lon.points <= 360.).all():
            subtract = -180.

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def label_global_map(fig, ax, xticks, yticks, xoff=-10, yoff=-10, degree=False, **text_kw):
    """Label gridlines of a global cartopy map."""
    geodetic_trans = ccrs.Geodetic()
    xlab_kw = ylab_kw = dict(va="center", ha="center", **text_kw)
    for xtick in xticks:
        s = format_lonlat(xtick, "lon", degree=degree)
        text_transform = offset_copy(
            geodetic_trans._as_mpl_transform(ax), fig=fig, units="points", x=0, y=yoff
        )
        ax.text(xtick, -90, s, transform=text_transform, **xlab_kw)

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# -*- coding: utf-8 -*-
"""Operations on cartesian geographical grid."""
import numpy as np

EARTH_RADIUS = 6371000.0  # m


def _guess_bounds(points, bound_position=0.5):
    """
    Guess bounds of grid cells.

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def roll_da_to0360(da, lon_name='longitude'):
    """Roll DataArray's data with longitudes from (-180, 180) to (0, 360)."""
    # Roll longitudes and corresponding data
    out = da.roll(longitude=da[lon_name].shape[0]//2, roll_coords=True)
    # Reset western (negative) longitudes to values within (180, 360) range
    out[lon_name] = out[lon_name] - (out[lon_name] // 360) * 360
    return out

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import pyvista as pv
import numpy as np

arr = np.random.rand(40, 72, 144)

grid = pv.UniformGrid()

grid.dimensions = np.array(arr.shape) + 1

grid.origin = (0, 0, 0)  # The bottom left corner of the data set

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dennissergeev

import cdsapi

c = cdsapi.Client()

c.retrieve(
    'reanalysis-era5-single-levels',
    {
        'product_type':'reanalysis',
        'format':'netcdf',
        # Select area: lat_n/lon_w/lat_s/lon_e in degrees