from astropy.visualization.wcsaxes import WCSAxes
import numpy as np
from madcubapy.coordinates import transform_coords_axes
from madcubapy.coordinates import transform_coords_fitsmap
__all__ = [
'copy_zoom_fitsmap',
'copy_zoom_axes',
'sync_zoom',
]
[docs]
def copy_zoom_fitsmap(
ref_fitsmap,
target_fitsmap,
x_lim,
y_lim,
origin=0):
"""
Copy a map's limits to another map.
Parameters
----------
ref_fitsmap : `~madcubapy.io.MadcubaMap` or `~astropy.nddata.CCDData`
Reference mape.
target_fitsmap : `~madcubapy.io.MadcubaMap` or `~astropy.nddata.CCDData`
Map into which limits are transformed.
x_lim : array-like
X axis limits from ref_fitsmap.
y_lim : array-like
Y axis limits from ref_fitsmap.
origin : int
Origin of the coordinates of the image. 0 for numpy standards,
and 1 for FITS standards.
Returns
-------
new_x_lim : `list`
Transformed X axis limits.
new_y_lim : `list`
Transformed Y axis limits.
"""
if len(x_lim) != 2 or len(y_lim) != 2:
raise TypeError(f"Limits need to be delimited by two coordinates "
+ "each (min, max)")
# Image corners
bottom_left = np.array([x_lim[0], y_lim[0]])
top_right = np.array([x_lim[1], y_lim[1]])
# Transform limits
new_bottom_left = transform_coords_fitsmap(ref_fitsmap=ref_fitsmap,
target_fitsmap=target_fitsmap,
points=bottom_left,
origin=origin)
new_top_right = transform_coords_fitsmap(ref_fitsmap=ref_fitsmap,
target_fitsmap=target_fitsmap,
points=top_right,
origin=origin)
# Return new limits
new_x_lim = [new_bottom_left[0], new_top_right[0]]
new_y_lim = [new_bottom_left[1], new_top_right[1]]
return new_x_lim, new_y_lim
[docs]
def copy_zoom_axes(
ref_ax,
target_ax):
"""
Copy a `~astropy.visualization.wcsaxes.WCSAxes` limits to another
`~astropy.visualization.wcsaxes.WCSAxes`.
Parameters
----------
ref_ax : `~astropy.visualization.wcsaxes.WCSAxes`
Reference Axes.
target_ax : `~astropy.visualization.wcsaxes.WCSAxes`
Axes into which limits are transformed.
"""
# Read limits
x_lim = ref_ax.get_xlim()
y_lim = ref_ax.get_ylim()
# Image corners
bottom_left = np.array([x_lim[0], y_lim[0]])
top_right = np.array([x_lim[1], y_lim[1]])
# Transform limits
new_bottom_left = transform_coords_axes(ref_ax=ref_ax,
target_ax=target_ax,
points=bottom_left)
new_top_right = transform_coords_axes(ref_ax=ref_ax,
target_ax=target_ax,
points=top_right)
# Set new limits
target_ax.set_xlim(new_bottom_left[0], new_top_right[0])
target_ax.set_ylim(new_bottom_left[1], new_top_right[1])
[docs]
def sync_zoom(
*axes):
"""
Synchronize X and Y limits between any number of
`~astropy.visualization.wcsaxes.WCSAxes` objects.
Parameters
----------
*axes : `~astropy.visualization.wcsaxes.WCSAxes`
WCSAxes objects to synchronize.
Notes
_____
Do not use this function too many times. It seems that python stores
every axes object connected in a given jupyter kernel run. If the
session runs for too long, the program will slow down considerably.
"""
# Check that all provided axes are instances of WCSAxes
if not all(isinstance(ax, WCSAxes) for ax in axes):
raise TypeError("All arguments must be instances of WCSAxes.")
class LimitSyncer:
def __init__(self):
# Shared state to prevent recursion
self.updating = False
def sync_x_limits(self, ax):
if self.updating:
return
self.updating = True
try:
# Read limits from reference axes
x_lim = ax.get_xlim()
y_lim = ax.get_ylim()
# Image corners
bottom_left = np.array([x_lim[0], y_lim[0]])
top_right = np.array([x_lim[1], y_lim[1]])
for axis in axes:
if axis != ax:
# Transform limits
new_bottom_left = transform_coords_axes(
ref_ax=ax,
target_ax=axis,
points=bottom_left
)
new_top_right = transform_coords_axes(
ref_ax=ax,
target_ax=axis,
points=top_right
)
# Set new limits in target axes
axis.set_xlim(new_bottom_left[0], new_top_right[0])
finally:
self.updating = False
def sync_y_limits(self, ax):
if self.updating:
return
self.updating = True
try:
# Read limits from reference axes
x_lim = ax.get_xlim()
y_lim = ax.get_ylim()
# Image corners
bottom_left = np.array([x_lim[0], y_lim[0]])
top_right = np.array([x_lim[1], y_lim[1]])
for axis in axes:
if axis != ax:
# Transform limits
new_bottom_left = transform_coords_axes(
ref_ax=ax,
target_ax=axis,
points=bottom_left
)
new_top_right = transform_coords_axes(
ref_ax=ax,
target_ax=axis,
points=top_right
)
# Set new limits in target axes
axis.set_ylim(new_bottom_left[1], new_top_right[1])
finally:
self.updating = False
# Create an instance of the limit syncer
syncer = LimitSyncer()
# Connect the limit change events to the syncer methods
# For this loop, it is needed to pass ax to the lambda function
for ax in axes:
ax.callbacks.connect('xlim_changed',
lambda event, ax=ax : syncer.sync_x_limits(ax))
ax.callbacks.connect('ylim_changed',
lambda event, ax=ax : syncer.sync_y_limits(ax))
