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Plotting data and models with SlimPlotting

title: Overview of SlimPlotting utilities author: Mathias Louboutin date: April 2023 –-

This example script is written using Weave.jl and can be converted to different format for documentation and usage This example is converted to a markdown file for the documentation.

Import SlimPlotting, SegyIO to read seismic data, JLD2 for hdf5-like files

using PythonPlot, SlimPlotting, SegyIO, JLD2

Initialize all needed data

Close all figures if any existing

plotclose("all")
Python: None

Path to the files and data used for these examples

data_path = dirname(pathof(SlimPlotting)) * "/../data/";

Read the data

# Pure array
vp = Float32.(segy_read("$(data_path)2dVP.sgy").data);
dm = diff(vp, dims = 1);
shot = Float32.(segy_read("$(data_path)2dshot.segy").data);
xloc = get_header(segy_read("$(data_path)2dshot.segy"), "GroupX")
fslice = JLD2.load("$(data_path)2dfslice.jld");

Create structures to mimic JUDI-like inputs

In the future this should be instead converted into an extension rather than implicit knowledge of the structure

# Dummy structures to check plot with metadata
struct geometry
    xloc::Any
end

struct shotrec
    data::Any
    dt::Any
    geometry::Any
end

struct Phys
    data::Any
    d::Any
end

## Make physical objects
dmp = Phys(dm, (10, 20))
vpp = Phys(vp, (10, 20))
fslicep = Phys(fslice["Freq"][1, :, :], (12.5, 12.5))
shotp = shotrec([shot], 0.008, geometry([xloc]));

Model perturbation

We plot here a model perturbation (i.e a Reverse-time Migrated image) and compare a few colormaps:

  • The perceptually accurate Greys colormap from colorcet
  • The standard matplotlib Greys colormap
  • Another perceptually accurate Greys colormap from colorcet
figure(figsize = (10, 10))
subplot(311)
plot_simage(dmp; new_fig = false, name = "Colorcet Greys")
subplot(312)
plot_simage(dm, (10, 20); cmap = "Greys", new_fig = false, name = "Greys")
subplot(313)
plot_simage(dm, (10, 20); cmap = :cet_CET_L2, new_fig = false, name = "Colorcet Greys 2")
tight_layout();
display(gcf());
Error: KeyError: key :cet_CET_D1A not found

Velocity

We plot here a velocity model and compare a few colormaps:

  • The perceptually accurate jet colormap from colorcet named cet_rainbow4
  • The ColorSchemes vik colormap
  • The matplotlib jet
figure(figsize = (10, 10))
subplot(311)
plot_velocity(vpp; new_fig = false, name = "colorcet jet", cmap = "cet_rainbow4")
subplot(312)
plot_velocity(vp, (10, 20); cmap = :vik, new_fig = false, name = "ColorSchemes's vik")
subplot(313)
plot_velocity(vp, (10, 20); cmap = "jet", new_fig = false, name = "matplotlib jet")
tight_layout();
display(gcf());
Error: KeyError: key :cet_rainbow4 not found

Frequency slice

We plot here a frequency slice for a seismic dataset and compare a few colormaps:

  • The perceptually accurate bwr colormap from colorcet named cet_CET_D1A
  • The standard matplotlib bwr colormap
  • The matplotlib "bwr
# Frequency slice
figure(figsize = (10, 5))
subplot(131)
plot_fslice(fslice["Freq"][1, :, :], (12.5, 12.5); new_fig = false, name = "colorcet bwr")
subplot(132)
plot_fslice(fslicep; cmap = :bwr, new_fig = false, name = "bwr")
subplot(133)
plot_fslice(fslicep; cmap = "bwr", new_fig = false, name = "Matplotlib bwr")
tight_layout();
display(gcf());
Error: KeyError: key :cet_CET_D1A not found

Shot record

Seismic blue-white-red

We plot here a frequency slice for a seismic dataset and compare a few colormaps for the bwr colormap:

  • The standard matplotlib bwr colormap
  • The perceptually accurate bwr colormap from colorcet named cet_CET_D1A and cet_CET_D1
# Shot record
figure(figsize = (10, 5))
subplot(131)
plot_sdata(shotp; new_fig = false, name = "matplotlib seismic", cmap = "bwr")
subplot(132)
plot_sdata(shot, (12.5, 0.008); cmap = :cet_CET_D1A, new_fig = false, name = "Colorcet bwr")
subplot(133)
plot_sdata(shot, (12.5, 0.008); cmap = :cet_CET_D1, new_fig = false, name = "Colorcet bwr 2")
tight_layout();
display(gcf());
Error: MissingException: No plotting backend found, either PyPlot or Python
Plot need to be loaded in the script

Seismic greys

We plot here a frequency slice for a seismic dataset and compare a few colormaps for the greys colormap:

  • The standard matplotlib gray colormap
  • The perceptually accurate greys colormap from colorcet named cet_CET_L1
# Shot record
figure(figsize = (10, 5))
subplot(121)
plot_sdata(shotp; new_fig = false, name = "colorcet gray", cmap = "cet_CET_L1")
subplot(122)
plot_sdata(shot, (12.5, 0.008); cmap = "gray", new_fig = false, name = "Greys")
tight_layout();
display(gcf());
Error: KeyError: key :cet_CET_L1 not found

Compare shot records

One of the main visual representation of FWI inversion is to compare the true shot record with the synthetic data from the current velocity model. A good way to visualize this difference is to overlay the two shot records alternating the traces between each shots with a different colormap to check the alignment of the events. We show below how to do this with the compare_shots function

figure(figsize = (10, 5))
subplot(131)
compare_shots(shotp, shotp; new_fig = false, name = "Overlap compare")
subplot(132)
compare_shots(
    shotp,
    shotp;
    new_fig = false,
    cmap = ("bwr", "RdBu"),
    name = "Overlap compare custom cmap",
)
subplot(133)
compare_shots(
    shotp,
    shotp;
    side_by_side = true,
    new_fig = false,
    name = "Side by side compare",
)
tight_layout();
display(gcf());
Error: KeyError: key :cet_CET_L1 not found

Wiggle traces

We finally show the traditional wiggle plot for a shot record used in seismic.

# Wiggle plot

figure(figsize=(5, 5))
subplot(111)
wiggle_plot(shot[1:5:end, 1:10:end], xloc[1:10:end], 0:0.02:4.6; new_fig=false)
tight_layout();
display(gcf())
Error: MissingException: No plotting backend found, either PyPlot or Python
Plot need to be loaded in the script