class ArrayPlotter:
"""
Simple plotter for drawing array level items
"""
def __init__(self, instrument, telescopes=None, system=None, ax=None):
"""
Parameters
----------
instrument: dictionary
intrument containers for this event
telescopes: list
List of telescopes included
system: Coordinate system
Coordinate system to transform coordinates into
"""
self.instrument = instrument
self.system = system
if telescopes is None:
self.telescopes = instrument.telescope_ids
else:
self.telescopes = telescopes
type_dict = {
28.0: 1,
16.0: 2,
2.1500000953674316: 3,
2.2829999923706055: 4,
5.599999904632568: 5
}
tel_x = [
self.instrument.tel_pos[i][0].to(u.m).value
for i in self.telescopes
]
tel_y = [
self.instrument.tel_pos[i][1].to(u.m).value
for i in self.telescopes
]
tel_z = [
self.instrument.tel_pos[i][2].to(u.m).value
for i in self.telescopes
]
self.axes = ax if ax is not None else plt.gca()
tel_type = np.asarray([
type_dict[self.instrument.optical_foclen[i].to(u.m).value]
for i in self.telescopes
])
self.tel_type = tel_type
if system is not None:
ground = GroundFrame(x=np.asarray(tel_x) * u.m,
y=np.asarray(tel_y) * u.m,
z=np.asarray(tel_z) * u.m)
new_sys = ground.transform_to(system)
self.tel_x = new_sys.x
self.tel_y = new_sys.y
else:
self.tel_x = tel_x * u.m
self.tel_y = tel_y * u.m
self.centre = (0, 0)
self.array = ArrayDisplay(telx=np.asarray(self.tel_x),
tely=np.asarray(self.tel_y),
tel_type=tel_type,
axes=self.axes)
self.hillas = None
def overlay_hillas(self,
hillas,
scale_fac=10000,
draw_axes=False,
**kwargs):
"""
Overlay hillas parameters on top of the array map
Parameters
----------
hillas: dictionary
Hillas moments objects to overlay
scale_fac: float
Scaling factor to array to hillas width and length when drawing
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
tel_x = [self.instrument.tel_pos[i][0].to(u.m).value for i in hillas]
tel_y = [self.instrument.tel_pos[i][1].to(u.m).value for i in hillas]
tel_z = [self.instrument.tel_pos[i][2].to(u.m).value for i in hillas]
if self.system is not None:
ground = GroundFrame(x=np.asarray(tel_x) * u.m,
y=np.asarray(tel_y) * u.m,
z=np.asarray(tel_z) * u.m)
new_sys = ground.transform_to(self.system)
self.array.overlay_moments(hillas, (new_sys.x, new_sys.y),
scale_fac,
cmap="Greys",
alpha=0.5,
**kwargs)
if draw_axes:
self.array.overlay_axis(hillas, (new_sys.x, new_sys.y))
else:
self.array.overlay_moments(hillas, (tel_x, tel_y),
scale_fac,
alpha=0.5,
cmap="Greys",
**kwargs)
self.hillas = hillas
def background_contour(self, x, y, background, **kwargs):
"""
Draw image contours in background of the display, useful when likelihood fitting
Parameters
----------
x: ndarray
array of image X coordinates
y: ndarray
array of image Y coordinates
background: ndarray
Array of image to use in background
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
self.axes.contour(x, y, background, **kwargs)
# Annoyingly we need to redraw everything
self.array = ArrayDisplay(telx=np.asarray(self.tel_x),
tely=np.asarray(self.tel_y),
tel_type=self.tel_type)
if self.hillas is not None:
self.overlay_hillas(self.hillas)
def draw_array(self, range=((-2000, 2000), (-2000, 2000)), annotate=False):
"""
Draw the array plotter (including any overlayed elements)
Parameters
----------
range: tuple
XY range in which to draw plotter
Returns
-------
None
"""
self.array.axes.set_xlim(
(self.centre[0] + range[0][0], range[0][1] + self.centre[0]))
self.array.axes.set_ylim(
(self.centre[1] + range[1][0], range[1][1] + self.centre[1]))
if annotate:
for txt, x, y in zip(self.telescopes, self.tel_x.value,
self.tel_y.value):
self.axes.annotate(txt, (x, y))
#self.axes.tight_layout()
#self.axes.show()
def draw_position(self, core_x, core_y, use_centre=False, **kwargs):
"""
Draw a marker at a position in the array plotter (for marking reconstructed
positions etc)
Parameters
----------
core_x: float
X position of point
core_y: float
Y position of point
use_centre: bool
Centre the plotter on this position
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
ground = GroundFrame(x=np.asarray(core_x) * u.m,
y=np.asarray(core_y) * u.m,
z=np.asarray(0) * u.m)
if self.system is not None:
new_sys = ground.transform_to(self.system)
else:
new_sys = ground
self.array.add_polygon(centroid=(new_sys.x.value, new_sys.y.value),
radius=10,
nsides=3,
**kwargs)
if use_centre:
self.centre = (new_sys.x.value, new_sys.y.value)
class ArrayPlotter:
"""
Simple plotter for drawing array level items
"""
def __init__(self, instrument, telescopes=None, system=None, ax=None):
"""
Parameters
----------
instrument: dictionary
intrument containers for this event
telescopes: list
List of telescopes included
system: Coordinate system
Coordinate system to transform coordinates into
"""
self.instrument = instrument
self.system = system
if telescopes is None:
self.telescopes = instrument.telescope_ids
else:
self.telescopes = telescopes
type_dict = {28.0: 1, 16.0: 2,
2.1500000953674316: 3,
2.2829999923706055: 4,
5.599999904632568: 5}
tel_x = [self.instrument.tel_pos[i][0].to(u.m).value for i in self.telescopes]
tel_y = [self.instrument.tel_pos[i][1].to(u.m).value for i in self.telescopes]
tel_z = [self.instrument.tel_pos[i][2].to(u.m).value for i in self.telescopes]
self.axes = ax if ax is not None else plt.gca()
tel_type = np.asarray([type_dict[self.instrument.optical_foclen[i].to(u.m).value] for i in self.telescopes])
self.tel_type = tel_type
if system is not None:
ground = GroundFrame(x=np.asarray(tel_x)*u.m, y=np.asarray(tel_y)*u.m, z=np.asarray(tel_z)*u.m)
new_sys = ground.transform_to(system)
self.tel_x = new_sys.x
self.tel_y = new_sys.y
else:
self.tel_x = tel_x*u.m
self.tel_y = tel_y*u.m
self.centre = (0,0)
self.array = ArrayDisplay(telx=np.asarray(self.tel_x), tely=np.asarray(self.tel_y), tel_type=tel_type,
axes=self.axes)
self.hillas = None
def overlay_hillas(self, hillas, scale_fac=10000, draw_axes=False, **kwargs):
"""
Overlay hillas parameters on top of the array map
Parameters
----------
hillas: dictionary
Hillas moments objects to overlay
scale_fac: float
Scaling factor to array to hillas width and length when drawing
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
tel_x = [self.instrument.tel_pos[i][0].to(u.m).value for i in hillas]
tel_y = [self.instrument.tel_pos[i][1].to(u.m).value for i in hillas]
tel_z = [self.instrument.tel_pos[i][2].to(u.m).value for i in hillas]
if self.system is not None:
ground = GroundFrame(x=np.asarray(tel_x)*u.m, y=np.asarray(tel_y)*u.m, z=np.asarray(tel_z)*u.m)
new_sys = ground.transform_to(self.system)
self.array.overlay_moments(hillas, (new_sys.x, new_sys.y), scale_fac,
cmap="Greys", alpha=0.5, **kwargs)
if draw_axes:
self.array.overlay_axis(hillas, (new_sys.x, new_sys.y))
else:
self.array.overlay_moments(hillas, (tel_x, tel_y), scale_fac, alpha=0.5,
cmap="Greys", **kwargs)
self.hillas = hillas
def background_contour(self, x, y, background, **kwargs):
"""
Draw image contours in background of the display, useful when likelihood fitting
Parameters
----------
x: ndarray
array of image X coordinates
y: ndarray
array of image Y coordinates
background: ndarray
Array of image to use in background
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
self.axes.contour(x, y, background, **kwargs)
# Annoyingly we need to redraw everything
self.array = ArrayDisplay(telx=np.asarray(self.tel_x),
tely=np.asarray(self.tel_y),
tel_type=self.tel_type)
if self.hillas is not None:
self.overlay_hillas(self.hillas)
def draw_array(self, range=((-2000, 2000), (-2000, 2000)),
annotate=False):
"""
Draw the array plotter (including any overlayed elements)
Parameters
----------
range: tuple
XY range in which to draw plotter
Returns
-------
None
"""
self.array.axes.set_xlim((self.centre[0]+range[0][0], range[0][1]+self.centre[0]))
self.array.axes.set_ylim((self.centre[1]+range[1][0], range[1][1]+self.centre[1]))
if annotate:
for txt, x, y in zip(self.telescopes,
self.tel_x.value, self.tel_y.value):
self.axes.annotate(txt, (x, y))
#self.axes.tight_layout()
#self.axes.show()
def draw_position(self, core_x, core_y, use_centre=False, **kwargs):
"""
Draw a marker at a position in the array plotter (for marking reconstructed
positions etc)
Parameters
----------
core_x: float
X position of point
core_y: float
Y position of point
use_centre: bool
Centre the plotter on this position
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
ground = GroundFrame(x=np.asarray(core_x) * u.m, y=np.asarray(core_y) * u.m, z=np.asarray(0) * u.m)
if self.system is not None:
new_sys = ground.transform_to(self.system)
else:
new_sys = ground
self.array.add_polygon(centroid=(new_sys.x.value,new_sys.y.value), radius=10, nsides=3, **kwargs)
if use_centre:
self.centre = (new_sys.x.value,new_sys.y.value)
class NominalPlotter:
"""
Simple plotter for drawing camera level items in the nominal system
"""
def __init__(self, hillas_parameters, draw_axes=False, ax=None, **kwargs):
"""
Parameters
----------
instrument: dictionary
intrument containers for this event
telescopes: list
List of telescopes included
system: Coordinate system
Coordinate system to transform coordinates into
"""
self.axes = ax if ax is not None else plt.gca()
self.cen_x = [
i.cen_x.to(u.deg).value for i in hillas_parameters.values()
]
self.cen_y = [
i.cen_y.to(u.deg).value for i in hillas_parameters.values()
]
self.centre = (0, 0)
self.array = ArrayDisplay(telx=np.asarray(self.cen_x),
tely=np.asarray(self.cen_y),
tel_type=np.ones(len(self.cen_y)),
axes=self.axes)
self.hillas = hillas_parameters
scale_fac = 57.3 * 2
self.array.overlay_moments(hillas_parameters, (self.cen_x, self.cen_y),
scale_fac,
cmap="Greys",
alpha=0.5,
**kwargs)
if draw_axes:
self.array.overlay_axis(hillas_parameters,
(self.cen_x, self.cen_y))
def background_contour(self, x, y, background, **kwargs):
"""
Draw image contours in background of the display, useful when likelihood fitting
Parameters
----------
x: ndarray
array of image X coordinates
y: ndarray
array of image Y coordinates
background: ndarray
Array of image to use in background
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
self.axes.contour(x, y, background, **kwargs)
# Annoyingly we need to redraw everything
self.array = ArrayDisplay(telx=np.asarray(self.cen_x),
tely=np.asarray(self.cen_y),
tel_type=np.ones(len(self.cen_y)),
axes=self.axes)
def draw_array(self, range=((-4, 4), (-4, 4))):
"""
Draw the array plotter (including any overlayed elements)
Parameters
----------
range: tuple
XY range in which to draw plotter
Returns
-------
None
"""
self.array.axes.set_xlim(
(self.centre[0] + range[0][0], range[0][1] + self.centre[0]))
self.array.axes.set_ylim(
(self.centre[1] + range[1][0], range[1][1] + self.centre[1]))
#self.axes.tight_layout()
#self.axes.show()
def draw_position(self, source_x, source_y, use_centre=False, **kwargs):
"""
Draw a marker at a position in the array plotter (for marking reconstructed
positions etc)
Parameters
----------
source_x: float
X position of point
source_y: float
Y position of point
use_centre: bool
Centre the plotter on this position
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
self.array.add_polygon(centroid=(source_x.to(u.deg).value,
source_y.to(u.deg).value),
radius=0.1,
nsides=3,
**kwargs)
if use_centre:
self.centre = (source_x.value, source_y.value)
class NominalPlotter:
"""
Simple plotter for drawing camera level items in the nominal system
"""
def __init__(self, hillas_parameters, draw_axes=False, ax=None, **kwargs):
"""
Parameters
----------
instrument: dictionary
intrument containers for this event
telescopes: list
List of telescopes included
system: Coordinate system
Coordinate system to transform coordinates into
"""
self.axes = ax if ax is not None else plt.gca()
self.cen_x = [i.cen_x.to(u.deg).value for i in hillas_parameters.values()]
self.cen_y = [i.cen_y.to(u.deg).value for i in hillas_parameters.values()]
self.centre = (0,0)
self.array = ArrayDisplay(telx=np.asarray(self.cen_x), tely=np.asarray(self.cen_y),
tel_type=np.ones(len(self.cen_y)), axes=self.axes)
self.hillas = hillas_parameters
scale_fac = 57.3 * 2
self.array.overlay_moments(hillas_parameters, (self.cen_x, self.cen_y), scale_fac,
cmap="Greys", alpha=0.5, **kwargs)
if draw_axes:
self.array.overlay_axis(hillas_parameters, (self.cen_x, self.cen_y))
def background_contour(self, x, y, background, **kwargs):
"""
Draw image contours in background of the display, useful when likelihood fitting
Parameters
----------
x: ndarray
array of image X coordinates
y: ndarray
array of image Y coordinates
background: ndarray
Array of image to use in background
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
self.axes.contour(x, y, background, **kwargs)
# Annoyingly we need to redraw everything
self.array = ArrayDisplay(telx=np.asarray(self.cen_x), tely=np.asarray(self.cen_y),
tel_type=np.ones(len(self.cen_y)), axes=self.axes)
def draw_array(self, range=((-4,4),(-4,4))):
"""
Draw the array plotter (including any overlayed elements)
Parameters
----------
range: tuple
XY range in which to draw plotter
Returns
-------
None
"""
self.array.axes.set_xlim((self.centre[0]+range[0][0], range[0][1]+self.centre[0]))
self.array.axes.set_ylim((self.centre[1]+range[1][0], range[1][1]+self.centre[1]))
#self.axes.tight_layout()
#self.axes.show()
def draw_position(self, source_x, source_y, use_centre=False, **kwargs):
"""
Draw a marker at a position in the array plotter (for marking reconstructed
positions etc)
Parameters
----------
source_x: float
X position of point
source_y: float
Y position of point
use_centre: bool
Centre the plotter on this position
kwargs: key=value
any style keywords to pass to matplotlib
Returns
-------
None
"""
self.array.add_polygon(centroid=(source_x.to(u.deg).value,source_y.to(u.deg).value), radius=0.1, nsides=3, **kwargs)
if use_centre:
self.centre = (source_x.value,source_y.value)
