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import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import add_metpy_logo, Hodograph, SkewT
from metpy.units import units
class Skewt:
def __init__(self, p, T, Td, title=None):
self._p = p
self._T = T
self._Td = Td
# Create a new figure. The dimensions here give a good aspect ratio
self._fig = plt.figure(figsize=(9, 9))
plt.rcParams["font.family"] = "monospace"
#self._fig = plt.figure()
if title is not None:
plt.suptitle(title, x=0, y=0, va='bottom', ha='left')
# Grid for plots
self._gs = gridspec.GridSpec(3, 3)
self._skew = SkewT(self._fig, rotation=45, subplot=self._gs[:, :2])
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
self._skew.plot(p, T, 'r')
self._skew.plot(p, Td, 'b')
plt.xlabel('$T$ $[^o C]$')
plt.ylabel('$p$ $[hPa]$')
def addWindUV(self, u, v):
self._u = u
self._v = v
ax = self._fig.add_subplot(self._gs[0, -1])
h = Hodograph(ax, component_range=max(u + v).magnitude)
h.add_grid(increment=20)
h.plot_colormapped(u, v, self._p)
plt.tight_layout()
plt.xlabel('$m/s$')
plt.ylabel('$m/s$')
self._skew.plot_barbs(self._p, u, v)
def addInfo(self, lines):
# TODO
ax = self._fig.add_subplot(self._gs[1,-1])
ax.text(0, 0, lines, ha='left', va='center', size=12)
ax.axis("off")
def plot(self, filename=None):
# Add the relevant special lines
#self._skew.ax.set_ylim(max(self._p), min(self._p))
self._skew.ax.set_ylim(1000, 100)
self._skew.plot_dry_adiabats()
self._skew.plot_moist_adiabats()
self._skew.plot_mixing_lines()
# Good bounds for aspect ratio
self._skew.ax.set_xlim(-30, 40)
if filename is not None:
plt.savefig(filename)
else:
plt.show()
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