import logging
import pyspedas
import numpy as np
from pyspedas.tplot_tools import get_y_range
from pyspedas.tplot_tools import tplot_wildcard_expand
[docs]
def options(name, option=None, value=None, opt_dict=None, quiet=False):
""" Set a large variety of options for individual plots.
Parameters
----------
name : str or list[str]
Names of tplot variables to be updated (wildcards accepted).
option : str, optional
The name of the option. See the options section below.
value : str, int, float, list, optional
The value of the option. See the options section below.
opt_dict : dict, optional
This can be a dictionary of option-value pairs. 'option' and 'value'
will not be needed if this dictionary item is supplied.
quiet: bool, optional
If True, do not complain about unrecognized options.
Options
-------
Many of the options are passed directly to matplotlib calls. For more extensive documentation about how to use these
obtions, see the matplotlib documentation: https://matplotlib.org/stable/users/index.html
Note that many X-axis options are controlled at the level of the entire plot, rather than per-variable (since plots with multiple panels will
share many X axis properties). See the tplot_options() routine for available per-plot options,
====================== =========== ===========================================================================================================================
Panel Options Value type Notes
====================== =========== ===========================================================================================================================
title str The title of the plot.
panel_size flt Number between (0,1], representing the percent size of the plot.
alpha flt Number between [0,1], gives the transparency of the plot lines.
line_width flt Sets plot line width.
line_style str scatter (to make scatter plots), or solid_line, dot, dash, dash_dot, dash_dot_dot_dot, long_dash.
border bool Turns on or off the top/right axes that would create a box around the plot.
var_label_format str The format of the tick labels if this variable is displayed as an alternative x axis. Default: {:.2f}
char_size int Defines character size for x/y/z titles and subtitles
right_axis bool If true,display a second Y axis on the right side of the plot.
second_axis_size numeric The size of the second axis to display
data_gap numeric If there is a gap in the data larger than this number in seconds, then insert
(cont) (cont) NaNs. This is similar to using the degap procedure on the variable, but is
(cont) (cont) applied at plot-time, and does not persist in the variable data.
annotations dict A dictionary or list of dictionaries of matplotlib text annotation parameters (see annotate() routine)
visible bool If False, do not display lines for this variable.
nodata bool If True, do not display lines for this variable.
====================== =========== ===========================================================================================================================
====================== =========== ===========================================================================================================================
Legend Options Value type Notes
====================== =========== ===========================================================================================================================
legend_names list A list of strings that will be used to identify the legends.
legend_location str A string giving the location of the legend box.
legend_size numeric The font size of the legend names
legend_shadow bool Turns on or off drop shadows on the legend box
legend_title str The title to display on the legend
legend_titlesize numeric The font size of the legend title
legend_color [str] The color of the legend names
legend_edgecolor str The border color of the legend box
legend_facecolor str The background color of the legend box
legend_markerfirst boolean Put the marker and line to the left of the label in the legend
legend_markerscale numeric The scale size of markers displayed in the legend
legend_linewidth numeric The width of the lines displayed in the legend
====================== =========== ===========================================================================================================================
====================== =========== ===========================================================================================================================
X Axis Options Value type Notes
====================== =========== ===========================================================================================================================
xtitle str The title to be placed under the x axis.
xsubtitle str The subtitle to be placed under the x axis
xtitle_color str The color of the x axis title.
xtick_length numeric The length of the x tick marks
xtick_width numeric The width of the x tick marks
xtick_color str The color of the x tick marks
xtick_labelcolor str The color of the x tick marks
xtick_direction str The direction of the x tick marks (in, out, inout)
====================== =========== ===========================================================================================================================
====================== =========== ===========================================================================================================================
Y Axis Options Value type Notes
====================== =========== ===========================================================================================================================
y_range flt/list Two numbers that give the y axis range of the plot. If a third argument is present, set linear or log scaling accordingly.
ylog bool True sets the y axis to log scale, False reverts.
ytitle str Title shown on the y axis. Use backslash for new lines.
ysubtitle str Subtitle shown on the y axis.
ytitle_color str The color of the y axis title.
ytick_length numeric The length of the Y tick marks
ytick_width numeric The width of the Y tick marks
ytick_color str The color of the Y tick marks
ytick_labelcolor str The color of the Y tick marks
ytick_direction str The direction of the Y tick marks (in, out, inout)
y_major_ticks [numeric] A list of values that will be used to set the major ticks on the Y axis.
y_minor_tick_interval numeric The interval between minor ticks on the Y axis.
====================== =========== ===========================================================================================================================
====================== =========== ===========================================================================================================================
Error Bar Options Value type Notes
====================== =========== ===========================================================================================================================
errorevery numeric Interval at which to show error bars
capsize numeric The size of error bar caps
ecolor str The color of the error bar lines
elinewidth numeric The width of the error bar lines
====================== =========== ===========================================================================================================================
====================== =========== ===========================================================================================================================
Marker/Symbol Options Value type Notes
====================== =========== ===========================================================================================================================
marker_size numeric The size of the markers displayed in the plot
markevery numeric Interval at which to show markers
symbols bool If True, display as a scatter plot (no lines)
====================== =========== ===========================================================================================================================
====================== =========== ===========================================================================================================================
Z / Specplot Options Value type Notes
====================== =========== ===========================================================================================================================
spec bool Display this variable as a spectrogram.
colormap str/list Color map to use for specplots https://matplotlib.org/examples/color/colormaps_reference.html.
z_range flt/list Two numbers that give the z axis range of the plot. If a third argument is present, set linear or log scaling accordingly.
zlog int True sets the z axis to log scale, False reverts (spectrograms only).
ztitle str Title shown on the z axis. Spec plots only. Use backslash for new lines.
zsubtitle str Subtitle shown on the z axis. Spec plots only.
ztitle_color str The color of the z axis title.
x_interp bool If true, perform smoothing of spectrograms in the X direction
x_interp_points numeric Number of interpolation points to use in the X direction
y_interp bool If true, perform smoothing of spectrograms in the Y direction
y_interp_points numeric Number of interpolation points to use in the Y direction
xrange_slice flt/list Two numbers that give the x axis range of spectrogram slicing plots.
yrange_slice flt/list Two numbers that give the y axis range of spectrogram slicing plots.
xlog_slice bool Sets x axis on slice plot to log scale if True.
ylog_slice bool Sets y axis on slice plot to log scale if True.
spec_dim_to_plot int/str If variable has more than two dimensions, this sets which dimension the "v"
(cont) (cont) variable will display on the y axis in spectrogram plots.
(cont) (cont) All other dimensions are summed into this one, unless "spec_slices_to_use"
(cont) (cont) is also set for this variable.
spec_slices_to_use str Must be a dictionary of coordinate:values. If a variable has more than two
(cont) (cont) dimensions, spectrogram plots will plot values at that particular slice of
(cont) (cont) that dimension. See examples for how it works.
====================== =========== ===========================================================================================================================
Many options have synonyms or variant spellings that are commonly used. The first column gives the name that is used
throughout the plotting code. The second column gives the synonyms that are accepted.
====================== ======================================================================================================================================
Canonical name Accepted synonyms
====================== ======================================================================================================================================
title name
line_color color, colors, col, cols, line_colors
legend_names labels, legend_name, legend_label, legend_labels
legend_location labels_location, legends_location, label_location, labels_location
legend_size labels_size, label_size
legend_shadow labels_shadow. label_shadow
legend_title label_title, labels_title
legend_titlesize lable_titlesize, labels_titlesize
legend_color legends_color, label_color, labels_color
legend_edgecolor label_edgecolor, labels_edgecolor
legend_facecolor label_facecolor, labels_facecolor
legend_markerfirst label_markerfirst, labels_markerfirst
legend_markerscale label_markerscale, labels_markerscale
legend_linewidth label_linewidth, labels_linewidth
legend_frameon label_frameon, labels_frameon
legend_ncols label_ncols, labels_ncols
line_style_name line_style, linestyle
char_size charsize
marker markers
marker_size markersize
markevery markerevery mark_every marker_every
symbol symbols
line_width thick
y_range yrange
z_range zrange
data_gap datagap
spec_dim_to_plot spec_plot_dim
var_label_format varlabel_format
annotations annotation
====================== ======================================================================================================================================
Returns
-------
None
Examples
--------
>>> # Change the y range of Variable1
>>> import pyspedas
>>> x_data = [1,2,3,4,5]
>>> y_data = [1,2,3,4,5]
>>> pyspedas.store_data("Variable1", data={'x':x_data, 'y':y_data})
>>> pyspedas.options('Variable1', 'yrange', [2,4])
>>> # Change Variable1 to use a log scale
>>> pyspedas.options('Variable1', 'ylog', 1)
>>> pyspedas.tplot('Variable1')
>>> # Multi-dimensional variable
>>> y_data = np.random.rand(5, 4, 3)
>>> v1_data = [0, 1, 3, 4]
>>> v2_data = [1, 2, 3]
>>> pyspedas.store_data("Variable2", data={'x': x_data, 'y': y_data, 'v1': v1_data, 'v2': v2_data})
>>> # Set the spectrogram plots to show dimension 'v2' at slice 'v1' = 0
>>> pyspedas.options('Variable2', 'spec', 1)
>>> pyspedas.options("Variable2", "spec_dim_to_plot", 'v2')
>>> pyspedas.options("Variable2", "spec_slices_to_use", {'v1': 0})
>>> pyspedas.tplot('Variable2')
"""
if isinstance(name, int):
name = list(pyspedas.tplot_tools.data_quants.keys())[name]
if opt_dict is None:
opt_dict = {option: value}
else:
if not isinstance(opt_dict,dict):
logging.error("dict must be a dictionary object. Returning.")
return
if not isinstance(name, list):
name = [name]
names = tplot_wildcard_expand(name)
for i in names:
for option, value in opt_dict.items():
# Lower case option for consistency
option = option.lower()
if i not in pyspedas.tplot_tools.data_quants.keys():
logging.info(str(i) + " is currently not in pyspedas.")
return
elif option in ['color', 'colors', 'col', 'cols', 'line_color', 'line_colors']:
if isinstance(value, list):
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['line_color'] = value
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['line_color'] = [value]
elif option == 'link':
if isinstance(value, list):
pyspedas.link(i, value[1], value[0])
elif option in ['annotation', 'annotations']:
# It is probably more convenient to use the annotations() wrapper function
# to manage annotations
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['annotations'] = value
elif option == 'colormap':
if isinstance(value, list):
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['colormap'] = value
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['colormap'] = [value]
elif option == 'second_axis_size':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['second_axis_size'] = value
elif option == 'spec':
_reset_plots(i)
if value:
if 'spec_bins' not in pyspedas.tplot_tools.data_quants[i].coords:
logging.warning(f"{i} does not contain coordinates for spectrogram plotting. Continuing...")
continue
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec'] = value
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = get_y_range(pyspedas.tplot_tools.data_quants[i])
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec'] = value
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = get_y_range(pyspedas.tplot_tools.data_quants[i])
# Set the default dimension to plot by. All others will be summed over.
if 'spec_dim_to_plot' not in pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']:
if 'v' in pyspedas.tplot_tools.data_quants[i].coords:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = 'v'
elif 'v2' in pyspedas.tplot_tools.data_quants[i].coords:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = 'v2'
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = 'v1'
elif option in ['legend_names', 'labels', 'legend_name', 'legend_label', 'legend_labels']:
if isinstance(value, list):
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_names'] = value
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_names'] = [value]
elif option in ['legend_location', 'labels_location', 'legends_location', 'label_location', 'labels_location']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_location'] = value
elif option in ['legend_size', 'labels_size', 'label_size']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_size'] = value
elif option in ['legend_shadow', 'labels_shadow', 'label_shadow']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_shadow'] = value
elif option in ['legend_title', 'label_title', 'labels_title']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_title'] = value
elif option in ['legend_titlesize', 'label_titlesize', 'labels_titlesize']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_titlesize'] = value
elif option in ['legend_color', 'legends_color','label_color','labels_color']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_color'] = value
elif option in ['legend_edgecolor', 'label_edgecolor', 'labels_edgecolor']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_edgecolor'] = value
elif option in ['legend_facecolor', 'label_facecolor', 'labels_facecolor']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_facecolor'] = value
elif option in ['legend_markerfirst', 'label_markerfirst', 'labels_markerfirst']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_markerfirst'] = value
elif option in ['legend_markerscale', 'label_markerscale', 'labels_markerscale']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_markerscale'] = value
elif option in ['legend_linewidth', 'label_linewidth', 'labels_linewidth']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_linewidth'] = value
elif option in ['legend_frameon', 'label_frameon', 'labels_frameon']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_frameon'] = value
elif option in ['legend_ncols', 'labels_ncols', 'label_ncols']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_ncols'] = value
elif option == 'xlog_slice':
if value:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['slice_xaxis_opt']['xi_axis_type'] = 'log'
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['slice_xaxis_opt']['xi_axis_type'] = 'linear'
elif option == 'ylog':
negflag = 0 # _ylog_check(data_quants, value, i)
if negflag == 0 and value:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'log'
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'linear'
elif option == 'ylog_slice':
if value:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['slice_yaxis_opt']['yi_axis_type'] = 'log'
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['slice_yaxis_opt']['yi_axis_type'] = 'linear'
elif option == 'zlog':
# check for negative values and warn the user that they will be ignored
negflag = _zlog_check(pyspedas.tplot_tools.data_quants, value, i)
if negflag != 0 and value:
logging.warning(str(i) + ' contains negative values; setting the z-axis to log scale will cause the negative values to be ignored on figures.')
if value:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'log'
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'linear'
elif option =='visible':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['visible'] = bool(value)
elif option =='nodata':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['visible'] = not bool(value)
# Obsolete? (except for value='none'?) JWL 2024-03-21
# These don't seem to be the correct format for matplotlib parameterized line styles.
elif option in ['line_style', 'linestyle', 'line_style_name']:
if value == 0 or value == 'solid_line':
to_be = []
elif value == 1 or value == 'dot':
to_be = [2, 4]
elif value == 2 or value == 'dash':
to_be = [6]
elif value == 3 or value == 'dash_dot':
to_be = [6, 4, 2, 4]
elif value == 4 or value == 'dash_dot_dot_dot':
to_be = [6, 4, 2, 4, 2, 4, 2, 4]
elif value == 5 or value == 'long_dash':
to_be = [10]
else:
to_be=value
# This does not appear to be used by tplot. JWL 2024-03-21
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['line_style'] = to_be
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['line_style_name'] = _convert_to_matplotlib_linestyle(value)
# unused?
if(value == 6 or value == 'none'):
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['visible'] = False
elif option in ['char_size', 'charsize']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['char_size'] = value
elif option in ['var_label_format', 'varlabel_format']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['var_label_format'] = value
elif option in ['name', 'title']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['title'] = value
elif option == "panel_size":
if value > 1 or value <= 0:
logging.info("Invalid panel_size value (%f). Should be in (0, 1]",value)
return
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['panel_size'] = value
elif option == 'alpha':
if value > 1 or value < 0:
logging.info("Invalid alpha value (%f). Should be [0, 1]",value)
return
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['alpha'] = value
elif option in ['marker', 'markers']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['marker'] = value
elif option == 'errorevery':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['errorevery'] = value
elif option == 'capsize':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['capsize'] = value
elif option == 'ecolor':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['ecolor'] = value
elif option == 'elinewidth':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['elinewidth'] = value
elif option in ['marker_size', 'markersize']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['marker_size'] = value
elif option in ['markevery', 'markerevery', 'mark_every', 'marker_every']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['markevery'] = value
elif option in ['symbols', 'symbol']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['symbols'] = value
elif option == 'xtick_length':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['xtick_length'] = value
elif option == 'ytick_length':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['ytick_length'] = value
elif option == 'xtick_width':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['xtick_width'] = value
elif option == 'ytick_width':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['ytick_width'] = value
elif option == 'xtick_color':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['xtickcolor'] = value
elif option == 'ytick_color':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['ytickcolor'] = value
elif option == 'xtick_labelcolor':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['xtick_labelcolor'] = value
elif option == 'ytick_labelcolor':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['ytick_labelcolor'] = value
elif option == 'xtick_direction':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['xtick_direction'] = value
elif option == 'ytick_direction':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['ytick_direction'] = value
elif option == 'right_axis':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['right_axis'] = value
elif option in ['thick', 'line_width']:
if isinstance(value, list):
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['line_width'] = value
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['line_opt']['line_width'] = [value]
elif option in ['yrange', 'y_range']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = [value[0], value[1]]
# track whether the yrange option was set by the user
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range_user'] = True
# IDL SPEDAS supports a 3-argument form of yrange, where the third argument selects
# log or linear scaling
if len(value) == 3:
if value[2]:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'log'
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'linear'
elif option == 'y_major_ticks':
# check whether the value is 1D array-like
if isinstance(value, (list, np.ndarray)):
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_major_ticks'] = value
else:
logging.warning('y_major_ticks must be a 1D array-like object')
elif option == 'y_minor_tick_interval':
# check whether the value is a number
if isinstance(value, (int, float)):
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_minor_tick_interval'] = value
else:
logging.warning('y_minor_tick_interval must be a number')
elif option in ['zrange', 'z_range']:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['z_range'] = [value[0], value[1]]
if len(value) == 3:
# IDL SPEDAS supports a 3-argument form of zrange, where the third element specifies linear vs. log scaling.
negflag = _zlog_check(pyspedas.tplot_tools.data_quants, value[2], i)
if negflag != 0 and value:
logging.warning(str(i) + ' contains negative values; setting the z-axis to log scale will cause the negative values to be ignored on figures.')
if value[2]:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'log'
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'linear'
elif option == 'xrange_slice':
plt_opts = pyspedas.tplot_tools.data_quants[i].attrs['plot_options']
if plt_opts.get('slice_xaxis_opt') is not None:
plt_opts['slice_xaxis_opt']['xi_range'] = [value[0], value[1]]
elif option == 'yrange_slice':
plt_opts = pyspedas.tplot_tools.data_quants[i].attrs['plot_options']
if plt_opts.get('slice_yaxis_opt') is not None:
plt_opts['slice_yaxis_opt']['yi_range'] = [value[0], value[1]]
elif option == 'xtitle':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['xaxis_opt']['axis_label'] = value
elif option == 'ytitle':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['axis_label'] = value
elif option == 'ztitle':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['axis_label'] = value
elif option == 'xsubtitle':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['xaxis_opt']['axis_subtitle'] = value
elif option == 'ysubtitle':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['axis_subtitle'] = value
elif option == 'zsubtitle':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['axis_subtitle'] = value
elif option == 'xtitle_color':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['xaxis_opt']['axis_color'] = value
elif option == 'ytitle_color':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['axis_color'] = value
elif option == 'ztitle_color':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['zaxis_opt']['axis_color'] = value
elif option in ['data_gap', 'datagap']: #jmm, 2023-06-20
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['data_gap'] = value
elif option in ['spec_dim_to_plot', 'spec_plot_dim']:
if len(pyspedas.tplot_tools.data_quants[i].values.shape) <= 2:
logging.warning(f"Must have more than 2 coordinate dimensions to set spec_coord_to_plot for {pyspedas.tplot_tools.data_quants[i].name}")
continue
# Set the 'spec_dim_to_plot' value to either 'v' or 'v1', 'v2', 'v3', etc.
if isinstance(value, int):
coord_to_plot = "v" + str(value)
if coord_to_plot not in pyspedas.tplot_tools.data_quants[i].coords:
if value == 1:
coord_to_plot = "v"
if coord_to_plot not in pyspedas.tplot_tools.data_quants[i].coords:
logging.warning(f"Dimension {value} not found in {pyspedas.tplot_tools.data_quants[i].name}")
continue
else:
logging.warning(f"Dimension {value} not found in {pyspedas.tplot_tools.data_quants[i].name}")
continue
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = coord_to_plot
elif isinstance(value, str):
coord_to_plot = value
if coord_to_plot not in pyspedas.tplot_tools.data_quants[i].coords:
logging.warning(f"Dimension {value} not found in {pyspedas.tplot_tools.data_quants[i].name}")
continue
else:
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = value
# If we're plotting against different coordinates, we need to change what we consider the "spec_bins"
pyspedas.tplot_tools.data_quants[i].coords['spec_bins'] = pyspedas.tplot_tools.data_quants[i].coords[coord_to_plot]
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = get_y_range(pyspedas.tplot_tools.data_quants[i])
elif option == 'spec_slices_to_use':
if not isinstance(value, dict):
logging.error("Must be a dictionary object in the format {'v2':15, 'v3':7}")
return
else:
for coord in value:
if coord not in pyspedas.tplot_tools.data_quants[i].coords:
logging.warning(f"Dimension {coord} not found in {pyspedas.tplot_tools.data_quants[i].name}")
continue
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['spec_slices_to_use'] = value
elif option == 'border':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['extras']['border'] = value
elif option == 'y_interp':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_interp'] = value
elif option == 'y_interp_points':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_interp_points'] = value
elif option == 'x_interp':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['x_interp'] = value
elif option == 'x_interp_points':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['x_interp_points'] = value
elif option == 'y_no_resample':
pyspedas.tplot_tools.data_quants[i].attrs['plot_options']['yaxis_opt']['y_no_resample'] = value
else:
# Apparently cdf_to_tplot is treating all variable attributes as potential plot
# options. Adding this warning will end up spamming the logs unless cdf_to_tplot is changed.
if not quiet:
logging.warning(f"Unrecognized option {option}")
#pass
return
def _ylog_check(data_quants, value, i):
negflag = 0
namedata = data_quants[i]
# check variable data
# if negative numbers, don't allow log setting
datasets = [namedata]
for oplot_name in namedata.attrs['plot_options']['overplots']:
datasets.append(data_quants[oplot_name])
if value == 1:
for dataset in datasets:
if 'spec' not in dataset.attrs['plot_options']['extras']:
if dataset.min(skipna=True) < 0:
logging.warning('Negative data is incompatible with log plotting.')
negflag = 1
break
else:
if dataset.attrs['plot_options']['extras']['spec'] == 1:
if dataset.coords['spec_bins'].min(skipna=True) < 0:
logging.warning('Negative data is incompatible with log plotting.')
negflag = 1
break
elif value != 1:
# Using the 'negflag' as a way to not log something if the user doesn't want it to be logged
negflag = 1
return negflag
def _zlog_check(data_quants, value, i):
negflag = 0
namedata = data_quants[i]
# check variable data
# if negative numbers, don't allow log setting
datasets = [namedata]
for oplot_name in namedata.attrs['plot_options']['overplots']:
datasets.append(data_quants[oplot_name])
for dataset in datasets:
if value == 1:
if 'spec' in dataset.attrs['plot_options']['extras']:
if dataset.attrs['plot_options']['extras']['spec'] == 1:
if dataset.min(skipna=True) < 0:
negflag = 1
break
elif value != 1:
# Using the 'negflag' as a way to not log something if the user doesn't want it to be logged
negflag = 1
return negflag
def _reset_plots(name):
if isinstance(pyspedas.tplot_tools.data_quants[name], dict): # non-record varying variable
return
pyspedas.tplot_tools.data_quants[name].attrs['plot_options']['extras']['spec'] = 0
pyspedas.tplot_tools.data_quants[name].attrs['plot_options']['extras']['alt'] = 0
pyspedas.tplot_tools.data_quants[name].attrs['plot_options']['extras']['map'] = 0
pyspedas.tplot_tools.data_quants[name].attrs['plot_options']['extras']['plotter'] = None
def _convert_to_matplotlib_linestyle(linestyle):
if not isinstance(linestyle,list):
linestyle = [linestyle]
converted_linestyles = []
for ls in linestyle:
if ls == 'solid_line':
converted_linestyles.append('solid')
elif ls == 'dot':
converted_linestyles.append('dotted')
elif ls == 'dash':
converted_linestyles.append('dashed')
elif ls == 'dash_dot':
converted_linestyles.append('dashdot')
else:
converted_linestyles.append(ls)
return converted_linestyles