Base Plot Configuration Pool
Contents
Base Plot Configuration Pool#
This page documents dantro’s base plot configuration pool, sorted by segments and using the naming convention.
Hint
To quickly search for individual entries, the search functionality of your browser (Cmd + F) may be very helpful.
Note that some entries (like those of the YAML anchors) may only be found if the complete file reference is expanded.
.defaults: default entries#
# This section defines defaults that are (meant to be) used in all plots.
# These find their way into the plot configuration via the `.creator` configs.
# .. Aggregated defaults ......................................................
.defaults:
based_on:
- .hlpr.tight_layout
- .defaults.style
- .defaults.file_ext
# .. Individual defaults ......................................................
.defaults.style:
based_on:
- .style.use_grid
style:
base_style: ~
figure.dpi: 254 # important also for PDF to avoid rasterization bugs
lines.linewidth: 1.2
axes.prop_cycle: *cy_tab20_split
legend.fontsize: x-small
.defaults.file_ext:
file_ext: pdf
.creator: selecting a plot creator#
More information: Plot Creators
.creator.base:
based_on: .defaults
creator: base
.creator.pyplot:
based_on: .defaults
creator: pyplot
.creator.universe:
based_on: .defaults
creator: universe
universes: all
.creator.multiverse:
based_on: .defaults
creator: multiverse
# .. Specializations ..........................................................
.creator.universe.any:
based_on: .creator.universe
universes: any
.creator.universe.first:
based_on: .creator.universe
universes: first
.creator.universe.all:
based_on: .creator.universe
universes: all
.plot: selecting a plot function#
More information:
# -- Facet grid ---------------------------------------------------------------
.plot.facet_grid:
module: !add [*dantro_plots, .generic]
plot_func: facet_grid
# .. Modifiers ................................................................
.plot.facet_grid.with_auto_encoding:
based_on: .plot.facet_grid
auto_encoding: true
col_wrap: auto
.plot.facet_grid.with_auto_kind:
based_on: .plot.facet_grid
kind: auto
# .. Specializations: working on xr.DataArray .................................
.plot.facet_grid.line:
based_on: .plot.facet_grid
kind: line
.plot.facet_grid.step:
based_on: .plot.facet_grid
kind: step
.plot.facet_grid.errorbars:
based_on: .plot.facet_grid
kind: errorbars
.plot.facet_grid.errorbands:
based_on: .plot.facet_grid.errorbars
use_bands: true
.plot.facet_grid.hist:
based_on: .plot.facet_grid
kind: hist
.plot.facet_grid.pcolormesh:
based_on: .plot.facet_grid
kind: pcolormesh
.plot.facet_grid.contour:
based_on: .plot.facet_grid
kind: contour
.plot.facet_grid.contourf:
based_on: .plot.facet_grid
kind: contourf
.plot.facet_grid.imshow:
based_on: .plot.facet_grid
kind: imshow
# .. Specializations: working on xr.Dataset ...................................
.plot.facet_grid.scatter:
based_on: .plot.facet_grid
kind: scatter
edgecolor: none
.plot.facet_grid.scatter3d:
based_on:
- .plot.facet_grid
- .hlpr.projection.3d
kind: scatter3d
# For faceting, projection needs to be set via xr.plot.FacetGrid.
# For the non-faceting case, `.hlpr.projection3d` takes care of that.
subplot_kws:
projection: 3d
# Need to set some better defaults
cbar_kwargs:
pad: 0.1
sharex: False
sharey: False
helpers:
subplots_adjust:
wspace: 0.1
hspace: 0.1
# -- Multiplot ----------------------------------------------------------------
.plot.multiplot:
module: !add [*dantro_plots, .multiplot]
plot_func: multiplot
# -- Legacy plots -------------------------------------------------------------
.plot.lineplot:
module: !add [*dantro_plots, .basic]
plot_func: lineplot
.style: choosing plot style#
More information: Adjusting a Plot’s Style
# More information:
# https://matplotlib.org/gallery/style_sheets/style_sheets_reference.html
# https://matplotlib.org/stable/tutorials/introductory/customizing.html
.style.use_grid:
style:
axes.grid: true
grid.linewidth: .4
grid.alpha: .5
.style.no_grid:
style:
axes.grid: false
.style.use_tex:
style:
text.usetex: true
# Requires LaTeX to be installed
# More info: https://matplotlib.org/tutorials/text/pgf.html
# -- Property cyclers ---------------------------------------------------------
.style.prop_cycle.tab20:
style:
axes.prop_cycle: *cy_tab20
.style.prop_cycle.tab20_split:
style:
axes.prop_cycle: *cy_tab20_split
.hlpr: invoking individual plot helper functions#
More information: The PlotHelper
# .. Figure setup .............................................................
.hlpr.projection.3d:
helpers:
setup_figure:
subplot_kw:
projection: 3d
# .. Saving a figure ..........................................................
.hlpr.tight_layout:
helpers:
save_figure:
bbox_inches: tight
.hlpr.no_tight_layout:
helpers:
save_figure:
bbox_inches: ~
# .. Limits ...................................................................
.hlpr.limits.x.min_max:
helpers:
set_limits:
x: [min, max]
.hlpr.limits.x.from_zero:
helpers:
set_limits:
x: [0, ~]
.hlpr.limits.y.min_max:
helpers:
set_limits:
y: [min, max]
.hlpr.limits.y.from_zero:
helpers:
set_limits:
y: [0, ~]
.hlpr.limits.z.min_max:
helpers:
set_limits:
z: [min, max]
.hlpr.limits.z.from_zero:
helpers:
set_limits:
z: [0, ~]
# .. Scales ...................................................................
.hlpr.scales.x.log_hist:
helpers:
set_scales:
x: &symlog_thresh1
scale: symlog
linthresh: 1
.hlpr.scales.y.log_hist:
helpers:
set_scales:
y:
<<: *symlog_thresh1
.hlpr.scales.z.log_hist:
helpers:
set_scales:
z:
<<: *symlog_thresh1
# .. Lines ....................................................................
.hlpr.lines.h_zero:
helpers:
set_hv_lines:
hlines:
- pos: 0.
<<: *style_hvline
.hlpr.lines.v_zero:
helpers:
set_hv_lines:
vlines:
- pos: 0.
<<: *style_hvline
# .. Legend ...................................................................
.hlpr.legend.use:
helpers:
set_legend:
use_legend: true
.hlpr.legend.gather_from_fig:
helpers:
set_legend:
use_legend: true
gather_from_fig: true
.hlpr.legend.hide:
helpers:
set_legend:
use_legend: false
.hlpr.legend.hide_if_large:
helpers:
set_legend:
use_legend: true
hiding_threshold: 10
# .. Figure legend ............................................................
.hlpr.figlegend.use:
helpers:
set_figlegend:
gather_from_fig: true
.hlpr.figlegend.hide_if_large:
helpers:
set_figlegend:
gather_from_fig: true
hiding_threshold: 10
# .. Automatically formatting x tick labels (on figure level) .................
.hlpr.autofmt_xdate:
helpers:
autofmt_xdate:
enabled: true
# .. Tick locators and formatters .............................................
.hlpr.ticks.x.hide:
helpers:
set_ticks:
x: &hide_major
major:
locs: []
labels: []
.hlpr.ticks.y.hide:
helpers:
set_ticks:
y:
<<: *hide_major
.hlpr.ticks.z.hide:
helpers:
set_ticks:
z:
<<: *hide_major
.hlpr.ticks.x.si_suffixes:
helpers:
set_tick_formatters:
x:
major: &eng_formatter
name: EngFormatter
# places: 0
sep: '$\,$'
.hlpr.ticks.y.si_suffixes:
helpers:
set_tick_formatters:
y:
major:
<<: *eng_formatter
.hlpr.ticks.z.si_suffixes:
helpers:
set_tick_formatters:
z:
major:
<<: *eng_formatter
.hlpr.ticks.x.fewer_ticks:
helpers:
set_tick_locators:
x:
major: &ticker_maxn_fewer
name: MaxNLocator
nbins: 5 # --> max. 6 ticks
steps: [1, 2, 5, 10]
min_n_ticks: 4
.hlpr.ticks.y.fewer_ticks:
helpers:
set_tick_locators:
y:
major:
<<: *ticker_maxn_fewer
.hlpr.ticks.z.fewer_ticks:
helpers:
set_tick_locators:
z:
major:
<<: *ticker_maxn_fewer
.hlpr.ticks.x.date:
helpers:
set_tick_formatters:
x:
major: &date_formatter
name: DateFormatter
args: ["%Y-%m-%d"]
.hlpr.ticks.y.date:
helpers:
set_tick_formatters:
y:
major:
<<: *date_formatter
.hlpr.ticks.z.date:
helpers:
set_tick_formatters:
z:
major:
<<: *date_formatter
.animation: controlling animation#
More information: Animations
.animation.defaults:
based_on:
- .animation.use_frames # ffmpeg might not be installed
animation:
writer_kwargs:
frames:
saving:
dpi: 92
ffmpeg:
init:
fps: 10
saving:
dpi: 92
.animation.enabled:
based_on: .animation.defaults
animation:
enabled: true
.animation.disabled:
based_on:
- .animation.defaults
- .defaults.file_ext
animation:
enabled: false
.animation.use_ffmpeg:
file_ext: mp4
animation:
writer: ffmpeg
.animation.use_frames:
based_on:
- .defaults.file_ext
animation:
writer: frames
.animation.high_dpi:
animation:
writer_kwargs:
frames:
saving:
dpi: 144
ffmpeg:
saving:
dpi: 144
.animation.higher_dpi:
animation:
writer_kwargs:
frames:
saving:
dpi: 254
ffmpeg:
saving:
dpi: 254
.dag: configuring the DAG framework#
More information:
# -- Options ------------------------------------------------------------------
# .. Verbosity ................................................................
.dag.quiet:
dag_options:
verbosity: 0
.dag.verbose:
dag_options:
verbosity: 2
# .. Caching ..................................................................
.dag.cache.disabled:
dag_options:
file_cache_defaults:
read: false
write: false
.dag.cache.use:
dag_options:
file_cache_defaults:
read: true
write:
enabled: true
min_compute_time: 1.
.dag.cache.read_only:
dag_options:
file_cache_defaults:
read: true
write: false
# .. TransformationDAG object cache ...........................................
.dag.object_cache.use:
dag_object_cache:
read: true
write: true
use_copy: false
.dag.object_cache.disabled:
dag_object_cache:
read: false
write: false
.dag.object_cache.clear:
based_on: .dag.object_cache.use
dag_object_cache:
write: false
clear: true
collect_garbage: true
# .. Aggregated DAG default options ...........................................
.dag.defaults:
based_on:
- .dag.cache.use
- .dag.object_cache.use
dag_options:
verbosity: 1
# -- Visualization ------------------------------------------------------------
# Parameters controlling DAG visualization
.dag.vis.defaults:
based_on:
- .dag.vis.enabled
- .dag.vis.style
# .. Controlling when to generate a visualization .............................
.dag.vis.disabled:
dag_visualization:
enabled: false
.dag.vis.enabled:
dag_visualization:
enabled: true
.dag.vis.always:
dag_visualization:
enabled: true
when:
always: true
only_once: true
.dag.vis.only_on_error:
dag_visualization:
enabled: true
when:
on_compute_error: true
on_plot_error: true
.dag.vis.only_in_debug_mode:
dag_visualization:
enabled: true
when:
on_compute_error: debug
on_plot_error: debug
# .. Controlling DAG visualization style ......................................
.dag.vis.style:
dag_visualization: {}
# NOTE Will add entries here in the future
# -- Definitions --------------------------------------------------------------
# The entries below set certain tags using the `dag_options.define` argument.
# This should not be confused with the .dag.meta_ops defined below.
.dag.define.defaults:
based_on:
- .dag.define._SkipPlot
# The `_skip_plot` tag can be used as a fallback option and will trigger the
# plot to be skipped if the fallback is used.
# Usage:
# - ...
# allow_failure: true
# fallback: !dag_tag _skip_plot
#
.dag.define._SkipPlot:
dag_options:
define:
_skip_plot:
- operation: raise_SkipPlot
args: [true]
# Imports and wraps a bunch of seaborn functions that can be invoked elsewhere.
# Usage:
# - call: [!dag_tag _create_sns_palette, "husl", 9]
#
.dag.define.sns_cmap_funcs:
dag_options:
define:
_create_sns_palette:
- import: [seaborn, color_palette]
- import_and_call: [functools, partial, !dag_prev ]
_create_sns_cmap:
- import: [seaborn, color_palette]
- import_and_call: [functools, partial, !dag_prev ]
kwargs:
as_cmap: true
_create_sns_diverging_cmap:
- import: [seaborn, diverging_palette]
- import_and_call: [functools, partial, !dag_prev ]
kwargs:
as_cmap: true
.dag.meta_ops: meta operations#
The following entries can be included into a plot configuration to make pre-defined meta-operations available for the data transformation framework.
Example
As an example, let’s include the .dag.meta_ops.compute_mean_and_stddev operation to calculate these values over the time and space dimensions and combine them into an xarray.Dataset.
This approach is very useful for generating a errorbars facet grid plot.
Also note how two further meta-operations are included additionally to create a rolling mean of the data and transform a coordinate dimension into a format that matplotlib accepts.
based_on:
# select the creator and use the errorbands plot function
- .creator.pyplot
- .plot.facet_grid.errorbands
# include some meta operations
- .dag.meta_ops.compute_mean_and_stddev
- .dag.meta_ops.rolling
- .dag.meta_ops.transform.coords.date2num
# call some pre-defined helpers
- .hlpr.ticks.x.date
- .hlpr.autofmt_xdate
- .hlpr.limits.x.min_max
# always create a DAG visualization
- .dag.vis.defaults
- .dag.vis.always
select:
air_temps:
path: xr_tutorial/arrays/air_temperature
transform:
- .squeeze_with_drop
# for matplotlib to accept this, need to transform the time coords
- .transform.coords.date2num: [!dag_prev , time]
transform:
# Compute the mean and standard deviation using included meta-operation
- compute_mean_and_stddev: [!dag_tag air_temps, [lat, lon]]
# Apply a rolling mean over 10 data points
- rolling.mean: [!dag_prev , {time: 10}]
tag: data
# Specify which data variable to plot as line and which as errorbands
x: time
y: mean
yerr: stddev
# Pretty it up a bit using helpers
helpers:
set_labels:
x: Time
y: Temperature [K]
set_title:
title: Mean Air Temperature
For background information on this dataset and example, have a look at the xarray documentation.
# The following entries can be included into a plot configuration to make
# certain meta-operations available for the data transformation framework.
# .. Data selection operations ................................................
.dag.meta_ops.select_all:
dag_options:
meta_operations:
#
# Explicitly select all elements.
# This can be called on a dantro LabelledDataGroup to resolve all data.
#
# Args:
# 0: The object to call `.sel` on
#
select_all:
- operation: .sel
args: [!arg 0]
kwargs: {} # equivalent to {combination_method: auto}
# .. Computation ..............................................................
.dag.meta_ops.compute_mean_and_stddev:
dag_options:
meta_operations:
#
# Compute mean and std over some dimensions and combine it into a dataset
#
# Args:
# 0: The xr.DataArray to calculate the values from
# 1 (optional): Dimension names to reduce, if not given reduces all
#
# Returns:
# xr.Dataset with data variables `mean` and `stddev`
#
compute_mean_and_stddev:
- define: !arg 0
tag: data
- define: !arg [1, ~]
tag: dims
- .mean: [!dag_tag data, !dag_tag dims]
tag: mean
- .std: [!dag_tag data, !dag_tag dims]
tag: stddev
- xr.Dataset:
- mean: !dag_tag mean
stddev: !dag_tag stddev
.dag.meta_ops.rolling:
dag_options:
define:
# A default window for `.rolling` operations on time dimension.
# Still needs to be passed explicitly.
_rolling_time_window: {time: 5}
meta_operations:
#
# Performs a rolling-window operation on an xr.DataArray
#
# Note: This exposes only part of the interface ...
#
# Args:
# 0: the data to call `.rolling` on
# 1: the window operation name, e.g. `mean`
# 2: window arguments, e.g. `{time: 5}`, can also use the
# pre-defined `!dag_tag _rolling_time_window` here.
# center: (optional, default: false) whether to center the coordinates
# on the windows (default: false)
# min_periods: (optional, default: None) Minimum number of
# observations in window required to have a value (otherwise
# result is NaN). If None, uses the window size.
#
rolling:
- .rolling: [!arg 0, !arg 2]
kwargs:
center: !kwarg [center, false]
min_periods: !kwarg [min_periods, ~]
- callattr: [!dag_prev , !arg 1]
#
# Special case of rolling *mean*
#
# Args:
# 0: the data to call `.rolling` on
# 1: window arguments, e.g. `{time: 5}` or the pre-defined
# `!dag_tag _rolling_time_window`
#
rolling.mean:
- rolling: [!arg 0 , mean, !arg 1]
# .. Coordinate transformations ...............................................
.dag.meta_ops.transform.coords.date2num:
dag_options:
meta_operations:
#
# Applies the matplotlib.dates.date2num operation to the specified
# coordinate dimensions.
# This becomes necessary if trying to use np.datetime objects for ticks.
#
# Args:
# 0: the data with the to-be-transformed coordinates
# 1: names of the coordinate dimensions to transform using date2num
#
.transform.coords.date2num:
- define: !arg 0
tag: d
- define: !arg 1
tag: dim
- import: [matplotlib.dates, date2num]
- .coords.transform: [!dag_tag d, !dag_tag dim, !dag_prev ]
# .. Misc .....................................................................
.dag.meta_ops.as_dataset:
dag_options:
meta_operations:
#
# Loads a dantro group into a xr.Dataset
#
# Args:
# 0: the group to load data from
# 1: paths of properties to load as data variables
#
as_dataset:
- call_lambda:
- "lambda grp, only: {k:v.data for k, v in grp.items() if k in only}"
- !arg 0
- !arg 1
- xr.Dataset
Complete File Reference#
# dantro base plot configuration pool
---
# YAML variable definitions that are used below to avoid repetition
_:
variables:
plots_module: &dantro_plots dantro.plot.funcs
aesthetics:
hvline: &style_hvline
linestyle: solid
color: grey
alpha: .4
linewidth: 2.
zorder: -42
# Defaults for a colorbar
# https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.colorbar.html
cbar_kwargs: &cbar_kwargs
shrink: .65
aspect: 30
orientation: vertical
pad: 0.05
colors: {}
cyclers:
# -- General purpose qualitative cyclers, based on tab20
tab20: &cy_tab20 >
cycler("color", ["1f77b4", "aec7e8", "ff7f0e", "ffbb78", "2ca02c",
"98df8a", "d62728", "ff9896", "9467bd", "c5b0d5",
"8c564b", "c49c94", "e377c2", "f7b6d2", "7f7f7f",
"c7c7c7", "bcbd22", "dbdb8d", "17becf", "9edae5"])
tab20_split: &cy_tab20_split >
cycler("color", ["1f77b4", "ff7f0e", "2ca02c", "d62728", "9467bd",
"8c564b", "e377c2", "7f7f7f", "bcbd22", "17becf",
"aec7e8", "ffbb78", "98df8a", "ff9896", "c5b0d5",
"c49c94", "f7b6d2", "c7c7c7", "dbdb8d", "9edae5"])
# =============================================================================
# ╔╦╗╔═╗╔═╗╔═╗╦ ╦╦ ╔╦╗╔═╗
# ║║║╣ ╠╣ ╠═╣║ ║║ ║ ╚═╗
# ═╩╝╚═╝╚ ╩ ╩╚═╝╩═╝╩ ╚═╝
# =============================================================================
# start: .defaults
# This section defines defaults that are (meant to be) used in all plots.
# These find their way into the plot configuration via the `.creator` configs.
# .. Aggregated defaults ......................................................
.defaults:
based_on:
- .hlpr.tight_layout
- .defaults.style
- .defaults.file_ext
# .. Individual defaults ......................................................
.defaults.style:
based_on:
- .style.use_grid
style:
base_style: ~
figure.dpi: 254 # important also for PDF to avoid rasterization bugs
lines.linewidth: 1.2
axes.prop_cycle: *cy_tab20_split
legend.fontsize: x-small
.defaults.file_ext:
file_ext: pdf
# =============================================================================
# ╔═╗╦ ╔═╗╔╦╗ ╔═╗╦═╗╔═╗╔═╗╔╦╗╔═╗╦═╗╔═╗
# ╠═╝║ ║ ║ ║ ║ ╠╦╝║╣ ╠═╣ ║ ║ ║╠╦╝╚═╗
# ╩ ╩═╝╚═╝ ╩ ╚═╝╩╚═╚═╝╩ ╩ ╩ ╚═╝╩╚═╚═╝
# =============================================================================
# start: .creator
.creator.base:
based_on: .defaults
creator: base
.creator.pyplot:
based_on: .defaults
creator: pyplot
.creator.universe:
based_on: .defaults
creator: universe
universes: all
.creator.multiverse:
based_on: .defaults
creator: multiverse
# .. Specializations ..........................................................
.creator.universe.any:
based_on: .creator.universe
universes: any
.creator.universe.first:
based_on: .creator.universe
universes: first
.creator.universe.all:
based_on: .creator.universe
universes: all
# =============================================================================
# ╔═╗╦ ╔═╗╔╦╗ ╔═╗╦ ╦╔╗╔╔═╗╔╦╗╦╔═╗╔╗╔╔═╗
# ╠═╝║ ║ ║ ║ ╠╣ ║ ║║║║║ ║ ║║ ║║║║╚═╗
# ╩ ╩═╝╚═╝ ╩ ╚ ╚═╝╝╚╝╚═╝ ╩ ╩╚═╝╝╚╝╚═╝
# =============================================================================
# start: .plot
# -- Facet grid ---------------------------------------------------------------
.plot.facet_grid:
module: !add [*dantro_plots, .generic]
plot_func: facet_grid
# .. Modifiers ................................................................
.plot.facet_grid.with_auto_encoding:
based_on: .plot.facet_grid
auto_encoding: true
col_wrap: auto
.plot.facet_grid.with_auto_kind:
based_on: .plot.facet_grid
kind: auto
# .. Specializations: working on xr.DataArray .................................
.plot.facet_grid.line:
based_on: .plot.facet_grid
kind: line
.plot.facet_grid.step:
based_on: .plot.facet_grid
kind: step
.plot.facet_grid.errorbars:
based_on: .plot.facet_grid
kind: errorbars
.plot.facet_grid.errorbands:
based_on: .plot.facet_grid.errorbars
use_bands: true
.plot.facet_grid.hist:
based_on: .plot.facet_grid
kind: hist
.plot.facet_grid.pcolormesh:
based_on: .plot.facet_grid
kind: pcolormesh
.plot.facet_grid.contour:
based_on: .plot.facet_grid
kind: contour
.plot.facet_grid.contourf:
based_on: .plot.facet_grid
kind: contourf
.plot.facet_grid.imshow:
based_on: .plot.facet_grid
kind: imshow
# .. Specializations: working on xr.Dataset ...................................
.plot.facet_grid.scatter:
based_on: .plot.facet_grid
kind: scatter
edgecolor: none
.plot.facet_grid.scatter3d:
based_on:
- .plot.facet_grid
- .hlpr.projection.3d
kind: scatter3d
# For faceting, projection needs to be set via xr.plot.FacetGrid.
# For the non-faceting case, `.hlpr.projection3d` takes care of that.
subplot_kws:
projection: 3d
# Need to set some better defaults
cbar_kwargs:
pad: 0.1
sharex: False
sharey: False
helpers:
subplots_adjust:
wspace: 0.1
hspace: 0.1
# -- Multiplot ----------------------------------------------------------------
.plot.multiplot:
module: !add [*dantro_plots, .multiplot]
plot_func: multiplot
# -- Legacy plots -------------------------------------------------------------
.plot.lineplot:
module: !add [*dantro_plots, .basic]
plot_func: lineplot
# =============================================================================
# ╔═╗╔╦╗╦ ╦╦ ╔═╗
# ╚═╗ ║ ╚╦╝║ ║╣
# ╚═╝ ╩ ╩ ╩═╝╚═╝
# =============================================================================
# start: .style
# More information:
# https://matplotlib.org/gallery/style_sheets/style_sheets_reference.html
# https://matplotlib.org/stable/tutorials/introductory/customizing.html
.style.use_grid:
style:
axes.grid: true
grid.linewidth: .4
grid.alpha: .5
.style.no_grid:
style:
axes.grid: false
.style.use_tex:
style:
text.usetex: true
# Requires LaTeX to be installed
# More info: https://matplotlib.org/tutorials/text/pgf.html
# -- Property cyclers ---------------------------------------------------------
.style.prop_cycle.tab20:
style:
axes.prop_cycle: *cy_tab20
.style.prop_cycle.tab20_split:
style:
axes.prop_cycle: *cy_tab20_split
# =============================================================================
# ╔═╗╦ ╔═╗╔╦╗ ╦ ╦╔═╗╦ ╔═╗╔═╗╦═╗╔═╗
# ╠═╝║ ║ ║ ║ ╠═╣║╣ ║ ╠═╝║╣ ╠╦╝╚═╗
# ╩ ╩═╝╚═╝ ╩ ╩ ╩╚═╝╩═╝╩ ╚═╝╩╚═╚═╝
# =============================================================================
# start: .hlpr
# .. Figure setup .............................................................
.hlpr.projection.3d:
helpers:
setup_figure:
subplot_kw:
projection: 3d
# .. Saving a figure ..........................................................
.hlpr.tight_layout:
helpers:
save_figure:
bbox_inches: tight
.hlpr.no_tight_layout:
helpers:
save_figure:
bbox_inches: ~
# .. Limits ...................................................................
.hlpr.limits.x.min_max:
helpers:
set_limits:
x: [min, max]
.hlpr.limits.x.from_zero:
helpers:
set_limits:
x: [0, ~]
.hlpr.limits.y.min_max:
helpers:
set_limits:
y: [min, max]
.hlpr.limits.y.from_zero:
helpers:
set_limits:
y: [0, ~]
.hlpr.limits.z.min_max:
helpers:
set_limits:
z: [min, max]
.hlpr.limits.z.from_zero:
helpers:
set_limits:
z: [0, ~]
# .. Scales ...................................................................
.hlpr.scales.x.log_hist:
helpers:
set_scales:
x: &symlog_thresh1
scale: symlog
linthresh: 1
.hlpr.scales.y.log_hist:
helpers:
set_scales:
y:
<<: *symlog_thresh1
.hlpr.scales.z.log_hist:
helpers:
set_scales:
z:
<<: *symlog_thresh1
# .. Lines ....................................................................
.hlpr.lines.h_zero:
helpers:
set_hv_lines:
hlines:
- pos: 0.
<<: *style_hvline
.hlpr.lines.v_zero:
helpers:
set_hv_lines:
vlines:
- pos: 0.
<<: *style_hvline
# .. Legend ...................................................................
.hlpr.legend.use:
helpers:
set_legend:
use_legend: true
.hlpr.legend.gather_from_fig:
helpers:
set_legend:
use_legend: true
gather_from_fig: true
.hlpr.legend.hide:
helpers:
set_legend:
use_legend: false
.hlpr.legend.hide_if_large:
helpers:
set_legend:
use_legend: true
hiding_threshold: 10
# .. Figure legend ............................................................
.hlpr.figlegend.use:
helpers:
set_figlegend:
gather_from_fig: true
.hlpr.figlegend.hide_if_large:
helpers:
set_figlegend:
gather_from_fig: true
hiding_threshold: 10
# .. Automatically formatting x tick labels (on figure level) .................
.hlpr.autofmt_xdate:
helpers:
autofmt_xdate:
enabled: true
# .. Tick locators and formatters .............................................
.hlpr.ticks.x.hide:
helpers:
set_ticks:
x: &hide_major
major:
locs: []
labels: []
.hlpr.ticks.y.hide:
helpers:
set_ticks:
y:
<<: *hide_major
.hlpr.ticks.z.hide:
helpers:
set_ticks:
z:
<<: *hide_major
.hlpr.ticks.x.si_suffixes:
helpers:
set_tick_formatters:
x:
major: &eng_formatter
name: EngFormatter
# places: 0
sep: '$\,$'
.hlpr.ticks.y.si_suffixes:
helpers:
set_tick_formatters:
y:
major:
<<: *eng_formatter
.hlpr.ticks.z.si_suffixes:
helpers:
set_tick_formatters:
z:
major:
<<: *eng_formatter
.hlpr.ticks.x.fewer_ticks:
helpers:
set_tick_locators:
x:
major: &ticker_maxn_fewer
name: MaxNLocator
nbins: 5 # --> max. 6 ticks
steps: [1, 2, 5, 10]
min_n_ticks: 4
.hlpr.ticks.y.fewer_ticks:
helpers:
set_tick_locators:
y:
major:
<<: *ticker_maxn_fewer
.hlpr.ticks.z.fewer_ticks:
helpers:
set_tick_locators:
z:
major:
<<: *ticker_maxn_fewer
.hlpr.ticks.x.date:
helpers:
set_tick_formatters:
x:
major: &date_formatter
name: DateFormatter
args: ["%Y-%m-%d"]
.hlpr.ticks.y.date:
helpers:
set_tick_formatters:
y:
major:
<<: *date_formatter
.hlpr.ticks.z.date:
helpers:
set_tick_formatters:
z:
major:
<<: *date_formatter
# =============================================================================
# ╔═╗╔╗╔╦╔╦╗╔═╗╔╦╗╦╔═╗╔╗╔
# ╠═╣║║║║║║║╠═╣ ║ ║║ ║║║║
# ╩ ╩╝╚╝╩╩ ╩╩ ╩ ╩ ╩╚═╝╝╚╝
# =============================================================================
# start: .animation
.animation.defaults:
based_on:
- .animation.use_frames # ffmpeg might not be installed
animation:
writer_kwargs:
frames:
saving:
dpi: 92
ffmpeg:
init:
fps: 10
saving:
dpi: 92
.animation.enabled:
based_on: .animation.defaults
animation:
enabled: true
.animation.disabled:
based_on:
- .animation.defaults
- .defaults.file_ext
animation:
enabled: false
.animation.use_ffmpeg:
file_ext: mp4
animation:
writer: ffmpeg
.animation.use_frames:
based_on:
- .defaults.file_ext
animation:
writer: frames
.animation.high_dpi:
animation:
writer_kwargs:
frames:
saving:
dpi: 144
ffmpeg:
saving:
dpi: 144
.animation.higher_dpi:
animation:
writer_kwargs:
frames:
saving:
dpi: 254
ffmpeg:
saving:
dpi: 254
# =============================================================================
# ╔╦╗╔═╗╔═╗ ╔═╗╦═╗╔═╗╔╦╗╔═╗╦ ╦╔═╗╦═╗╦╔═
# ║║╠═╣║ ╦ ╠╣ ╠╦╝╠═╣║║║║╣ ║║║║ ║╠╦╝╠╩╗
# ═╩╝╩ ╩╚═╝ ╚ ╩╚═╩ ╩╩ ╩╚═╝╚╩╝╚═╝╩╚═╩ ╩
# =============================================================================
# start: .dag
# -- Options ------------------------------------------------------------------
# .. Verbosity ................................................................
.dag.quiet:
dag_options:
verbosity: 0
.dag.verbose:
dag_options:
verbosity: 2
# .. Caching ..................................................................
.dag.cache.disabled:
dag_options:
file_cache_defaults:
read: false
write: false
.dag.cache.use:
dag_options:
file_cache_defaults:
read: true
write:
enabled: true
min_compute_time: 1.
.dag.cache.read_only:
dag_options:
file_cache_defaults:
read: true
write: false
# .. TransformationDAG object cache ...........................................
.dag.object_cache.use:
dag_object_cache:
read: true
write: true
use_copy: false
.dag.object_cache.disabled:
dag_object_cache:
read: false
write: false
.dag.object_cache.clear:
based_on: .dag.object_cache.use
dag_object_cache:
write: false
clear: true
collect_garbage: true
# .. Aggregated DAG default options ...........................................
.dag.defaults:
based_on:
- .dag.cache.use
- .dag.object_cache.use
dag_options:
verbosity: 1
# -- Visualization ------------------------------------------------------------
# Parameters controlling DAG visualization
.dag.vis.defaults:
based_on:
- .dag.vis.enabled
- .dag.vis.style
# .. Controlling when to generate a visualization .............................
.dag.vis.disabled:
dag_visualization:
enabled: false
.dag.vis.enabled:
dag_visualization:
enabled: true
.dag.vis.always:
dag_visualization:
enabled: true
when:
always: true
only_once: true
.dag.vis.only_on_error:
dag_visualization:
enabled: true
when:
on_compute_error: true
on_plot_error: true
.dag.vis.only_in_debug_mode:
dag_visualization:
enabled: true
when:
on_compute_error: debug
on_plot_error: debug
# .. Controlling DAG visualization style ......................................
.dag.vis.style:
dag_visualization: {}
# NOTE Will add entries here in the future
# -- Definitions --------------------------------------------------------------
# The entries below set certain tags using the `dag_options.define` argument.
# This should not be confused with the .dag.meta_ops defined below.
.dag.define.defaults:
based_on:
- .dag.define._SkipPlot
# The `_skip_plot` tag can be used as a fallback option and will trigger the
# plot to be skipped if the fallback is used.
# Usage:
# - ...
# allow_failure: true
# fallback: !dag_tag _skip_plot
#
.dag.define._SkipPlot:
dag_options:
define:
_skip_plot:
- operation: raise_SkipPlot
args: [true]
# Imports and wraps a bunch of seaborn functions that can be invoked elsewhere.
# Usage:
# - call: [!dag_tag _create_sns_palette, "husl", 9]
#
.dag.define.sns_cmap_funcs:
dag_options:
define:
_create_sns_palette:
- import: [seaborn, color_palette]
- import_and_call: [functools, partial, !dag_prev ]
_create_sns_cmap:
- import: [seaborn, color_palette]
- import_and_call: [functools, partial, !dag_prev ]
kwargs:
as_cmap: true
_create_sns_diverging_cmap:
- import: [seaborn, diverging_palette]
- import_and_call: [functools, partial, !dag_prev ]
kwargs:
as_cmap: true
# =============================================================================
# ╔╦╗╔═╗╔═╗ ╔╦╗╔═╗╔╦╗╔═╗ ╔═╗╔═╗╔═╗╦═╗╔═╗╔╦╗╦╔═╗╔╗╔╔═╗
# ║║╠═╣║ ╦ ║║║║╣ ║ ╠═╣ ║ ║╠═╝║╣ ╠╦╝╠═╣ ║ ║║ ║║║║╚═╗
# ═╩╝╩ ╩╚═╝ ╩ ╩╚═╝ ╩ ╩ ╩ ╚═╝╩ ╚═╝╩╚═╩ ╩ ╩ ╩╚═╝╝╚╝╚═╝
# =============================================================================
# start: .dag.meta_ops
# The following entries can be included into a plot configuration to make
# certain meta-operations available for the data transformation framework.
# .. Data selection operations ................................................
.dag.meta_ops.select_all:
dag_options:
meta_operations:
#
# Explicitly select all elements.
# This can be called on a dantro LabelledDataGroup to resolve all data.
#
# Args:
# 0: The object to call `.sel` on
#
select_all:
- operation: .sel
args: [!arg 0]
kwargs: {} # equivalent to {combination_method: auto}
# .. Computation ..............................................................
.dag.meta_ops.compute_mean_and_stddev:
dag_options:
meta_operations:
#
# Compute mean and std over some dimensions and combine it into a dataset
#
# Args:
# 0: The xr.DataArray to calculate the values from
# 1 (optional): Dimension names to reduce, if not given reduces all
#
# Returns:
# xr.Dataset with data variables `mean` and `stddev`
#
compute_mean_and_stddev:
- define: !arg 0
tag: data
- define: !arg [1, ~]
tag: dims
- .mean: [!dag_tag data, !dag_tag dims]
tag: mean
- .std: [!dag_tag data, !dag_tag dims]
tag: stddev
- xr.Dataset:
- mean: !dag_tag mean
stddev: !dag_tag stddev
.dag.meta_ops.rolling:
dag_options:
define:
# A default window for `.rolling` operations on time dimension.
# Still needs to be passed explicitly.
_rolling_time_window: {time: 5}
meta_operations:
#
# Performs a rolling-window operation on an xr.DataArray
#
# Note: This exposes only part of the interface ...
#
# Args:
# 0: the data to call `.rolling` on
# 1: the window operation name, e.g. `mean`
# 2: window arguments, e.g. `{time: 5}`, can also use the
# pre-defined `!dag_tag _rolling_time_window` here.
# center: (optional, default: false) whether to center the coordinates
# on the windows (default: false)
# min_periods: (optional, default: None) Minimum number of
# observations in window required to have a value (otherwise
# result is NaN). If None, uses the window size.
#
rolling:
- .rolling: [!arg 0, !arg 2]
kwargs:
center: !kwarg [center, false]
min_periods: !kwarg [min_periods, ~]
- callattr: [!dag_prev , !arg 1]
#
# Special case of rolling *mean*
#
# Args:
# 0: the data to call `.rolling` on
# 1: window arguments, e.g. `{time: 5}` or the pre-defined
# `!dag_tag _rolling_time_window`
#
rolling.mean:
- rolling: [!arg 0 , mean, !arg 1]
# .. Coordinate transformations ...............................................
.dag.meta_ops.transform.coords.date2num:
dag_options:
meta_operations:
#
# Applies the matplotlib.dates.date2num operation to the specified
# coordinate dimensions.
# This becomes necessary if trying to use np.datetime objects for ticks.
#
# Args:
# 0: the data with the to-be-transformed coordinates
# 1: names of the coordinate dimensions to transform using date2num
#
.transform.coords.date2num:
- define: !arg 0
tag: d
- define: !arg 1
tag: dim
- import: [matplotlib.dates, date2num]
- .coords.transform: [!dag_tag d, !dag_tag dim, !dag_prev ]
# .. Misc .....................................................................
.dag.meta_ops.as_dataset:
dag_options:
meta_operations:
#
# Loads a dantro group into a xr.Dataset
#
# Args:
# 0: the group to load data from
# 1: paths of properties to load as data variables
#
as_dataset:
- call_lambda:
- "lambda grp, only: {k:v.data for k, v in grp.items() if k in only}"
- !arg 0
- !arg 1
- xr.Dataset
# =============================================================================