def plot_agency_magnitude_pair(data, overlay=False, xlim=[], ylim=[],
marker="o", figure_size=(7, 8), filetype="png", resolution=300,
filename=None):
"""
Plots the agency magnitude pair
:param dict data:
Query result for a particular joint agency-magnitude pair combination
:param bool overlay:
Allows another layer to be rendered on top (True) or closes the figure
for plotting (False)
:param list xlim:
Lower and upper bounds for x-axis
:param list ylim:
Lower and upper bounds for y-axis
"""
if not data:
print "No pairs found - abandoning plot!"
return
fig = plt.figure(figsize=figure_size)
keys = data.keys()
plt.errorbar(data[keys[0]], data[keys[2]],
xerr=data[keys[1]], yerr=data[keys[3]],
marker=marker, mfc="b", mec="k", ls="None",
ecolor="r")
plt.xlabel(utils._to_latex(keys[0]), fontsize=16)
plt.ylabel(utils._to_latex(keys[2]), fontsize=16)
plt.grid(True)
if len(xlim) == 2:
lowx = xlim[0]
highx = xlim[1]
else:
lowx = np.floor(np.min(data[keys[0]]))
highx = np.ceil(np.max(data[keys[0]]))
if len(ylim) == 2:
lowy = ylim[0]
highy = ylim[1]
else:
lowy = np.floor(np.min(data[keys[2]]))
highy = np.ceil(np.max(data[keys[2]]))
if lowy < lowx:
lowx = lowy
if highy > highx:
highx = highy
plt.ylim(lowx, highx)
plt.xlim(lowx, highx)
# Overlay 1:1 line
plt.plot(np.array([lowx, highx]), np.array([lowx, highx]), ls="--",
color=[0.5, 0.5, 0.5], zorder=1)
plt.tight_layout()
if filename:
utils._save_image(filename, filetype, resolution)
if not overlay:
plt.show()
return data
def get_string(self, output_string, input_string):
"""
Returns the title string
"""
base_string = "{:s} = ".format(_to_latex(output_string))
for iloc, param in enumerate(self.params):
if iloc == 0:
base_string = base_string + "{:.3f}".format(param)
elif iloc == 1:
base_string = base_string + " {:s}{:s}".format(
_set_string(param), _to_latex(input_string))
else:
base_string = base_string + (
" %s%s$^%d$" %
(_set_string(param), _to_latex(input_string), iloc))
return base_string
def get_string(self, output_string, input_string):
"""
Returns the title string
"""
base_string = "%s = e$^{(%.3f %s %s)}$ %s" % (
_to_latex(output_string), self.params[0],
_set_string(self.params[1]), self._to_latex(input_string),
_set_string(self.params[2]))
return base_string
def get_string(self, output_string, input_string):
"""
Returns the title string
"""
base_string = "{:s} = ".format(_to_latex(output_string))
# Equation 1
upper_string = base_string +\
"{:.3f} {:s}{:s} for {:s} < {:.2f}".format(
self.params[0][1],
_set_string(self.params[0][0]),
_to_latex(input_string),
_to_latex(input_string),
self.corner_magnitude)
lower_string = base_string +\
"{:.3f} {:s}{:s} for {:s} $\geq$ {:.2f}".format(
self.params[1][1],
_set_string(self.params[1][0]),
_to_latex(input_string),
_to_latex(input_string),
self.corner_magnitude)
return "\n".join([upper_string, lower_string])
def get_string(self, output_string, input_string):
"""
Returns the title string
"""
n_seg = len(self.params)
full_string = []
for iloc, params in enumerate(self.params):
eq_string = "{:s} = {:.3f} {:s} {:s}".format(
_to_latex(output_string), params[0], _set_string(params[1]),
_to_latex(input_string))
if iloc == 0:
cond_string = eq_string + " for {:s} < {:.3f}".format(
_to_latex(input_string), params[2])
elif iloc == (n_seg - 1):
cond_string = eq_string + " for {:s} $\geq$ {:.3f}".format(
_to_latex(input_string), params[2])
else:
cond_string = eq_string +\
" for {:.3f} $\leq$ {:s} < {:.3f}".format(
self.params[iloc - 1][2],
_to_latex(input_string),
params[2])
full_string.append(cond_string)
return "\n".join([case_string for case_string in full_string])
def plot_agency_magnitude_density(data, overlay=False, number_samples=0,
xlim=[], ylim=[], figure_size=(7, 8), lognorm=True,
filetype="png", resolution=300, filename=None):
"""
"""
keys = data.keys()
if not data:
print "No pairs found - abandoning plot!"
return
if len(xlim) == 2:
lowx = xlim[0]
highx = xlim[1]
else:
lowx = np.floor(np.min(data[keys[0]]))
highx = np.ceil(np.max(data[keys[0]]))
if len(ylim) == 2:
lowy = ylim[0]
highy = ylim[1]
else:
lowy = np.floor(np.min(data[keys[2]]))
highy = np.ceil(np.max(data[keys[2]]))
if lowy < lowx:
lowx = lowy
if highy > highx:
highx = highy
xbins = np.linspace(lowx - 0.05, highx + 0.05,
((highx + 0.05 - lowx - 0.05) / 0.1) + 2.0)
ybins = np.linspace(lowx - 0.05, highx + 0.05,
((highx + 0.05 - lowx - 0.05) / 0.1) + 2.0)
density = sample_agency_magnitude_pairs(data, xbins, ybins, number_samples)
fig = plt.figure(figsize=figure_size)
if lognorm:
cmap = deepcopy(matplotlib.cm.get_cmap("jet"))
data_norm = LogNorm(vmin=0.1, vmax=np.max(density))
else:
cmap = deepcopy(matplotlib.cm.get_cmap("jet"))
cmap.set_under("w")
data_norm = Normalize(vmin=0.1, vmax=np.max(density))
#density[density < 1E-15] == np.nan
plt.pcolormesh(xbins[:-1] + 0.05, ybins[:-1] + 0.05, density.T,
norm=data_norm, cmap=cmap)
cbar = plt.colorbar()
cbar.set_label("Number Events", fontsize=16)
plt.xlabel(utils._to_latex(keys[0]), fontsize=16)
plt.ylabel(utils._to_latex(keys[2]), fontsize=16)
plt.grid(True)
plt.ylim(lowx, highx)
plt.xlim(lowx, highx)
# Overlay 1:1 line
plt.plot(np.array([lowx, highx]), np.array([lowx, highx]), ls="--",
color=[0.5, 0.5, 0.5], zorder=1)
plt.tight_layout()
if filename:
utils._save_image(filename, filetype, resolution)
if not overlay:
plt.show()
return data
def plot_agency_magnitude_density(data,
overlay=False,
number_samples=0,
xlim=[],
ylim=[],
figure_size=(7, 8),
lognorm=True,
filetype="png",
resolution=300,
filename=None):
"""
"""
keys = data.keys()
if not data:
print "No pairs found - abandoning plot!"
return
if len(xlim) == 2:
lowx = xlim[0]
highx = xlim[1]
else:
lowx = np.floor(np.min(data[keys[0]]))
highx = np.ceil(np.max(data[keys[0]]))
if len(ylim) == 2:
lowy = ylim[0]
highy = ylim[1]
else:
lowy = np.floor(np.min(data[keys[2]]))
highy = np.ceil(np.max(data[keys[2]]))
if lowy < lowx:
lowx = lowy
if highy > highx:
highx = highy
xbins = np.linspace(lowx - 0.05, highx + 0.05,
((highx + 0.05 - lowx - 0.05) / 0.1) + 2.0)
ybins = np.linspace(lowx - 0.05, highx + 0.05,
((highx + 0.05 - lowx - 0.05) / 0.1) + 2.0)
density = sample_agency_magnitude_pairs(data, xbins, ybins, number_samples)
fig = plt.figure(figsize=figure_size)
if lognorm:
cmap = deepcopy(matplotlib.cm.get_cmap("jet"))
data_norm = LogNorm(vmin=0.1, vmax=np.max(density))
else:
cmap = deepcopy(matplotlib.cm.get_cmap("jet"))
cmap.set_under("w")
data_norm = Normalize(vmin=0.1, vmax=np.max(density))
#density[density < 1E-15] == np.nan
plt.pcolormesh(xbins[:-1] + 0.05,
ybins[:-1] + 0.05,
density.T,
norm=data_norm,
cmap=cmap)
cbar = plt.colorbar()
cbar.set_label("Number Events", fontsize=16)
plt.xlabel(utils._to_latex(keys[0]), fontsize=16)
plt.ylabel(utils._to_latex(keys[2]), fontsize=16)
plt.grid(True)
plt.ylim(lowx, highx)
plt.xlim(lowx, highx)
# Overlay 1:1 line
plt.plot(np.array([lowx, highx]),
np.array([lowx, highx]),
ls="--",
color=[0.5, 0.5, 0.5],
zorder=1)
plt.tight_layout()
if filename:
utils._save_image(filename, filetype, resolution)
if not overlay:
plt.show()
return data
def plot_agency_magnitude_pair(data,
overlay=False,
xlim=[],
ylim=[],
marker="o",
figure_size=(7, 8),
filetype="png",
resolution=300,
filename=None):
"""
Plots the agency magnitude pair
:param dict data:
Query result for a particular joint agency-magnitude pair combination
:param bool overlay:
Allows another layer to be rendered on top (True) or closes the figure
for plotting (False)
:param list xlim:
Lower and upper bounds for x-axis
:param list ylim:
Lower and upper bounds for y-axis
"""
if not data:
print "No pairs found - abandoning plot!"
return
fig = plt.figure(figsize=figure_size)
keys = data.keys()
plt.errorbar(data[keys[0]],
data[keys[2]],
xerr=data[keys[1]],
yerr=data[keys[3]],
marker=marker,
mfc="b",
mec="k",
ls="None",
ecolor="r")
plt.xlabel(utils._to_latex(keys[0]), fontsize=16)
plt.ylabel(utils._to_latex(keys[2]), fontsize=16)
plt.grid(True)
if len(xlim) == 2:
lowx = xlim[0]
highx = xlim[1]
else:
lowx = np.floor(np.min(data[keys[0]]))
highx = np.ceil(np.max(data[keys[0]]))
if len(ylim) == 2:
lowy = ylim[0]
highy = ylim[1]
else:
lowy = np.floor(np.min(data[keys[2]]))
highy = np.ceil(np.max(data[keys[2]]))
if lowy < lowx:
lowx = lowy
if highy > highx:
highx = highy
plt.ylim(lowx, highx)
plt.xlim(lowx, highx)
# Overlay 1:1 line
plt.plot(np.array([lowx, highx]),
np.array([lowx, highx]),
ls="--",
color=[0.5, 0.5, 0.5],
zorder=1)
plt.tight_layout()
if filename:
utils._save_image(filename, filetype, resolution)
if not overlay:
plt.show()
return data
