def curvelinear_test1(fig):
"""
grid for custom transform.
"""
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y - x
def inv_tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y + x
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
# ax1 will have a ticks and gridlines defined by the given
# transform (+ transData of the Axes). Note that the transform of
# the Axes itself (i.e., transData) is not affected by the given
# transform.
fig.add_subplot(ax1)
xx, yy = tr([3, 6], [5.0, 10.])
ax1.plot(xx, yy, linewidth=2.0)
ax1.set_aspect(1.)
ax1.set_xlim(0, 10.)
ax1.set_ylim(0, 10.)
ax1.axis["t"] = ax1.new_floating_axis(0, 3.)
ax1.axis["t2"] = ax1.new_floating_axis(1, 7.)
ax1.grid(True, zorder=0)
def __spacetime_diagram_o_frame(self):
# from (x',t') to (x,t)
def tr(x_prime, t_prime):
x_prime, t_prime = np.asarray(x_prime), np.asarray(t_prime)
return self.lorentz_transformations.transform(
x_prime, t_prime, -self.velocity)
# form (x,t) to (x',t')
def inv_tr(x, t):
x, t = np.asarray(x), np.asarray(t)
return self.lorentz_transformations.transform(x, t, self.velocity)
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax = Subplot(self.fig, 1, 2, 1, grid_helper=grid_helper) if self.showOPrime \
else Subplot(self.fig, 1, 1, 1, grid_helper=grid_helper)
self.fig.add_subplot(ax)
ax.set_xlabel("x", loc="center")
ax.set_ylabel("t", loc="center")
# O' x axis
ax.axis["x1"] = x1 = ax.new_floating_axis(1, 0)
x1.label.set_text("x'")
# O' t axis
ax.axis["t1"] = t1 = ax.new_floating_axis(0, 0)
t1.label.set_text("t'")
self.__add_x_and_y_axis(ax)
ax.format_coord = self.__format_coord_o_frame
self.__remove_ticks(ax, x1, t1)
self.world_lines_plotter.plot(plt, ax, self.velocity)
def curvelinear_test1(fig):
"""
grid for custom transform.
"""
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y - x
def inv_tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y + x
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
# ax1 will have a ticks and gridlines defined by the given
# transform (+ transData of the Axes). Note that the transform of
# the Axes itself (i.e., transData) is not affected by the given
# transform.
fig.add_subplot(ax1)
xx, yy = tr([3, 6], [5.0, 10.])
ax1.plot(xx, yy, linewidth=2.0)
ax1.set_aspect(1.)
ax1.set_xlim(0, 10.)
ax1.set_ylim(0, 10.)
ax1.axis["t"] = ax1.new_floating_axis(0, 3.)
ax1.axis["t2"] = ax1.new_floating_axis(1, 7.)
ax1.grid(True, zorder=0)
def plotCorrelation(tauArray,kappaMatrix,kappaLower=None,kappaUpper=None,CI=None,amplify=1):
"""Plots Pearson Correlation Coefficient K(t,tau) with rotated
axis to indicate absolute t, and relative time shift tau, between
two signals x(t),y(t).
Specified matrix has to be square with values -1 < p < +1
with corresponding time array giving the absolute time, t
of the centers of each correlated window."""
# defining tranformation for relative time shifts
def R(x, y):
x, y = asarray(x), asarray(y)
#return x,y
return (2*x - y)/2, (y + 2*x)/2
def Rt(x, y):
x, y = asarray(x), asarray(y)
#return x,y
return x + y, x - y
# create figure with rotated axes
fig = figure(figsize=(10, 10),frameon=False)
grid_locator = angle_helper.LocatorDMS(20)
grid_helper = GridHelperCurveLinear((R, Rt),
grid_locator1=grid_locator,
grid_locator2=grid_locator)
ax = Subplot(fig, 1, 1, 1, grid_helper=grid_helper)
fig.add_subplot(ax);ax.axis('off');
# copying over matrix
K = array(kappaMatrix)
# zero out correlations if confidence intervals overlap zero
if all(kappaLower != None) and all(kappaUpper != None) :
K[ (kappaLower<0) * (0<kappaUpper) ] = 0
# zero out statistically insignificant correlations
if all(CI != None) :
K[ abs(kappaMatrix) < CI ] = 0
# display pearson correlation matrix with +ive in red and -ive in blue
ax.imshow(K,cmap="RdBu_r",interpolation="none",origin="bottom",
extent = (tauArray[0],tauArray[-1],tauArray[0],tauArray[-1]),vmin=-1.0/amplify,vmax=1.0/amplify)
# display rotated axes time,t and time delay,tau
ax.axis["tau"] = tau = ax.new_floating_axis(0,0)
ax.axis["t"] = t = ax.new_floating_axis(1,0)
# setting axes options
ax.set_xlim(tauArray[0],tauArray[-1])
ax.set_ylim(tauArray[0],tauArray[-1])
ax.grid(which="both")
ax.set_aspect(1)
return fig
def curvelinear_test1(fig):
"""
grid for custom transform.
"""
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y-x
def inv_tr(x,y):
x, y = np.asarray(x), np.asarray(y)
return x, y+x
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
fig.add_subplot(ax1)
xx, yy = tr([3, 6], [5.0, 10.])
ax1.plot(xx, yy)
ax1.set_aspect(1.)
ax1.set_xlim(0, 10.)
ax1.set_ylim(0, 10.)
ax1.axis["t"]=ax1.new_floating_axis(0, 3.)
ax1.axis["t2"]=ax1.new_floating_axis(1, 7.)
ax1.grid(True)
def curvelinear_test1(fig):
"""
Grid for custom transform.
"""
def tr(x, y):
x, y = numpy.asarray(x), numpy.asarray(y)
return x, y - (2 * x) # return x + (5 * y), (7 * y) + (3 * x)
def inv_tr(x, y):
x, y = numpy.asarray(x), numpy.asarray(y)
return x, y + (2 * x)
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax1 = Subplot(fig, 1, 1, 1, grid_helper=grid_helper)
# ax1 will have a ticks and gridlines defined by the given
# transform (+ transData of the Axes). Note that the transform of
# the Axes itself (i.e., transData) is not affected by the given
# transform.
fig.add_subplot(ax1)
xx, yy = tr([0, 1], [0, 2])
ax1.plot(xx, yy, linewidth=2.0)
ax1.set_aspect(1)
ax1.set_xlim(-3, 3)
ax1.set_ylim(-3, 3)
ax1.axis["t"] = ax1.new_floating_axis(
0, 0
) # first argument appears to be slope, second argument appears to be starting point on vertical
ax1.axis["t2"] = ax1.new_floating_axis(1, 0)
ax1.axhline(y=0, color='r')
ax1.axvline(x=0, color='r')
ax1.grid(True, zorder=0)
from mpl_toolkits.axisartist import Subplot
from mpl_toolkits.axisartist.grid_helper_curvelinear import \
GridHelperCurveLinear
def tr(x, y): # source (data) to target (rectilinear plot) coordinates
x, y = numpy.asarray(x), numpy.asarray(y)
return x + 0.2 * y, y - x
def inv_tr(x, y):
x, y = numpy.asarray(x), numpy.asarray(y)
return x - 0.2 * y, y + x
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax6 = Subplot(fig, nrow, ncol, 6, grid_helper=grid_helper)
fig.add_subplot(ax6)
ax6.set_title('non-ortho axes')
xx, yy = tr([3, 6], [5.0, 10.])
ax6.plot(xx, yy)
ax6.set_aspect(1.)
ax6.set_xlim(0, 10.)
ax6.set_ylim(0, 10.)
ax6.axis["t"] = ax6.new_floating_axis(0, 3.)
ax6.axis["t2"] = ax6.new_floating_axis(1, 7.)
ax6.grid(True)
plt.show()
class Tephigram:
"""
Generate a tephigram of one or more pressure and temperature data sets.
"""
def __init__(
self,
figure=None,
isotherm_locator=None,
dry_adiabat_locator=None,
anchor=None,
):
"""
Initialise the tephigram transformation and plot axes.
Kwargs:
* figure:
An existing :class:`matplotlib.figure.Figure` instance for the
tephigram plot. If a figure is not provided, a new figure will
be created by default.
* isotherm_locator:
A :class:`tephi.Locator` instance or a numeric step size
for the isotherm lines.
* dry_adiabat_locator:
A :class:`tephi.Locator` instance or a numeric step size
for the dry adiabat lines.
* anchor:
A sequence of two pressure, temperature pairs specifying the extent
of the tephigram plot in terms of the bottom left hand corner and
the top right hand corner. Pressure data points must be in units of
mb or hPa, and temperature data points must be in units of degC.
For example:
.. plot::
:include-source:
import matplotlib.pyplot as plt
from numpy import column_stack
import os.path
import tephi
from tephi import Tephigram
dew_point = os.path.join(tephi.DATA_DIR, 'dews.txt')
dry_bulb = os.path.join(tephi.DATA_DIR, 'temps.txt')
dew_data, temp_data = tephi.loadtxt(dew_point, dry_bulb)
dews = column_stack((dew_data.pressure, dew_data.temperature))
temps = column_stack((temp_data.pressure, temp_data.temperature))
tpg = Tephigram()
tpg.plot(dews, label='Dew-point', color='blue', linewidth=2)
tpg.plot(temps, label='Dry-bulb', color='red', linewidth=2)
plt.show()
"""
if not figure:
# Create a default figure.
self.figure = plt.figure(0, figsize=(9, 9))
else:
self.figure = figure
# Configure the locators.
if isotherm_locator and not isinstance(isotherm_locator, Locator):
if not isinstance(isotherm_locator, numbers.Number):
raise ValueError("Invalid isotherm locator")
locator_isotherm = Locator(isotherm_locator)
else:
locator_isotherm = isotherm_locator
if dry_adiabat_locator and not isinstance(dry_adiabat_locator,
Locator):
if not isinstance(dry_adiabat_locator, numbers.Number):
raise ValueError("Invalid dry adiabat locator")
locator_theta = Locator(dry_adiabat_locator)
else:
locator_theta = dry_adiabat_locator
# Define the tephigram coordinate-system transformation.
self.tephi_transform = transforms.TephiTransform()
ghelper = GridHelperCurveLinear(
self.tephi_transform,
tick_formatter1=_FormatterIsotherm(),
grid_locator1=locator_isotherm,
tick_formatter2=_FormatterTheta(),
grid_locator2=locator_theta,
)
self.axes = Subplot(self.figure, 1, 1, 1, grid_helper=ghelper)
self.transform = self.tephi_transform + self.axes.transData
self.axes.axis["isotherm"] = self.axes.new_floating_axis(1, 0)
self.axes.axis["theta"] = self.axes.new_floating_axis(0, 0)
self.axes.axis["left"].get_helper().nth_coord_ticks = 0
self.axes.axis["left"].toggle(all=True)
self.axes.axis["bottom"].get_helper().nth_coord_ticks = 1
self.axes.axis["bottom"].toggle(all=True)
self.axes.axis["top"].get_helper().nth_coord_ticks = 0
self.axes.axis["top"].toggle(all=False)
self.axes.axis["right"].get_helper().nth_coord_ticks = 1
self.axes.axis["right"].toggle(all=True)
self.axes.gridlines.set_linestyle("solid")
self.figure.add_subplot(self.axes)
# Configure default axes.
axis = self.axes.axis["left"]
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va("baseline")
axis.major_ticklabels.set_rotation(135)
axis = self.axes.axis["right"]
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va("baseline")
axis.major_ticklabels.set_rotation(-135)
self.axes.axis["top"].major_ticklabels.set_fontsize(10)
axis = self.axes.axis["bottom"]
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_ha("left")
axis.major_ticklabels.set_va("top")
axis.major_ticklabels.set_rotation(-45)
# Isotherms: lines of constant temperature (degC).
axis = self.axes.axis["isotherm"]
axis.set_axis_direction("right")
axis.set_axislabel_direction("-")
axis.major_ticklabels.set_rotation(90)
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va("bottom")
axis.major_ticklabels.set_color("grey")
axis.major_ticklabels.set_visible(False) # turned-off
# Dry adiabats: lines of constant potential temperature (degC).
axis = self.axes.axis["theta"]
axis.set_axis_direction("right")
axis.set_axislabel_direction("+")
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va("bottom")
axis.major_ticklabels.set_color("grey")
axis.major_ticklabels.set_visible(False) # turned-off
axis.line.set_linewidth(3)
axis.line.set_linestyle("--")
# Lock down the aspect ratio.
self.axes.set_aspect(1.0)
self.axes.grid(True)
# Initialise the text formatter for the navigation status bar.
self.axes.format_coord = self._status_bar
# Factor in the tephigram transform.
ISOBAR_TEXT["transform"] = self.transform
WET_ADIABAT_TEXT["transform"] = self.transform
MIXING_RATIO_TEXT["transform"] = self.transform
# Create plot collections for the tephigram isopleths.
func = partial(
isopleths.isobar,
MIN_THETA,
MAX_THETA,
self.axes,
self.transform,
ISOBAR_LINE,
)
self._isobars = _PlotCollection(
self.axes,
ISOBAR_SPEC,
MAX_PRESSURE,
func,
ISOBAR_TEXT,
fixed=ISOBAR_FIXED,
minimum=MIN_PRESSURE,
)
func = partial(
isopleths.wet_adiabat,
MAX_PRESSURE,
MIN_TEMPERATURE,
self.axes,
self.transform,
WET_ADIABAT_LINE,
)
self._wet_adiabats = _PlotCollection(
self.axes,
WET_ADIABAT_SPEC,
MAX_WET_ADIABAT,
func,
WET_ADIABAT_TEXT,
fixed=WET_ADIABAT_FIXED,
minimum=MIN_WET_ADIABAT,
xfocus=True,
)
func = partial(
isopleths.mixing_ratio,
MIN_PRESSURE,
MAX_PRESSURE,
self.axes,
self.transform,
MIXING_RATIO_LINE,
)
self._mixing_ratios = _PlotCollection(
self.axes,
MIXING_RATIO_SPEC,
MIXING_RATIOS,
func,
MIXING_RATIO_TEXT,
fixed=MIXING_RATIO_FIXED,
)
# Initialise for the tephigram plot event handler.
plt.connect("motion_notify_event", _handler)
self.axes.tephigram = True
self.axes.tephigram_original_delta_xlim = DEFAULT_WIDTH
self.original_delta_xlim = DEFAULT_WIDTH
self.axes.tephigram_transform = self.tephi_transform
self.axes.tephigram_inverse = self.tephi_transform.inverted()
self.axes.tephigram_isopleths = [
self._isobars,
self._wet_adiabats,
self._mixing_ratios,
]
# The tephigram profiles.
self._profiles = []
self.axes.tephigram_profiles = self._profiles
# Center the plot around the anchor extent.
self._anchor = anchor
if self._anchor is not None:
self._anchor = np.asarray(anchor)
if (self._anchor.ndim != 2 or self._anchor.shape[-1] != 2
or len(self._anchor) != 2):
msg = ("Invalid anchor, expecting [(bottom-left-pressure, "
"bottom-left-temperature), (top-right-pressure, "
"top-right-temperature)]")
raise ValueError(msg)
(
(bottom_pressure, bottom_temp),
(top_pressure, top_temp),
) = self._anchor
if (bottom_pressure - top_pressure) < 0:
raise ValueError("Invalid anchor pressure range")
if (bottom_temp - top_temp) < 0:
raise ValueError("Invalid anchor temperature range")
self._anchor = isopleths.Profile(anchor, self.axes)
self._anchor.plot(visible=False)
xlim, ylim = self._calculate_extents()
self.axes.set_xlim(xlim)
self.axes.set_ylim(ylim)
def plot(self, data, **kwargs):
"""
Plot the environmental lapse rate profile of the pressure and
temperature data points.
The pressure and temperature data points are transformed into
potential temperature and temperature data points before plotting.
By default, the tephigram will automatically center the plot around
all profiles.
.. warning::
Pressure data points must be in units of mb or hPa, and temperature
data points must be in units of degC.
Args:
* data: pressure and temperature pair data points.
.. note::
All keyword arguments are passed through to
:func:`matplotlib.pyplot.plot`.
For example:
.. plot::
:include-source:
import matplotlib.pyplot as plt
from tephi import Tephigram
tpg = Tephigram()
data = [[1006, 26.4], [924, 20.3], [900, 19.8],
[850, 14.5], [800, 12.9], [755, 8.3]]
profile = tpg.plot(data, color='red', linestyle='--',
linewidth=2, marker='o')
barbs = [(10, 45, 900), (20, 60, 850), (25, 90, 800)]
profile.barbs(barbs)
plt.show()
For associating wind barbs with an environmental lapse rate profile,
see :meth:`~tephi.isopleths.Profile.barbs`.
"""
profile = isopleths.Profile(data, self.axes)
profile.plot(**kwargs)
self._profiles.append(profile)
# Center the tephigram plot around all the profiles.
if self._anchor is None:
xlim, ylim = self._calculate_extents(xfactor=0.25, yfactor=0.05)
self.axes.set_xlim(xlim)
self.axes.set_ylim(ylim)
# Refresh the tephigram plot isopleths.
_refresh_isopleths(self.axes)
# Show the plot legend.
if "label" in kwargs:
font_properties = FontProperties(size="x-small")
plt.legend(
loc="upper left",
fancybox=True,
shadow=True,
prop=font_properties,
)
return profile
def _status_bar(self, x_point, y_point):
"""Generate text for the interactive backend navigation status bar."""
temperature, theta = transforms.convert_xy2Tt(x_point, y_point)
pressure, _ = transforms.convert_Tt2pT(temperature, theta)
xlim = self.axes.get_xlim()
zoom = (xlim[1] - xlim[0]) / self.original_delta_xlim
msg = "T:{:.2f}, theta:{:.2f}, phi:{:.2f} (zoom:{:.3f})"
text = msg.format(float(temperature), float(theta), float(pressure),
zoom)
return text
def _calculate_extents(self, xfactor=None, yfactor=None):
min_x = min_y = 1e10
max_x = max_y = -1e-10
profiles = self._profiles
transform = self.tephi_transform.transform
if self._anchor is not None:
profiles = [self._anchor]
for profile in profiles:
temperature = profile.temperature.reshape(-1, 1)
theta = profile.theta.reshape(-1, 1)
xy_points = transform(np.concatenate((temperature, theta), axis=1))
x_points = xy_points[:, 0]
y_points = xy_points[:, 1]
min_x = np.min([min_x, np.min(x_points)])
min_y = np.min([min_y, np.min(y_points)])
max_x = np.max([max_x, np.max(x_points)])
max_y = np.max([max_y, np.max(y_points)])
if xfactor is not None:
delta_x = max_x - min_x
min_x, max_x = min_x - xfactor * delta_x, max_x + xfactor * delta_x
if yfactor is not None:
delta_y = max_y - min_y
min_y, max_y = min_y - yfactor * delta_y, max_y + yfactor * delta_y
return ([min_x, max_x], [min_y, max_y])
class Tephigram(object):
"""
Generate a tephigram of one or more pressure and temperature data sets.
"""
def __init__(self, figure=None, isotherm_locator=None,
dry_adiabat_locator=None, anchor=None):
"""
Initialise the tephigram transformation and plot axes.
Kwargs:
* figure:
An existing :class:`matplotlib.figure.Figure` instance for the
tephigram plot. If a figure is not provided, a new figure will
be created by default.
* isotherm_locator:
A :class:`edson.Locator` instance or a numeric step size
for the isotherm lines.
* dry_adiabat_locator:
A :class:`edson.Locator` instance or a numeric step size
for the dry adiabat lines.
* anchor:
A sequence of two pressure, temperature pairs specifying the extent
of the tephigram plot in terms of the bottom left hand corner and
the top right hand corner. Pressure data points must be in units of
mb or hPa, and temperature data points must be in units of degC.
For example:
.. plot::
:include-source:
import matplotlib.pyplot as plt
import os.path
import edson
from edson import Tephigram
dew_point = os.path.join(edson.RESOURCES_DIR, 'tephigram', 'dews.txt')
dry_bulb = os.path.join(edson.RESOURCES_DIR, 'tephigram', 'temps.txt')
dew_data, temp_data = edson.loadtxt(dew_point, dry_bulb)
dews = zip(dew_data.pressure, dew_data.temperature)
temps = zip(temp_data.pressure, temp_data.temperature)
tephi = Tephigram()
tephi.plot(dews, label='Dew-point', color='blue', linewidth=2, marker='s')
tephi.plot(temps, label='Dry-bulb', color='red', linewidth=2, marker='o')
plt.show()
"""
if not figure:
# Create a default figure.
self.figure = plt.figure(0, figsize=(9, 9))
else:
self.figure = figure
# Configure the locators.
if isotherm_locator and not isinstance(isotherm_locator, Locator):
if not isinstance(isotherm_locator, numbers.Number):
raise ValueError('Invalid isotherm locator')
locator_isotherm = Locator(isotherm_locator)
else:
locator_isotherm = isotherm_locator
if dry_adiabat_locator and not isinstance(dry_adiabat_locator, Locator):
if not isinstance(dry_adiabat_locator, numbers.Number):
raise ValueError('Invalid dry adiabat locator')
locator_theta = Locator(dry_adiabat_locator)
else:
locator_theta = dry_adiabat_locator
# Define the tephigram coordinate-system transformation.
self.tephi_transform = transforms.TephiTransform()
grid_helper1 = GridHelperCurveLinear(self.tephi_transform,
tick_formatter1=_FormatterIsotherm(),
grid_locator1=locator_isotherm,
tick_formatter2=_FormatterTheta(),
grid_locator2=locator_theta)
self.axes = Subplot(self.figure, 1, 1, 1, grid_helper=grid_helper1)
self.transform = self.tephi_transform + self.axes.transData
self.axes.axis['isotherm'] = self.axes.new_floating_axis(1, 0)
self.axes.axis['theta'] = self.axes.new_floating_axis(0, 0)
self.axes.axis['left'].get_helper().nth_coord_ticks = 0
self.axes.axis['left'].toggle(all=True)
self.axes.axis['bottom'].get_helper().nth_coord_ticks = 1
self.axes.axis['bottom'].toggle(all=True)
self.axes.axis['top'].get_helper().nth_coord_ticks = 0
self.axes.axis['top'].toggle(all=False)
self.axes.axis['right'].get_helper().nth_coord_ticks = 1
self.axes.axis['right'].toggle(all=True)
self.axes.gridlines.set_linestyle('solid')
self.figure.add_subplot(self.axes)
# Configure default axes.
axis = self.axes.axis['left']
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va('baseline')
axis.major_ticklabels.set_rotation(135)
axis = self.axes.axis['right']
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va('baseline')
axis.major_ticklabels.set_rotation(-135)
self.axes.axis['top'].major_ticklabels.set_fontsize(10)
axis = self.axes.axis['bottom']
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_ha('left')
axis.major_ticklabels.set_va('top')
axis.major_ticklabels.set_rotation(-45)
# Isotherms: lines of constant temperature (degC).
axis = self.axes.axis['isotherm']
axis.set_axis_direction('right')
axis.set_axislabel_direction('-')
axis.major_ticklabels.set_rotation(90)
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va('bottom')
axis.major_ticklabels.set_color('grey')
axis.major_ticklabels.set_visible(False) # turned-off
# Dry adiabats: lines of constant potential temperature (degC).
axis = self.axes.axis['theta']
axis.set_axis_direction('right')
axis.set_axislabel_direction('+')
axis.major_ticklabels.set_fontsize(10)
axis.major_ticklabels.set_va('bottom')
axis.major_ticklabels.set_color('grey')
axis.major_ticklabels.set_visible(False) # turned-off
axis.line.set_linewidth(3)
axis.line.set_linestyle('--')
# Lock down the aspect ratio.
self.axes.set_aspect(1.)
self.axes.grid(True)
# Initialise the text formatter for the navigation status bar.
self.axes.format_coord = self._status_bar
# Factor in the tephigram transform.
ISOBAR_TEXT['transform'] = self.transform
WET_ADIABAT_TEXT['transform'] = self.transform
MIXING_RATIO_TEXT['transform'] = self.transform
# Create plot collections for the tephigram isopleths.
func = partial(isopleths.isobar, MIN_THETA, MAX_THETA, self.axes, self.transform, ISOBAR_LINE)
self._isobars = _PlotCollection(self.axes, ISOBAR_SPEC, MAX_PRESSURE, func, ISOBAR_TEXT,
fixed=ISOBAR_FIXED, minimum=MIN_PRESSURE)
func = partial(isopleths.wet_adiabat, MAX_PRESSURE, MIN_TEMPERATURE, self.axes, self.transform, WET_ADIABAT_LINE)
self._wet_adiabats = _PlotCollection(self.axes, WET_ADIABAT_SPEC, MAX_WET_ADIABAT, func, WET_ADIABAT_TEXT,
fixed=WET_ADIABAT_FIXED, minimum=MIN_WET_ADIABAT, xfocus=True)
func = partial(isopleths.mixing_ratio, MIN_PRESSURE, MAX_PRESSURE, self.axes, self.transform, MIXING_RATIO_LINE)
self._mixing_ratios = _PlotCollection(self.axes, MIXING_RATIO_SPEC, MIXING_RATIOS, func, MIXING_RATIO_TEXT,
fixed=MIXING_RATIO_FIXED)
# Initialise for the tephigram plot event handler.
plt.connect('motion_notify_event', _handler)
self.axes.tephigram = True
self.axes.tephigram_original_delta_xlim = self.original_delta_xlim = DEFAULT_WIDTH
self.axes.tephigram_transform = self.tephi_transform
self.axes.tephigram_inverse = self.tephi_transform.inverted()
self.axes.tephigram_isopleths = [self._isobars, self._wet_adiabats, self._mixing_ratios]
# The tephigram profiles.
self._profiles = []
self.axes.tephigram_profiles = self._profiles
# Center the plot around the anchor extent.
self._anchor = anchor
if self._anchor is not None:
self._anchor = np.asarray(anchor)
if self._anchor.ndim != 2 or self._anchor.shape[-1] != 2 or \
len(self._anchor) != 2:
msg = 'Invalid anchor, expecting [(bottom-left-pressure, ' \
'bottom-left-temperature), (top-right-pressure, ' \
'top-right-temperature)]'
raise ValueError(msg)
(bottom_pressure, bottom_temp), \
(top_pressure, top_temp) = self._anchor
if (bottom_pressure - top_pressure) < 0:
raise ValueError('Invalid anchor pressure range')
if (bottom_temp - top_temp) < 0:
raise ValueError('Invalid anchor temperature range')
self._anchor = isopleths.Profile(anchor, self.axes)
self._anchor.plot(visible=False)
xlim, ylim = self._calculate_extents()
self.axes.set_xlim(xlim)
self.axes.set_ylim(ylim)
def plot(self, data, **kwargs):
"""
Plot the environmental lapse rate profile of the pressure and
temperature data points.
The pressure and temperature data points are transformed into
potential temperature and temperature data points before plotting.
By default, the tephigram will automatically center the plot around
all profiles.
.. warning::
Pressure data points must be in units of mb or hPa, and temperature
data points must be in units of degC.
Args:
* data: pressure and temperature pair data points.
.. note::
All keyword arguments are passed through to
:func:`matplotlib.pyplot.plot`.
For example:
.. plot::
:include-source:
import matplotlib.pyplot as plt
from edson import Tephigram
tephi = Tephigram()
data = [[1006, 26.4], [924, 20.3], [900, 19.8],
[850, 14.5], [800, 12.9], [755, 8.3]]
profile = tephi.plot(data, color='red', linestyle='--',
linewidth=2, marker='o')
barbs = [(10, 45, 900), (20, 60, 850), (25, 90, 800)]
profile.barbs(barbs)
plt.show()
For associating wind barbs with an environmental lapse rate profile,
see :meth:`~edson.isopleths.Profile.barbs`.
"""
profile = isopleths.Profile(data, self.axes)
profile.plot(**kwargs)
self._profiles.append(profile)
# Center the tephigram plot around all the profiles.
if self._anchor is None:
xlim, ylim = self._calculate_extents(xfactor=.25, yfactor=.05)
self.axes.set_xlim(xlim)
self.axes.set_ylim(ylim)
# Refresh the tephigram plot isopleths.
_refresh_isopleths(self.axes)
# Show the plot legend.
if 'label' in kwargs:
font_properties = FontProperties(size='x-small')
plt.legend(loc='upper left', fancybox=True, shadow=True, prop=font_properties)
return profile
def _status_bar(self, x_point, y_point):
"""Generate text for the interactive backend navigation status bar."""
temperature, theta = transforms.xy_to_temperature_theta(x_point, y_point)
pressure, _ = transforms.temperature_theta_to_pressure_temperature(temperature, theta)
xlim = self.axes.get_xlim()
zoom = (xlim[1] - xlim[0]) / self.original_delta_xlim
text = "T:%.2f, theta:%.2f, phi:%.2f (zoom:%.3f)" % (float(temperature), float(theta), float(pressure), zoom)
return text
def _calculate_extents(self, xfactor=None, yfactor=None):
min_x = min_y = 1e10
max_x = max_y = -1e-10
profiles = self._profiles
if self._anchor is not None:
profiles = [self._anchor]
for profile in profiles:
xy_points = self.tephi_transform.transform(np.concatenate((profile.temperature.reshape(-1, 1),
profile.theta.reshape(-1, 1)),
axis=1))
x_points = xy_points[:, 0]
y_points = xy_points[:, 1]
min_x, min_y = np.min([min_x, np.min(x_points)]), np.min([min_y, np.min(y_points)])
max_x, max_y = np.max([max_x, np.max(x_points)]), np.max([max_y, np.max(y_points)])
if xfactor is not None:
delta_x = max_x - min_x
min_x, max_x = min_x - xfactor * delta_x, max_x + xfactor * delta_x
if yfactor is not None:
delta_y = max_y - min_y
min_y, max_y = min_y - yfactor * delta_y, max_y + yfactor * delta_y
return ([min_x, max_x], [min_y, max_y])
