In [2]:
import numpy as np
import xarray as xr
import math
import matplotlib.pyplot as plt
%matplotlib inline
In [4]:
ds = xr.open_dataset('/data/jpetrie/MEOPAR/SalishSea/results/d9f69a38-160e-11e6-9b98-0025909a8461/SS5x5_1h_20041019_20041023_ptrc_T.nc')
In [5]:
print(ds)
<xarray.Dataset>
Dimensions: (axis_nbounds: 2, deptht: 40, time_counter: 120, x: 5, y: 5)
Coordinates:
nav_lat (y, x) float32 -0.5 -0.5 -0.5 -0.5 -0.5 0.0 0.0 ...
nav_lon (y, x) float32 0.0 0.5 1.0 1.5 2.0 0.0 0.5 1.0 1.5 ...
* deptht (deptht) float32 1.28205 3.84615 6.41026 8.97436 ...
time_centered (time_counter) datetime64[ns] 2004-10-19T00:30:00 ...
* time_counter (time_counter) datetime64[ns] 2004-10-19T00:30:00 ...
* axis_nbounds (axis_nbounds) int64 0 1
* x (x) int64 0 1 2 3 4
* y (y) int64 0 1 2 3 4
Data variables:
deptht_bounds (deptht, axis_nbounds) float32 0.0 2.5641 2.5641 ...
NO3 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
time_centered_bounds (time_counter, axis_nbounds) float64 3.307e+09 ...
time_counter_bounds (time_counter, axis_nbounds) float64 3.307e+09 ...
NH4 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
Si (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
PHY2 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
PHY (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
MYRI (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
MICZ (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
DOC (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
POC (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
bSi (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
O2 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
Attributes:
name: SS5x5_1h_20041019_20041023
description: sog variables
title: sog variables
Conventions: CF-1.5
production: An IPSL model
timeStamp: 2016-May-09 10:52:56 PDT
In [9]:
print(ds.dims)
print(ds.dims['deptht'])
Frozen(SortedKeysDict({'x': 5, 'y': 5, 'axis_nbounds': 2, 'deptht': 40, 'time_counter': 120}))
40
In [10]:
ds.data_vars
Out[10]:
Data variables:
deptht_bounds (deptht, axis_nbounds) float32 0.0 2.5641 2.5641 ...
NO3 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
time_centered_bounds (time_counter, axis_nbounds) float64 3.307e+09 ...
time_counter_bounds (time_counter, axis_nbounds) float64 3.307e+09 ...
NH4 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
Si (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
PHY2 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
PHY (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
MYRI (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
MICZ (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
DOC (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
POC (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
bSi (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
O2 (time_counter, deptht, y, x) float64 0.0 0.0 0.0 ...
In [21]:
ds.coords['nav_lat'].values
Out[21]:
array([[-0.5, -0.5, -0.5, -0.5, -0.5],
[ 0. , 0. , 0. , 0. , 0. ],
[ 0.5, 0.5, 0.5, 0.5, 0.5],
[ 1. , 1. , 1. , 1. , 1. ],
[ 1.5, 1.5, 1.5, 1.5, 1.5]], dtype=float32)
In [16]:
ds.attrs
Out[16]:
OrderedDict([('name', 'SS5x5_1h_20041019_20041023'),
('description', 'sog variables'),
('title', 'sog variables'),
('Conventions', 'CF-1.5'),
('production', 'An IPSL model'),
('timeStamp', '2016-May-09 10:52:56 PDT')])
In [10]:
Out[10]:
array([ 4. , 5.375 , 8.375 , ..., 133.1875, 8.25 , 7.625 ])
In [50]:
data_subset = ds.POC.values[:,:,2,2].T
fig, ax = plt.subplots(1, 1,figsize=(15,15))
mesh = ax.pcolormesh(data_subset)
fig.colorbar(mesh)
mesh.set_clim(vmin=data_subset.min(), vmax=data_subset.max())
In [46]:
data_subset.max()
Out[46]:
1.0276473760604858