def plotter(fdict):
""" Go """
ctx = get_autoplot_context(fdict, get_description())
if ctx["sz"] < 5:
ctx["sz"] = 5
if ctx["hours"] > 300:
ctx["hours"] = 300
endts = ctx["endts"]
basets = endts - datetime.timedelta(hours=ctx["hours"])
# Retrieve available obs
df = load_data(ctx, basets, endts)
# figure out our grid bounds
ctx["bnds2163"] = compute_grid_bounds(ctx)
# add zeros and QC
df = add_zeros(df, ctx)
# do gridding
df2 = df[df[USEME]]
lons, lats, vals = do_analysis(df2, ctx)
rng = [0.01, 1, 2, 3, 4, 6, 8, 12, 18, 24, 30, 36]
cmap = nwssnow()
if ctx["t"] == "cwa":
sector = "cwa"
else:
sector = "state" if len(ctx["csector"]) == 2 else ctx["csector"]
mp = MapPlot(
sector=sector,
state=ctx["csector"],
cwa=(ctx["wfo"] if len(ctx["wfo"]) == 3 else ctx["wfo"][1:]),
axisbg="white",
title=("NWS Local Storm Report%s Snowfall Total Analysis") %
(" & COOP" if ctx["coop"] == "yes" else "", ),
subtitle=("%.0f reports over past %.0f hours till %s, "
"grid size: %.0fkm, Rbf: %s"
"" % (
len(df2.index),
ctx["hours"],
endts.strftime("%d %b %Y %I:%M %p"),
ctx["sz"],
ctx["f"],
)),
)
if df2["val"].max() > 0 and ctx["p"] in ["both", "contour"]:
mp.contourf(lons,
lats,
vals,
rng,
cmap=cmap,
clip_on=(ctx["t"] != "cwa"))
# Allow analysis to bleed outside the CWA per request.
if ctx["t"] == "cwa":
mp.draw_mask(sector="conus")
mp.draw_cwas(linewidth=2)
mp.drawcounties()
if not df.empty and ctx["p"] in ["both", "plot"]:
df2 = df[df["plotme"]]
mp.plot_values(
df2["lon"].values,
df2["lat"].values,
df2["val"].values,
fmt="%.1f",
labelbuffer=2,
)
if ctx["z"] == "plot":
df2 = df[df["state"] == "Z"]
if not df2.empty:
mp.plot_values(
df2["lon"].values,
df2["lat"].values,
df2["state"].values,
fmt="%s",
color="#FF0000",
labelbuffer=0,
)
mp.drawcities()
return mp.fig, df.drop(["geo", "plotme"], axis=1)
