Notebook

Test `surface_current_tiles` Module¶

Render figure object produced by the nowcast.figures.publish.surface_current_tiles module. Provides data for visual testing to confirm that refactoring has not adversely changed figure for web page.

Set-up and function call replicates as nearly as possible what is done in the nowcast.workers.make_surface_current_tiles worker.

Notebooks like this should be developed in a Nowcast Figures Development Environment so that all of the necessary dependency packages are installed. The development has to be done on a workstation that has the SalishSeaCast NEMO model results /results/ parition mounted.

In [1]:

from glob import glob
import io
import os
from pathlib import Path

import arrow
from matplotlib.backends.backend_agg import FigureCanvas
import yaml

from nowcast.figures.publish import surface_current_tiles
from nowcast.figures.surface_current_domain import tile_coords_dic

In [2]:

%matplotlib inline

The bits of config/nowcast.yaml that are required:

In [3]:

config = '''
    results archive:
        nowcast: /results/SalishSea/nowcast-blue.201806/
        forecast: /results/SalishSea/forecast.201806/
        
    figures:
        grid dir: /SalishSeaCast/grid/
        
    run types:
        forecast:
            coordinates: coordinates_seagrid_SalishSea201702.nc
            bathymetry: bathymetry_201702.nc
            mesh mask: mesh_mask201702.nc
'''

config = yaml.load(io.StringIO(config))

The bits that the make_surface_current_tiles worker must provide:

In [4]:

run_type = "forecast"
run_date = arrow.get("2019-02-22")

dmy = run_date.format("DDMMMYY").lower()
dmym1 = run_date.replace(days=-1).format("DDMMMYY").lower()

results_dir0 = Path(config["results archive"][run_type], dmy)
results_dirm1 = Path(config["results archive"]["nowcast"], dmy)
results_dirm2 = Path(config["results archive"]["nowcast"], dmym1)

grid_dir = Path(config["figures"]["grid dir"])
coordf = grid_dir / config["run types"][run_type]["coordinates"]
mesh_maskf = grid_dir / config["run types"][run_type]["mesh mask"]
bathyf = grid_dir / config["run types"][run_type]["bathymetry"]

for results_dir in [results_dirm2, results_dirm1, results_dir0]:

    u_list = glob(os.fspath(results_dir) + "/SalishSea_1h_*_grid_U.nc")
    v_list = glob(os.fspath(results_dir) + "/SalishSea_1h_*_grid_V.nc")

    Uf = Path(u_list[0])
    Vf = Path(v_list[0])

In [5]:

from importlib import reload
reload(surface_current_tiles)

t_index = 0
expansion_factor = 0.1  # 10% overlap for each tile

fig_list, tile_names = surface_current_tiles.make_figure(
    run_date,
    t_index,
    Uf,
    Vf,
    coordf,
    mesh_maskf,
    bathyf,
    tile_coords_dic,
    expansion_factor,
)
canvas = FigureCanvas(fig_list[9])
fig_list[9]

/media/doug/warehouse/conda_envs/nowcast-fig-dev-mpl-3/lib/python3.6/site-packages/matplotlib/contour.py:1243: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/media/doug/warehouse/conda_envs/nowcast-fig-dev-mpl-3/lib/python3.6/site-packages/numpy/core/fromnumeric.py:688: UserWarning: Warning: 'partition' will ignore the 'mask' of the MaskedArray.
  a.partition(kth, axis=axis, kind=kind, order=order)

Out[5]:

In [ ]:

Test surface_current_tiles Module¶

Test `surface_current_tiles` Module¶