Module pyaurorax.tools.classes.keogram
Class representation for a keogram.
Expand source code
# Copyright 2024 University of Calgary
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Class representation for a keogram.
"""
import os
import datetime
import warnings
import aacgmv2
import matplotlib.pyplot as plt
import numpy as np
from dataclasses import dataclass
from typing import List, Optional, Tuple, Literal, Union, Any
from ...data.ucalgary import Skymap
@dataclass
class Keogram:
"""
Class representation for a keogram
Attributes:
data (numpy.ndarray):
The derived keogram data.
timestamp (List[datetime.datetime]):
Timestamps corresponding to each keogram slice.
ccd_y (numpy.ndarray):
The y-axis representing CCD Y coordinates for the keogram.
mag_y (numpy.ndarray):
The y-axis representing magnetic latitude for the keogram.
geo_y (numpy.ndarray):
The y-axis representing geographic latitude for the keogram.
"""
def __init__(self,
data: np.ndarray,
timestamp: List[datetime.datetime],
slice_idx: Optional[int] = None,
ccd_y: Optional[np.ndarray] = None,
mag_y: Optional[np.ndarray] = None,
geo_y: Optional[np.ndarray] = None):
# public vars
self.data = data
self.timestamp = timestamp
self.ccd_y = ccd_y
self.mag_y = mag_y
self.geo_y = geo_y
# private vars
self.__slice_idx = slice_idx
def __str__(self) -> str:
return self.__repr__()
def __repr__(self) -> str:
data_str = "array(dims=%s, dtype=%s)" % (self.data.shape, self.data.dtype)
timestamp_str = "[%d datetime objects]" % (len(self.timestamp))
ccd_y_str = "None" if self.ccd_y is None else "array(%d values)" % (self.ccd_y.shape[0])
mag_y_str = "None" if self.mag_y is None else "array(%d values)" % (self.mag_y.shape[0])
geo_y_str = "None" if self.geo_y is None else "array(%d values)" % (self.geo_y.shape[0])
return "Keogram(data=%s, timestamp=%s, ccd_y=%s, mag_y=%s, geo_y=%s)" % (data_str, timestamp_str, ccd_y_str, mag_y_str, geo_y_str)
def set_geographic_latitudes(self, skymap: Skymap, altitude_km: Optional[Union[int, float]] = None) -> None:
"""
Set the geographic latitude values for this keogram, using the specified skymap
data. The data will be set to the geo_y attribute of this Keogram object, which
can then be used for plotting and/or further analysis.
Args:
skymap (pyaurorax.data.ucalgary.Skymap):
The skymap object to use. This parameter is required.
altitude_km (int):
The altitude to use, in kilometers. If not specified, it will use the default in the
skymap object. If the specified altitude is not valid, a ValueError will be raised.
Returns:
None. The Keogram object's `geo_y` attribute will be updated.
Raises:
ValueError: Issues with specified altitude.
"""
# check for slice idx
if (self.__slice_idx is None):
raise ValueError("Unable to set the geographic latitudes since the slice_idx is None. If this keogram " +
"object was create as part of the custom_keogram routines, this is expected and performing " +
"this action not supported at this time.")
# determine altitude index to use
if (altitude_km is not None):
# Obtain lat/lon arrays from skymap
if (altitude_km * 1000.0 in skymap.full_map_altitude):
altitude_idx = np.where(altitude_km * 1000.0 == skymap.full_map_altitude)
self.geo_y = np.squeeze(skymap.full_map_latitude[altitude_idx, :, self.__slice_idx]).copy()
else:
# Make sure altitude is in range that can be interpolated
if (altitude_km * 1000.0 < skymap.full_map_altitude[0]) or (altitude_km * 1000.0 > skymap.full_map_altitude[2]):
raise ValueError("Altitude " + str(altitude_km) + " outside valid range of " +
str((skymap.full_map_altitude[0] / 1000.0, skymap.full_map_altitude[2] / 1000.0)))
# Initialze empty lat/lon arrays
lats = np.full(np.squeeze(skymap.full_map_latitude[0, :, :]).shape, np.nan, dtype=skymap.full_map_latitude[0, :, :].dtype)
# Interpolate lats and lons at desired altitude
for i in range(skymap.full_map_latitude.shape[1]):
for j in range(skymap.full_map_latitude.shape[2]):
lats[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_latitude[:, i, j])
self.geo_y = lats[:, self.__slice_idx].copy()
else:
# use default middle altitude
self.geo_y = np.squeeze(skymap.full_map_latitude[1,:, self.__slice_idx]).copy()
def set_magnetic_latitudes(self, skymap: Skymap, timestamp: datetime.datetime, altitude_km: Optional[Union[int, float]] = None) -> None:
"""
Set the magnetic latitude values for this keogram, using the specified skymap
data. AACGMv2 will be utilized to perform the calculations. The resulting data
will be set to the mag_y attribute of this Keogram object, which can then be
used for plotting and/or further analysis.
Args:
skymap (pyaurorax.data.ucalgary.Skymap):
The skymap object to use. This parameter is required.
timestamp (datetime.datetime):
The timestamp to use when converting skymap data to magnetic coordinates. Utilizes
AACGMv2 to do the conversion.
altitude_km (int):
The altitude to use. If not specified, it will use the default in the skymap
object. If the specified altitude is not valid, a ValueError will be raised.
Returns:
None. The Keogram object's `mag_y` attribute will be updated.
Raises:
ValueError: Issues with specified altitude.
"""
# check for slice idx
if (self.__slice_idx is None):
raise ValueError("Unable to set the geographic latitudes since the slice_idx is None. If this keogram " +
"object was create as part of the custom_keogram routines, this is expected and performing " +
"this action not supported at this time.")
# determine altitude index to use
if (altitude_km is not None):
# Obtain lat/lon arrays from skymap
if (altitude_km * 1000.0 in skymap.full_map_altitude):
altitude_idx = np.where(altitude_km * 1000.0 == skymap.full_map_altitude)
lats = np.squeeze(skymap.full_map_latitude[altitude_idx, :, :])
lons = np.squeeze(skymap.full_map_longitude[altitude_idx, :, :])
lons[np.where(lons > 180)] -= 360.0
else:
# Make sure altitude is in range that can be interpolated
if (altitude_km * 1000.0 < skymap.full_map_altitude[0]) or (altitude_km * 1000.0 > skymap.full_map_altitude[2]):
raise ValueError("Altitude " + str(altitude_km) + " outside valid range of " +
str((skymap.full_map_altitude[0] / 1000.0, skymap.full_map_altitude[2] / 1000.0)))
# Initialze empty lat/lon arrays
lats = np.full(np.squeeze(skymap.full_map_latitude[0, :, :]).shape, np.nan, dtype=skymap.full_map_latitude[0, :, :].dtype)
lons = lats.copy()
# Interpolate lats and lons at desired altitude
for i in range(skymap.full_map_latitude.shape[1]):
for j in range(skymap.full_map_latitude.shape[2]):
lats[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_latitude[:, i, j])
lons[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_longitude[:, i, j])
lons[np.where(lons > 180)] -= 360.0
# Convert lats and lons to geomagnetic coordinates
mag_lats, mag_lons, mag_alts = aacgmv2.convert_latlon_arr(lats.flatten(),
lons.flatten(), (lons * 0.0).flatten(),
timestamp,
method_code='G2A')
mag_lats = np.reshape(mag_lats, lats.shape)
mag_lons = np.reshape(mag_lons, lons.shape)
# Set the y axis to the desired slice index of the magnetic latitudes
self.mag_y = mag_lats[:, self.__slice_idx].copy()
else:
# Convert middle altitude lats and lons to geomagnetic coordinates
mag_lats, mag_lons, mag_alts = aacgmv2.convert_latlon_arr(np.squeeze(skymap.full_map_latitude[1, :, :]).flatten(),
np.squeeze(skymap.full_map_longitude[1, :, :]).flatten(),
(skymap.full_map_longitude[1, :, :] * 0.0).flatten(),
timestamp,
method_code='G2A')
mag_lats = np.reshape(mag_lats, np.squeeze(skymap.full_map_latitude[1, :, :]).shape)
mag_lons = np.reshape(mag_lons, np.squeeze(skymap.full_map_longitude[1, :, :]).shape)
# Set the y axis to the desired slice index of the magnetic latitudes
self.mag_y = mag_lats[:, self.__slice_idx].copy()
def plot(self,
y_type: Literal["ccd", "mag", "geo"] = "ccd",
title: Optional[str] = None,
figsize: Optional[Tuple[int, int]] = None,
cmap: Optional[str] = None,
aspect: Optional[Union[Literal["equal", "auto"], float]] = None,
axes_visible: bool = True,
xlabel: str = "Time (UTC)",
ylabel: Optional[str] = None,
xtick_increment: Optional[int] = None,
ytick_increment: Optional[int] = None,
returnfig: bool = False,
savefig: bool = False,
savefig_filename: Optional[str] = None,
savefig_quality: Optional[int] = None) -> Any:
"""
Generate a plot of the keogram data.
Either display it (default behaviour), save it to disk (using the `savefig` parameter), or
return the matplotlib plot object for further usage (using the `returnfig` parameter).
Args:
y_type (str):
Type of y-axis to use when plotting. Options are `ccd`, `mag`, or `geo`. The
default is `ccd`. This parameter is required.
title (str):
The title to display above the plotted keogram.
figsize (tuple):
The matplotlib figure size to use when plotting. For example `figsize=(14,4)`.
cmap (str):
The matplotlib colormap to use.
Commonly used colormaps are:
- REGO: `gist_heat`
- THEMIS ASI: `gray`
- TREx Blue: `Blues_r`
- TREx NIR: `gray`
- TREx RGB: `None`
A list of all available colormaps can be found on the
[matplotlib documentation](https://matplotlib.org/stable/gallery/color/colormap_reference.html).
aspect (str or float):
The matplotlib imshow aspect ration to use. A common value for this is `auto`. All valid values
can be found on the [matplotlib documentation](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html).
axes_visible (bool):
Display the axes. Default is `True`.
xlabel (str):
The x-axis label to use. Default is `Time (UTC)`.
ylabel (str):
The y-axis label to use. Default is based on y_type.
xtick_increment (int):
The x-axis tick increment to use. Default is 100.
ytick_increment (int):
The y-axis tick increment to use. Default is 50.
returnfig (bool):
Instead of displaying the image, return the matplotlib figure object. This allows for further plot
manipulation, for example, adding labels or a title in a different location than the default.
Remember - if this parameter is supplied, be sure that you close your plot after finishing work
with it. This can be achieved by doing `plt.close(fig)`.
Note that this method cannot be used in combination with `savefig`.
savefig (bool):
Save the displayed image to disk instead of displaying it. The parameter savefig_filename is required if
this parameter is set to True. Defaults to `False`.
savefig_filename (str):
Filename to save the image to. Must be specified if the savefig parameter is set to True.
savefig_quality (int):
Quality level of the saved image. This can be specified if the savefig_filename is a JPG image. If it
is a PNG, quality is ignored. Default quality level for JPGs is matplotlib/Pillow's default of 75%.
Returns:
The displayed keogram, by default. If `savefig` is set to True, nothing will be returned. If `returnfig` is
set to True, the plotting variables `(fig, ax)` will be returned.
Raises:
ValueError: Issues with the y-axis choice.
"""
# check return mode
if (returnfig is True and savefig is True):
raise ValueError("Only one of returnfig or savefig can be set to True")
if (returnfig is True and (savefig_filename is not None or savefig_quality is not None)):
warnings.warn("The figure will be returned, but a savefig option parameter was supplied. Consider " +
"removing the savefig option parameter(s) as they will be ignored.",
stacklevel=1)
elif (savefig is False and (savefig_filename is not None or savefig_quality is not None)):
warnings.warn("A savefig option parameter was supplied, but the savefig parameter is False. The " +
"savefig option parameters will be ignored.",
stacklevel=1)
# init figure and plot data
fig = plt.figure(figsize=figsize)
ax = fig.add_axes((0, 0, 1, 1))
ax.imshow(self.data, origin="lower", cmap=cmap, aspect=aspect)
# set title
if (title is not None):
ax.set_title(title)
# set axes
if (axes_visible is True):
# do checks for y-axis that was chosen
if (y_type == "geo" and self.geo_y is None):
raise ValueError("Unable to plot using geo_y data. The geo_y attribute is currently None, so either populate "
"it with data using the set_geographic_latitudes() function, or choose a different y_type")
elif (y_type == "mag" and self.mag_y is None):
raise ValueError("Unable to plot using mag_y data. The mag_y attribute is currently None, so either populate "
"it with data using the set_magnetic_latitudes() function, or choose a different y_type")
# set y axis data, and y label
y_axis_data = self.ccd_y
if (y_type == "mag"):
y_axis_data = self.mag_y
if (ylabel is None):
ylabel = "Magnetic latitude"
elif (y_type == "geo"):
y_axis_data = self.geo_y
if (ylabel is None):
ylabel = "Geographic latitude"
else:
if (ylabel is None):
ylabel = "CCD Y"
# print labels
ax.set_xlabel(xlabel, fontsize=14)
ax.set_ylabel(ylabel, fontsize=14)
# generate x ticks and labels
#
# TODO: make this more dynamic
if (xtick_increment is None):
xtick_increment = 100 # assume data is 3 second cadence; good enough for now
x_ticks = np.arange(0, self.data.shape[1], xtick_increment)
x_labels = self.timestamp[::xtick_increment]
for i in range(0, len(x_labels)):
x_labels[i] = x_labels[i].strftime("%H:%M") # type: ignore
ax.set_xticks(x_ticks, x_labels) # type: ignore
# do check for ccd_y
if (self.ccd_y is None):
warnings.warn(
"Unable to plot y-axis. If this keogram object was create as part of the custom_keogram " +
"routines, this is expected and plotting a custom keogram with axes is not supported at this time.",
stacklevel=1,
)
else:
# generate y ticks and labels
if (y_type == "ccd"):
# TODO: make this more dynamic
if (ytick_increment is None):
ytick_increment = 50
# generate y ticks and labels
y_ticks = y_axis_data[::ytick_increment] # type: ignore
y_labels = y_axis_data[::ytick_increment] # type: ignore
# apply yticks
ax.set_yticks(y_ticks, y_labels) # type: ignore
elif (y_type == "geo" and self.geo_y is not None) or (y_type == "mag" and self.mag_y is not None):
# set tick increments
if (ytick_increment is None):
ytick_increment = 50
# generate y ticks and labels
y_ticks = self.ccd_y[25::ytick_increment]
y_labels = np.round(y_axis_data, 1).astype(str)[25::ytick_increment] # type: ignore
y_labels[np.where(y_labels == 'nan')] = ''
# apply yticks
ax.set_yticks(y_ticks, y_labels)
else:
# disable axes
ax.set_axis_off()
# save figure or show it
if (savefig is True):
# check that filename has been set
if (savefig_filename is None):
raise ValueError("The savefig_filename parameter is missing, but required since savefig was set to True.")
# save the figure
f_extension = os.path.splitext(savefig_filename)[-1].lower()
if (".jpg" == f_extension or ".jpeg" == f_extension):
# check quality setting
if (savefig_quality is not None):
plt.savefig(savefig_filename, quality=savefig_quality, bbox_inches="tight")
else:
plt.savefig(savefig_filename, bbox_inches="tight")
else:
if (savefig_quality is not None):
# quality specified, but output filename is not a JPG, so show a warning
warnings.warn("The savefig_quality parameter was specified, but is only used for saving JPG files. The " +
"savefig_filename parameter was determined to not be a JPG file, so the quality will be ignored",
stacklevel=1)
plt.savefig(savefig_filename, bbox_inches="tight")
# clean up by closing the figure
plt.close(fig)
elif (returnfig is True):
# return the figure and axis objects
return (fig, ax)
else:
# show the figure
plt.show(fig)
# cleanup by closing the figure
plt.close(fig)
# return
return NoneClasses
class Keogram (data: numpy.ndarray, timestamp: List[datetime.datetime], slice_idx: Optional[int] = None, ccd_y: Optional[numpy.ndarray] = None, mag_y: Optional[numpy.ndarray] = None, geo_y: Optional[numpy.ndarray] = None)-
Class representation for a keogram
Attributes
data:numpy.ndarray- The derived keogram data.
timestamp:List[datetime.datetime]- Timestamps corresponding to each keogram slice.
ccd_y:numpy.ndarray- The y-axis representing CCD Y coordinates for the keogram.
mag_y:numpy.ndarray- The y-axis representing magnetic latitude for the keogram.
geo_y:numpy.ndarray- The y-axis representing geographic latitude for the keogram.
Expand source code
@dataclass class Keogram: """ Class representation for a keogram Attributes: data (numpy.ndarray): The derived keogram data. timestamp (List[datetime.datetime]): Timestamps corresponding to each keogram slice. ccd_y (numpy.ndarray): The y-axis representing CCD Y coordinates for the keogram. mag_y (numpy.ndarray): The y-axis representing magnetic latitude for the keogram. geo_y (numpy.ndarray): The y-axis representing geographic latitude for the keogram. """ def __init__(self, data: np.ndarray, timestamp: List[datetime.datetime], slice_idx: Optional[int] = None, ccd_y: Optional[np.ndarray] = None, mag_y: Optional[np.ndarray] = None, geo_y: Optional[np.ndarray] = None): # public vars self.data = data self.timestamp = timestamp self.ccd_y = ccd_y self.mag_y = mag_y self.geo_y = geo_y # private vars self.__slice_idx = slice_idx def __str__(self) -> str: return self.__repr__() def __repr__(self) -> str: data_str = "array(dims=%s, dtype=%s)" % (self.data.shape, self.data.dtype) timestamp_str = "[%d datetime objects]" % (len(self.timestamp)) ccd_y_str = "None" if self.ccd_y is None else "array(%d values)" % (self.ccd_y.shape[0]) mag_y_str = "None" if self.mag_y is None else "array(%d values)" % (self.mag_y.shape[0]) geo_y_str = "None" if self.geo_y is None else "array(%d values)" % (self.geo_y.shape[0]) return "Keogram(data=%s, timestamp=%s, ccd_y=%s, mag_y=%s, geo_y=%s)" % (data_str, timestamp_str, ccd_y_str, mag_y_str, geo_y_str) def set_geographic_latitudes(self, skymap: Skymap, altitude_km: Optional[Union[int, float]] = None) -> None: """ Set the geographic latitude values for this keogram, using the specified skymap data. The data will be set to the geo_y attribute of this Keogram object, which can then be used for plotting and/or further analysis. Args: skymap (pyaurorax.data.ucalgary.Skymap): The skymap object to use. This parameter is required. altitude_km (int): The altitude to use, in kilometers. If not specified, it will use the default in the skymap object. If the specified altitude is not valid, a ValueError will be raised. Returns: None. The Keogram object's `geo_y` attribute will be updated. Raises: ValueError: Issues with specified altitude. """ # check for slice idx if (self.__slice_idx is None): raise ValueError("Unable to set the geographic latitudes since the slice_idx is None. If this keogram " + "object was create as part of the custom_keogram routines, this is expected and performing " + "this action not supported at this time.") # determine altitude index to use if (altitude_km is not None): # Obtain lat/lon arrays from skymap if (altitude_km * 1000.0 in skymap.full_map_altitude): altitude_idx = np.where(altitude_km * 1000.0 == skymap.full_map_altitude) self.geo_y = np.squeeze(skymap.full_map_latitude[altitude_idx, :, self.__slice_idx]).copy() else: # Make sure altitude is in range that can be interpolated if (altitude_km * 1000.0 < skymap.full_map_altitude[0]) or (altitude_km * 1000.0 > skymap.full_map_altitude[2]): raise ValueError("Altitude " + str(altitude_km) + " outside valid range of " + str((skymap.full_map_altitude[0] / 1000.0, skymap.full_map_altitude[2] / 1000.0))) # Initialze empty lat/lon arrays lats = np.full(np.squeeze(skymap.full_map_latitude[0, :, :]).shape, np.nan, dtype=skymap.full_map_latitude[0, :, :].dtype) # Interpolate lats and lons at desired altitude for i in range(skymap.full_map_latitude.shape[1]): for j in range(skymap.full_map_latitude.shape[2]): lats[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_latitude[:, i, j]) self.geo_y = lats[:, self.__slice_idx].copy() else: # use default middle altitude self.geo_y = np.squeeze(skymap.full_map_latitude[1,:, self.__slice_idx]).copy() def set_magnetic_latitudes(self, skymap: Skymap, timestamp: datetime.datetime, altitude_km: Optional[Union[int, float]] = None) -> None: """ Set the magnetic latitude values for this keogram, using the specified skymap data. AACGMv2 will be utilized to perform the calculations. The resulting data will be set to the mag_y attribute of this Keogram object, which can then be used for plotting and/or further analysis. Args: skymap (pyaurorax.data.ucalgary.Skymap): The skymap object to use. This parameter is required. timestamp (datetime.datetime): The timestamp to use when converting skymap data to magnetic coordinates. Utilizes AACGMv2 to do the conversion. altitude_km (int): The altitude to use. If not specified, it will use the default in the skymap object. If the specified altitude is not valid, a ValueError will be raised. Returns: None. The Keogram object's `mag_y` attribute will be updated. Raises: ValueError: Issues with specified altitude. """ # check for slice idx if (self.__slice_idx is None): raise ValueError("Unable to set the geographic latitudes since the slice_idx is None. If this keogram " + "object was create as part of the custom_keogram routines, this is expected and performing " + "this action not supported at this time.") # determine altitude index to use if (altitude_km is not None): # Obtain lat/lon arrays from skymap if (altitude_km * 1000.0 in skymap.full_map_altitude): altitude_idx = np.where(altitude_km * 1000.0 == skymap.full_map_altitude) lats = np.squeeze(skymap.full_map_latitude[altitude_idx, :, :]) lons = np.squeeze(skymap.full_map_longitude[altitude_idx, :, :]) lons[np.where(lons > 180)] -= 360.0 else: # Make sure altitude is in range that can be interpolated if (altitude_km * 1000.0 < skymap.full_map_altitude[0]) or (altitude_km * 1000.0 > skymap.full_map_altitude[2]): raise ValueError("Altitude " + str(altitude_km) + " outside valid range of " + str((skymap.full_map_altitude[0] / 1000.0, skymap.full_map_altitude[2] / 1000.0))) # Initialze empty lat/lon arrays lats = np.full(np.squeeze(skymap.full_map_latitude[0, :, :]).shape, np.nan, dtype=skymap.full_map_latitude[0, :, :].dtype) lons = lats.copy() # Interpolate lats and lons at desired altitude for i in range(skymap.full_map_latitude.shape[1]): for j in range(skymap.full_map_latitude.shape[2]): lats[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_latitude[:, i, j]) lons[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_longitude[:, i, j]) lons[np.where(lons > 180)] -= 360.0 # Convert lats and lons to geomagnetic coordinates mag_lats, mag_lons, mag_alts = aacgmv2.convert_latlon_arr(lats.flatten(), lons.flatten(), (lons * 0.0).flatten(), timestamp, method_code='G2A') mag_lats = np.reshape(mag_lats, lats.shape) mag_lons = np.reshape(mag_lons, lons.shape) # Set the y axis to the desired slice index of the magnetic latitudes self.mag_y = mag_lats[:, self.__slice_idx].copy() else: # Convert middle altitude lats and lons to geomagnetic coordinates mag_lats, mag_lons, mag_alts = aacgmv2.convert_latlon_arr(np.squeeze(skymap.full_map_latitude[1, :, :]).flatten(), np.squeeze(skymap.full_map_longitude[1, :, :]).flatten(), (skymap.full_map_longitude[1, :, :] * 0.0).flatten(), timestamp, method_code='G2A') mag_lats = np.reshape(mag_lats, np.squeeze(skymap.full_map_latitude[1, :, :]).shape) mag_lons = np.reshape(mag_lons, np.squeeze(skymap.full_map_longitude[1, :, :]).shape) # Set the y axis to the desired slice index of the magnetic latitudes self.mag_y = mag_lats[:, self.__slice_idx].copy() def plot(self, y_type: Literal["ccd", "mag", "geo"] = "ccd", title: Optional[str] = None, figsize: Optional[Tuple[int, int]] = None, cmap: Optional[str] = None, aspect: Optional[Union[Literal["equal", "auto"], float]] = None, axes_visible: bool = True, xlabel: str = "Time (UTC)", ylabel: Optional[str] = None, xtick_increment: Optional[int] = None, ytick_increment: Optional[int] = None, returnfig: bool = False, savefig: bool = False, savefig_filename: Optional[str] = None, savefig_quality: Optional[int] = None) -> Any: """ Generate a plot of the keogram data. Either display it (default behaviour), save it to disk (using the `savefig` parameter), or return the matplotlib plot object for further usage (using the `returnfig` parameter). Args: y_type (str): Type of y-axis to use when plotting. Options are `ccd`, `mag`, or `geo`. The default is `ccd`. This parameter is required. title (str): The title to display above the plotted keogram. figsize (tuple): The matplotlib figure size to use when plotting. For example `figsize=(14,4)`. cmap (str): The matplotlib colormap to use. Commonly used colormaps are: - REGO: `gist_heat` - THEMIS ASI: `gray` - TREx Blue: `Blues_r` - TREx NIR: `gray` - TREx RGB: `None` A list of all available colormaps can be found on the [matplotlib documentation](https://matplotlib.org/stable/gallery/color/colormap_reference.html). aspect (str or float): The matplotlib imshow aspect ration to use. A common value for this is `auto`. All valid values can be found on the [matplotlib documentation](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html). axes_visible (bool): Display the axes. Default is `True`. xlabel (str): The x-axis label to use. Default is `Time (UTC)`. ylabel (str): The y-axis label to use. Default is based on y_type. xtick_increment (int): The x-axis tick increment to use. Default is 100. ytick_increment (int): The y-axis tick increment to use. Default is 50. returnfig (bool): Instead of displaying the image, return the matplotlib figure object. This allows for further plot manipulation, for example, adding labels or a title in a different location than the default. Remember - if this parameter is supplied, be sure that you close your plot after finishing work with it. This can be achieved by doing `plt.close(fig)`. Note that this method cannot be used in combination with `savefig`. savefig (bool): Save the displayed image to disk instead of displaying it. The parameter savefig_filename is required if this parameter is set to True. Defaults to `False`. savefig_filename (str): Filename to save the image to. Must be specified if the savefig parameter is set to True. savefig_quality (int): Quality level of the saved image. This can be specified if the savefig_filename is a JPG image. If it is a PNG, quality is ignored. Default quality level for JPGs is matplotlib/Pillow's default of 75%. Returns: The displayed keogram, by default. If `savefig` is set to True, nothing will be returned. If `returnfig` is set to True, the plotting variables `(fig, ax)` will be returned. Raises: ValueError: Issues with the y-axis choice. """ # check return mode if (returnfig is True and savefig is True): raise ValueError("Only one of returnfig or savefig can be set to True") if (returnfig is True and (savefig_filename is not None or savefig_quality is not None)): warnings.warn("The figure will be returned, but a savefig option parameter was supplied. Consider " + "removing the savefig option parameter(s) as they will be ignored.", stacklevel=1) elif (savefig is False and (savefig_filename is not None or savefig_quality is not None)): warnings.warn("A savefig option parameter was supplied, but the savefig parameter is False. The " + "savefig option parameters will be ignored.", stacklevel=1) # init figure and plot data fig = plt.figure(figsize=figsize) ax = fig.add_axes((0, 0, 1, 1)) ax.imshow(self.data, origin="lower", cmap=cmap, aspect=aspect) # set title if (title is not None): ax.set_title(title) # set axes if (axes_visible is True): # do checks for y-axis that was chosen if (y_type == "geo" and self.geo_y is None): raise ValueError("Unable to plot using geo_y data. The geo_y attribute is currently None, so either populate " "it with data using the set_geographic_latitudes() function, or choose a different y_type") elif (y_type == "mag" and self.mag_y is None): raise ValueError("Unable to plot using mag_y data. The mag_y attribute is currently None, so either populate " "it with data using the set_magnetic_latitudes() function, or choose a different y_type") # set y axis data, and y label y_axis_data = self.ccd_y if (y_type == "mag"): y_axis_data = self.mag_y if (ylabel is None): ylabel = "Magnetic latitude" elif (y_type == "geo"): y_axis_data = self.geo_y if (ylabel is None): ylabel = "Geographic latitude" else: if (ylabel is None): ylabel = "CCD Y" # print labels ax.set_xlabel(xlabel, fontsize=14) ax.set_ylabel(ylabel, fontsize=14) # generate x ticks and labels # # TODO: make this more dynamic if (xtick_increment is None): xtick_increment = 100 # assume data is 3 second cadence; good enough for now x_ticks = np.arange(0, self.data.shape[1], xtick_increment) x_labels = self.timestamp[::xtick_increment] for i in range(0, len(x_labels)): x_labels[i] = x_labels[i].strftime("%H:%M") # type: ignore ax.set_xticks(x_ticks, x_labels) # type: ignore # do check for ccd_y if (self.ccd_y is None): warnings.warn( "Unable to plot y-axis. If this keogram object was create as part of the custom_keogram " + "routines, this is expected and plotting a custom keogram with axes is not supported at this time.", stacklevel=1, ) else: # generate y ticks and labels if (y_type == "ccd"): # TODO: make this more dynamic if (ytick_increment is None): ytick_increment = 50 # generate y ticks and labels y_ticks = y_axis_data[::ytick_increment] # type: ignore y_labels = y_axis_data[::ytick_increment] # type: ignore # apply yticks ax.set_yticks(y_ticks, y_labels) # type: ignore elif (y_type == "geo" and self.geo_y is not None) or (y_type == "mag" and self.mag_y is not None): # set tick increments if (ytick_increment is None): ytick_increment = 50 # generate y ticks and labels y_ticks = self.ccd_y[25::ytick_increment] y_labels = np.round(y_axis_data, 1).astype(str)[25::ytick_increment] # type: ignore y_labels[np.where(y_labels == 'nan')] = '' # apply yticks ax.set_yticks(y_ticks, y_labels) else: # disable axes ax.set_axis_off() # save figure or show it if (savefig is True): # check that filename has been set if (savefig_filename is None): raise ValueError("The savefig_filename parameter is missing, but required since savefig was set to True.") # save the figure f_extension = os.path.splitext(savefig_filename)[-1].lower() if (".jpg" == f_extension or ".jpeg" == f_extension): # check quality setting if (savefig_quality is not None): plt.savefig(savefig_filename, quality=savefig_quality, bbox_inches="tight") else: plt.savefig(savefig_filename, bbox_inches="tight") else: if (savefig_quality is not None): # quality specified, but output filename is not a JPG, so show a warning warnings.warn("The savefig_quality parameter was specified, but is only used for saving JPG files. The " + "savefig_filename parameter was determined to not be a JPG file, so the quality will be ignored", stacklevel=1) plt.savefig(savefig_filename, bbox_inches="tight") # clean up by closing the figure plt.close(fig) elif (returnfig is True): # return the figure and axis objects return (fig, ax) else: # show the figure plt.show(fig) # cleanup by closing the figure plt.close(fig) # return return NoneMethods
def plot(self, y_type: Literal['ccd', 'mag', 'geo'] = 'ccd', title: Optional[str] = None, figsize: Optional[Tuple[int, int]] = None, cmap: Optional[str] = None, aspect: Union[Literal['equal', 'auto'], float, ForwardRef(None)] = None, axes_visible: bool = True, xlabel: str = 'Time (UTC)', ylabel: Optional[str] = None, xtick_increment: Optional[int] = None, ytick_increment: Optional[int] = None, returnfig: bool = False, savefig: bool = False, savefig_filename: Optional[str] = None, savefig_quality: Optional[int] = None) ‑> Any-
Generate a plot of the keogram data.
Either display it (default behaviour), save it to disk (using the
savefigparameter), or return the matplotlib plot object for further usage (using thereturnfigparameter).Args
y_type:str- Type of y-axis to use when plotting. Options are
ccd,mag, orgeo. The default isccd. This parameter is required. title:str- The title to display above the plotted keogram.
figsize:tuple- The matplotlib figure size to use when plotting. For example
figsize=(14,4). cmap:str-
The matplotlib colormap to use.
Commonly used colormaps are:
- REGO:
gist_heat - THEMIS ASI:
gray - TREx Blue:
Blues_r - TREx NIR:
gray - TREx RGB:
None
A list of all available colormaps can be found on the matplotlib documentation.
- REGO:
aspect:strorfloat- The matplotlib imshow aspect ration to use. A common value for this is
auto. All valid values can be found on the matplotlib documentation. axes_visible:bool- Display the axes. Default is
True. xlabel:str- The x-axis label to use. Default is
Time (UTC). ylabel:str- The y-axis label to use. Default is based on y_type.
xtick_increment:int- The x-axis tick increment to use. Default is 100.
ytick_increment:int- The y-axis tick increment to use. Default is 50.
returnfig:bool-
Instead of displaying the image, return the matplotlib figure object. This allows for further plot manipulation, for example, adding labels or a title in a different location than the default.
Remember - if this parameter is supplied, be sure that you close your plot after finishing work with it. This can be achieved by doing
plt.close(fig).Note that this method cannot be used in combination with
savefig. savefig:bool- Save the displayed image to disk instead of displaying it. The parameter savefig_filename is required if
this parameter is set to True. Defaults to
False. savefig_filename:str- Filename to save the image to. Must be specified if the savefig parameter is set to True.
savefig_quality:int- Quality level of the saved image. This can be specified if the savefig_filename is a JPG image. If it is a PNG, quality is ignored. Default quality level for JPGs is matplotlib/Pillow's default of 75%.
Returns
The displayed keogram, by default. If
savefigis set to True, nothing will be returned. Ifreturnfigis set to True, the plotting variables(fig, ax)will be returned.Raises
ValueError- Issues with the y-axis choice.
Expand source code
def plot(self, y_type: Literal["ccd", "mag", "geo"] = "ccd", title: Optional[str] = None, figsize: Optional[Tuple[int, int]] = None, cmap: Optional[str] = None, aspect: Optional[Union[Literal["equal", "auto"], float]] = None, axes_visible: bool = True, xlabel: str = "Time (UTC)", ylabel: Optional[str] = None, xtick_increment: Optional[int] = None, ytick_increment: Optional[int] = None, returnfig: bool = False, savefig: bool = False, savefig_filename: Optional[str] = None, savefig_quality: Optional[int] = None) -> Any: """ Generate a plot of the keogram data. Either display it (default behaviour), save it to disk (using the `savefig` parameter), or return the matplotlib plot object for further usage (using the `returnfig` parameter). Args: y_type (str): Type of y-axis to use when plotting. Options are `ccd`, `mag`, or `geo`. The default is `ccd`. This parameter is required. title (str): The title to display above the plotted keogram. figsize (tuple): The matplotlib figure size to use when plotting. For example `figsize=(14,4)`. cmap (str): The matplotlib colormap to use. Commonly used colormaps are: - REGO: `gist_heat` - THEMIS ASI: `gray` - TREx Blue: `Blues_r` - TREx NIR: `gray` - TREx RGB: `None` A list of all available colormaps can be found on the [matplotlib documentation](https://matplotlib.org/stable/gallery/color/colormap_reference.html). aspect (str or float): The matplotlib imshow aspect ration to use. A common value for this is `auto`. All valid values can be found on the [matplotlib documentation](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html). axes_visible (bool): Display the axes. Default is `True`. xlabel (str): The x-axis label to use. Default is `Time (UTC)`. ylabel (str): The y-axis label to use. Default is based on y_type. xtick_increment (int): The x-axis tick increment to use. Default is 100. ytick_increment (int): The y-axis tick increment to use. Default is 50. returnfig (bool): Instead of displaying the image, return the matplotlib figure object. This allows for further plot manipulation, for example, adding labels or a title in a different location than the default. Remember - if this parameter is supplied, be sure that you close your plot after finishing work with it. This can be achieved by doing `plt.close(fig)`. Note that this method cannot be used in combination with `savefig`. savefig (bool): Save the displayed image to disk instead of displaying it. The parameter savefig_filename is required if this parameter is set to True. Defaults to `False`. savefig_filename (str): Filename to save the image to. Must be specified if the savefig parameter is set to True. savefig_quality (int): Quality level of the saved image. This can be specified if the savefig_filename is a JPG image. If it is a PNG, quality is ignored. Default quality level for JPGs is matplotlib/Pillow's default of 75%. Returns: The displayed keogram, by default. If `savefig` is set to True, nothing will be returned. If `returnfig` is set to True, the plotting variables `(fig, ax)` will be returned. Raises: ValueError: Issues with the y-axis choice. """ # check return mode if (returnfig is True and savefig is True): raise ValueError("Only one of returnfig or savefig can be set to True") if (returnfig is True and (savefig_filename is not None or savefig_quality is not None)): warnings.warn("The figure will be returned, but a savefig option parameter was supplied. Consider " + "removing the savefig option parameter(s) as they will be ignored.", stacklevel=1) elif (savefig is False and (savefig_filename is not None or savefig_quality is not None)): warnings.warn("A savefig option parameter was supplied, but the savefig parameter is False. The " + "savefig option parameters will be ignored.", stacklevel=1) # init figure and plot data fig = plt.figure(figsize=figsize) ax = fig.add_axes((0, 0, 1, 1)) ax.imshow(self.data, origin="lower", cmap=cmap, aspect=aspect) # set title if (title is not None): ax.set_title(title) # set axes if (axes_visible is True): # do checks for y-axis that was chosen if (y_type == "geo" and self.geo_y is None): raise ValueError("Unable to plot using geo_y data. The geo_y attribute is currently None, so either populate " "it with data using the set_geographic_latitudes() function, or choose a different y_type") elif (y_type == "mag" and self.mag_y is None): raise ValueError("Unable to plot using mag_y data. The mag_y attribute is currently None, so either populate " "it with data using the set_magnetic_latitudes() function, or choose a different y_type") # set y axis data, and y label y_axis_data = self.ccd_y if (y_type == "mag"): y_axis_data = self.mag_y if (ylabel is None): ylabel = "Magnetic latitude" elif (y_type == "geo"): y_axis_data = self.geo_y if (ylabel is None): ylabel = "Geographic latitude" else: if (ylabel is None): ylabel = "CCD Y" # print labels ax.set_xlabel(xlabel, fontsize=14) ax.set_ylabel(ylabel, fontsize=14) # generate x ticks and labels # # TODO: make this more dynamic if (xtick_increment is None): xtick_increment = 100 # assume data is 3 second cadence; good enough for now x_ticks = np.arange(0, self.data.shape[1], xtick_increment) x_labels = self.timestamp[::xtick_increment] for i in range(0, len(x_labels)): x_labels[i] = x_labels[i].strftime("%H:%M") # type: ignore ax.set_xticks(x_ticks, x_labels) # type: ignore # do check for ccd_y if (self.ccd_y is None): warnings.warn( "Unable to plot y-axis. If this keogram object was create as part of the custom_keogram " + "routines, this is expected and plotting a custom keogram with axes is not supported at this time.", stacklevel=1, ) else: # generate y ticks and labels if (y_type == "ccd"): # TODO: make this more dynamic if (ytick_increment is None): ytick_increment = 50 # generate y ticks and labels y_ticks = y_axis_data[::ytick_increment] # type: ignore y_labels = y_axis_data[::ytick_increment] # type: ignore # apply yticks ax.set_yticks(y_ticks, y_labels) # type: ignore elif (y_type == "geo" and self.geo_y is not None) or (y_type == "mag" and self.mag_y is not None): # set tick increments if (ytick_increment is None): ytick_increment = 50 # generate y ticks and labels y_ticks = self.ccd_y[25::ytick_increment] y_labels = np.round(y_axis_data, 1).astype(str)[25::ytick_increment] # type: ignore y_labels[np.where(y_labels == 'nan')] = '' # apply yticks ax.set_yticks(y_ticks, y_labels) else: # disable axes ax.set_axis_off() # save figure or show it if (savefig is True): # check that filename has been set if (savefig_filename is None): raise ValueError("The savefig_filename parameter is missing, but required since savefig was set to True.") # save the figure f_extension = os.path.splitext(savefig_filename)[-1].lower() if (".jpg" == f_extension or ".jpeg" == f_extension): # check quality setting if (savefig_quality is not None): plt.savefig(savefig_filename, quality=savefig_quality, bbox_inches="tight") else: plt.savefig(savefig_filename, bbox_inches="tight") else: if (savefig_quality is not None): # quality specified, but output filename is not a JPG, so show a warning warnings.warn("The savefig_quality parameter was specified, but is only used for saving JPG files. The " + "savefig_filename parameter was determined to not be a JPG file, so the quality will be ignored", stacklevel=1) plt.savefig(savefig_filename, bbox_inches="tight") # clean up by closing the figure plt.close(fig) elif (returnfig is True): # return the figure and axis objects return (fig, ax) else: # show the figure plt.show(fig) # cleanup by closing the figure plt.close(fig) # return return None def set_geographic_latitudes(self, skymap: pyucalgarysrs.data.classes.Skymap, altitude_km: Union[int, float, ForwardRef(None)] = None) ‑> None-
Set the geographic latitude values for this keogram, using the specified skymap data. The data will be set to the geo_y attribute of this Keogram object, which can then be used for plotting and/or further analysis.
Args
skymap:Skymap- The skymap object to use. This parameter is required.
altitude_km:int- The altitude to use, in kilometers. If not specified, it will use the default in the skymap object. If the specified altitude is not valid, a ValueError will be raised.
Returns
None. The Keogram object's
geo_yattribute will be updated.Raises
ValueError- Issues with specified altitude.
Expand source code
def set_geographic_latitudes(self, skymap: Skymap, altitude_km: Optional[Union[int, float]] = None) -> None: """ Set the geographic latitude values for this keogram, using the specified skymap data. The data will be set to the geo_y attribute of this Keogram object, which can then be used for plotting and/or further analysis. Args: skymap (pyaurorax.data.ucalgary.Skymap): The skymap object to use. This parameter is required. altitude_km (int): The altitude to use, in kilometers. If not specified, it will use the default in the skymap object. If the specified altitude is not valid, a ValueError will be raised. Returns: None. The Keogram object's `geo_y` attribute will be updated. Raises: ValueError: Issues with specified altitude. """ # check for slice idx if (self.__slice_idx is None): raise ValueError("Unable to set the geographic latitudes since the slice_idx is None. If this keogram " + "object was create as part of the custom_keogram routines, this is expected and performing " + "this action not supported at this time.") # determine altitude index to use if (altitude_km is not None): # Obtain lat/lon arrays from skymap if (altitude_km * 1000.0 in skymap.full_map_altitude): altitude_idx = np.where(altitude_km * 1000.0 == skymap.full_map_altitude) self.geo_y = np.squeeze(skymap.full_map_latitude[altitude_idx, :, self.__slice_idx]).copy() else: # Make sure altitude is in range that can be interpolated if (altitude_km * 1000.0 < skymap.full_map_altitude[0]) or (altitude_km * 1000.0 > skymap.full_map_altitude[2]): raise ValueError("Altitude " + str(altitude_km) + " outside valid range of " + str((skymap.full_map_altitude[0] / 1000.0, skymap.full_map_altitude[2] / 1000.0))) # Initialze empty lat/lon arrays lats = np.full(np.squeeze(skymap.full_map_latitude[0, :, :]).shape, np.nan, dtype=skymap.full_map_latitude[0, :, :].dtype) # Interpolate lats and lons at desired altitude for i in range(skymap.full_map_latitude.shape[1]): for j in range(skymap.full_map_latitude.shape[2]): lats[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_latitude[:, i, j]) self.geo_y = lats[:, self.__slice_idx].copy() else: # use default middle altitude self.geo_y = np.squeeze(skymap.full_map_latitude[1,:, self.__slice_idx]).copy() def set_magnetic_latitudes(self, skymap: pyucalgarysrs.data.classes.Skymap, timestamp: datetime.datetime, altitude_km: Union[int, float, ForwardRef(None)] = None) ‑> None-
Set the magnetic latitude values for this keogram, using the specified skymap data. AACGMv2 will be utilized to perform the calculations. The resulting data will be set to the mag_y attribute of this Keogram object, which can then be used for plotting and/or further analysis.
Args
skymap:Skymap- The skymap object to use. This parameter is required.
timestamp:datetime.datetime- The timestamp to use when converting skymap data to magnetic coordinates. Utilizes AACGMv2 to do the conversion.
altitude_km:int- The altitude to use. If not specified, it will use the default in the skymap object. If the specified altitude is not valid, a ValueError will be raised.
Returns
None. The Keogram object's
mag_yattribute will be updated.Raises
ValueError- Issues with specified altitude.
Expand source code
def set_magnetic_latitudes(self, skymap: Skymap, timestamp: datetime.datetime, altitude_km: Optional[Union[int, float]] = None) -> None: """ Set the magnetic latitude values for this keogram, using the specified skymap data. AACGMv2 will be utilized to perform the calculations. The resulting data will be set to the mag_y attribute of this Keogram object, which can then be used for plotting and/or further analysis. Args: skymap (pyaurorax.data.ucalgary.Skymap): The skymap object to use. This parameter is required. timestamp (datetime.datetime): The timestamp to use when converting skymap data to magnetic coordinates. Utilizes AACGMv2 to do the conversion. altitude_km (int): The altitude to use. If not specified, it will use the default in the skymap object. If the specified altitude is not valid, a ValueError will be raised. Returns: None. The Keogram object's `mag_y` attribute will be updated. Raises: ValueError: Issues with specified altitude. """ # check for slice idx if (self.__slice_idx is None): raise ValueError("Unable to set the geographic latitudes since the slice_idx is None. If this keogram " + "object was create as part of the custom_keogram routines, this is expected and performing " + "this action not supported at this time.") # determine altitude index to use if (altitude_km is not None): # Obtain lat/lon arrays from skymap if (altitude_km * 1000.0 in skymap.full_map_altitude): altitude_idx = np.where(altitude_km * 1000.0 == skymap.full_map_altitude) lats = np.squeeze(skymap.full_map_latitude[altitude_idx, :, :]) lons = np.squeeze(skymap.full_map_longitude[altitude_idx, :, :]) lons[np.where(lons > 180)] -= 360.0 else: # Make sure altitude is in range that can be interpolated if (altitude_km * 1000.0 < skymap.full_map_altitude[0]) or (altitude_km * 1000.0 > skymap.full_map_altitude[2]): raise ValueError("Altitude " + str(altitude_km) + " outside valid range of " + str((skymap.full_map_altitude[0] / 1000.0, skymap.full_map_altitude[2] / 1000.0))) # Initialze empty lat/lon arrays lats = np.full(np.squeeze(skymap.full_map_latitude[0, :, :]).shape, np.nan, dtype=skymap.full_map_latitude[0, :, :].dtype) lons = lats.copy() # Interpolate lats and lons at desired altitude for i in range(skymap.full_map_latitude.shape[1]): for j in range(skymap.full_map_latitude.shape[2]): lats[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_latitude[:, i, j]) lons[i, j] = np.interp(altitude_km * 1000.0, skymap.full_map_altitude, skymap.full_map_longitude[:, i, j]) lons[np.where(lons > 180)] -= 360.0 # Convert lats and lons to geomagnetic coordinates mag_lats, mag_lons, mag_alts = aacgmv2.convert_latlon_arr(lats.flatten(), lons.flatten(), (lons * 0.0).flatten(), timestamp, method_code='G2A') mag_lats = np.reshape(mag_lats, lats.shape) mag_lons = np.reshape(mag_lons, lons.shape) # Set the y axis to the desired slice index of the magnetic latitudes self.mag_y = mag_lats[:, self.__slice_idx].copy() else: # Convert middle altitude lats and lons to geomagnetic coordinates mag_lats, mag_lons, mag_alts = aacgmv2.convert_latlon_arr(np.squeeze(skymap.full_map_latitude[1, :, :]).flatten(), np.squeeze(skymap.full_map_longitude[1, :, :]).flatten(), (skymap.full_map_longitude[1, :, :] * 0.0).flatten(), timestamp, method_code='G2A') mag_lats = np.reshape(mag_lats, np.squeeze(skymap.full_map_latitude[1, :, :]).shape) mag_lons = np.reshape(mag_lons, np.squeeze(skymap.full_map_longitude[1, :, :]).shape) # Set the y axis to the desired slice index of the magnetic latitudes self.mag_y = mag_lats[:, self.__slice_idx].copy()