def testClosestValAbove(self):
val = util.closest_val(20., self.array)
assert val == 2
def testClosestValInternalNegative(self):
val = util.closest_val(-3.5, -1 * self.array)
assert val == 1
def testClosestValInternal(self):
val = util.closest_val(3.5, self.array)
assert val == 1
def testClosestValBelow(self):
val = util.closest_val(-5., self.array)
assert val == 0
def testValueErrorOnEmptyArray(self):
util.closest_val(1., np.array([]))
def testClosestValSingle(self):
val = util.closest_val(1., np.array([50.]))
assert val == 0
def testValueErrorOnEmptyList(self):
util.closest_val(1., [])
def testClosestValAboveList(self):
val = util.closest_val(20., self.list)
assert val == 2
def testClosestValBelowList(self):
val = util.closest_val(-5., self.list)
assert val == 0
def testClosestValInternalList(self):
val = util.closest_val(3.5, self.list)
assert val == 1
def plot_moist_adiabats(self, p=None, thetaes=None, **kwargs):
r'''Plot moist adiabats.
Adds saturated pseudo-adiabats (lines of constant equivalent potential
temperature) to the plot. The default style of these lines is dashed
blue lines with an alpha value of 0.5. These can be overridden using
keyword arguments.
Parameters
----------
p : array_like, optional
1-dimensional array of pressure values to be included in the moist
adiabats. If not specified, they will be linearly distributed
across the current plotted pressure range.
thetaes : array_like, optional
1-dimensional array of saturation equivalent potential temperature
values for moist adiabats. By default these will be generated based
on the current temperature limits.
kwargs
Other keyword arguments to pass to
`matplotlib.collections.LineCollection`
See Also
--------
plot_dry_adiabats
`matplotlib.collections.LineCollection`
`metpy.calc.moist_lapse`
'''
for artist in self._moist_adiabats:
artist.remove()
self._moist_adiabats = []
thetaes = thetaes # port workaround, can refactor at any time
def dT_dp(y, p0):
return calculate(
'Gammam', T=y, p=p0, RH=100., p_units='hPa',
T_units='degC') / (g0 * calculate(
'rho', T=y, p=p0, p_units='hPa', T_units='degC',
RH=100.)) * 100.
if thetaes is None and p is None:
if (self.get_xlim() == self.default_xlim
and self.get_ylim() == self.default_ylim):
data = np.load(
resource_filename(__name__,
'data/default_moist_adiabat_data.npz'))
p = data['p']
thetaes = data['t0']
t = data['t']
else:
# Determine set of starting temps if necessary
if thetaes is None:
xmin, xmax = self.get_xlim()
thetaes = np.concatenate(
(np.arange(xmin, 0, 5), np.arange(0, xmax + 51, 5)))
# Get pressure levels based on ylims if necessary
if p is None:
p = np.linspace(*self.get_ylim())
thetaes_base = odeint(dT_dp, thetaes,
np.array([1e3, p[0]],
dtype=np.float64))[-1, :]
# Assemble into data for plotting
result = odeint(dT_dp, thetaes_base, p)
t = result.T
linedata = [np.vstack((ti, p)).T for ti in t]
# Add to plot
kwargs.setdefault('colors', '#166916')
kwargs.setdefault('linestyles', '-')
kwargs.setdefault('alpha', 1)
kwargs.setdefault('linewidth', 0.5)
kwargs.setdefault('zorder', 1.1)
collection = LineCollection(linedata, **kwargs)
self._moist_adiabats.append(collection)
self.add_collection(collection)
label_index = closest_val(240., p)
T_label = t[:, label_index].flatten()
for i in range(len(thetaes)):
t = self.text(T_label[i],
p[label_index],
'{:.0f}'.format(thetaes[i]),
fontsize=8,
ha='left',
va='center',
rotation=-65,
color='#166916',
bbox={
'facecolor': 'w',
'edgecolor': 'w',
'alpha': 0,
},
zorder=1.2)
t.set_clip_on(True)
self._moist_adiabats.append(t)
