mat_wrap_2d.yaml

# These settings specify the default matplotlib settings when "D figures and subplots are plotted.

# For example, the `GridScatter` section has the following lines:

# GridScatter:
#    figure:
#      c: k
#    subplot:
#      c: k

# This means that when a 2D grid of data is plotted it will use `c=k`, meaning the grid points appear black,
# provided the values of these parameters are not manually set by the user via a `MatPlot2D` object.
#
# In the above example, subplots (e.g. more than one image) will always use `c=k` by default as well.
#
# These configuration options can be customized such that the appearance of figures and subplots for a user is
# optimal for your computer set up.

ArrayOverlay:        # wrapper for `plt.imshow()`: customize arrays overlaid.
  figure:
    alpha: 0.5
  subplot:
    alpha: 0.5
Contour:             # wrapper for `plt.contour()`: customize contours plotted on the figure.
  figure:
    colors: "k"
    total_contours: 10     # Number of contours to plot
    use_log10: true        # If true, contours are plotted with log10 spacing, if False, linear spacing.
    include_values: true   # If true, the values of the contours are plotted on the figure.
  subplot:
    colors: "k"
    total_contours: 10     # Number of contours to plot
    use_log10: true        # If true, contours are plotted with log10 spacing, if False, linear spacing.
    include_values: true   # If true, the values of the contours are plotted on the figure.
BorderScatter:       # wrapper for `plt.scatter()`: customize the apperance of 2D borders.
  figure:
    c: r
    marker: .
    s: 30
  subplot:
    c: r
    marker: .
    s: 10
GridErrorbar:        # wrapper for `plt.errrorbar()`: customize grids with errors.
  figure:
    alpha: 0.5
    c: k
    fmt: o
    linewidth: 5
    marker: o
    markersize: 8
  subplot:
    alpha: 0.5
    c: k
    fmt: o
    linewidth: 5
    marker: o
    markersize: 8
GridPlot:            # wrapper for `plt.plot()`: customize how grids plotted via this method appear.
  figure:
    c: w
  subplot:
    c: w
GridScatter:        # wrapper for `plt.scatter()`: customize appearances of Grid2D.
  figure:
    c: k
    marker: .
    s: 1
  subplot:
    c: k
    marker: .
    s: 1
IndexScatter:        # wrapper for `plt.scatter()`: customize indexes (e.g. data / source plane or frame objects of an Inversion)
  figure:
    c: r,g,b,m,y,k
    marker: .
    s: 20
  subplot:
    c: r,g,b,m,y,k
    marker: .
    s: 20
IndexPlot:        # wrapper for `plt.plot()`: customize indexes (e.g. data / source plane or frame objects of an Inversion)
  figure:
    c: r,g,b,m,y,k
    linewidth: 3
  subplot:
    c: r,g,b,m,y,k
    linewidth: 3
MaskScatter:         # wrapper for `plt.scatter()`: customize the appearance of 2D masks.
  figure:
    c: k
    marker: x
    s: 10
  subplot:
    c: k
    marker: x
    s: 10
MeshGridScatter:     # wrapper for `plt.scatter()`: customize the appearance of mesh grids of Inversions in the source-plane / source-frame.
  figure:
    c: r
    marker: .
    s: 2
  subplot:
    c: r
    marker: .
    s: 2
OriginScatter:       # wrapper for `plt.scatter()`: customize the appearance of the (y,x) origin on figures.
  figure:
    c: k
    marker: x
    s: 80
  subplot:
    c: k
    marker: x
    s: 80
PatchOverlay:        # wrapper for `plt.gcf().gca().add_collection`: customize how overlaid patches appear.
  figure:
    edgecolor: c
    facecolor: null
  subplot:
    edgecolor: c
    facecolor: null
PositionsScatter:    # wrapper for `plt.scatter()`: customize the appearance of positions input via `Visuals2d.positions`.
  figure:
    c: k,m,y,b,r,g
    marker: .
    s: 32
  subplot:
    c: k,m,y,b,r,g
    marker: .
    s: 32
VectorYXQuiver:      # wrapper for `plt.quiver()`: customize (y,x) vectors appearances (e.g. a shear field).
  figure:
    alpha: 1.0
    angles: xy
    headlength: 0
    headwidth: 1
    linewidth: 5
    pivot: middle
    units: xy
  subplot:
    alpha: 1.0
    angles: xy
    headlength: 0
    headwidth: 1
    linewidth: 5
    pivot: middle
    units: xy
DelaunayDrawer:       # wrapper for `plt.fill()`: customize the appearance of Delaunay mesh's.
  figure:
    alpha: 0.7
    edgecolor: k
    linewidth: 0.0
  subplot:
    alpha: 0.7
    edgecolor: k
    linewidth: 0.0  
VoronoiDrawer:       # wrapper for `plt.fill()`: customize the appearance of Voronoi mesh's.
  figure:
    alpha: 0.7
    edgecolor: k
    linewidth: 0.3
  subplot:
    alpha: 0.7
    edgecolor: k
    linewidth: 0.3
ParallelOverscanPlot:
  figure:
    c: k
    linestyle: '-'
    linewidth: 1
  subplot:
    c: k
    linestyle: '-'
    linewidth: 1
SerialOverscanPlot:
  figure:
    c: k
    linestyle: '-'
    linewidth: 1
  subplot:
    c: k
    linestyle: '-'
    linewidth: 1
SerialPrescanPlot:
  figure:
    c: k
    linestyle: '-'
    linewidth: 1
  subplot:
    c: k
    linestyle: '-'
    linewidth: 1