quick_plot

quick_plot is a python script that uses matplotlib to create simple visualizations of data from the command line.

Author

Dent Earl

Dependencies

• Python 2.7
• matplotlib 1.1.0

Installation

1. Download the package.
2. cd into the directory.
3. Type make.

Input file format

The input file may contain comment lines (lines that start with #). Files may contain one or more columns (white space delimited) of numbers

Usage

usage: quick_plot file1 file2 file3... [options]

quick_plot is a tool to produce quick plots. col1 of input file is x value col2 is y
value. If the --mode is column/bar/hist then only col1 is used.

positional arguments:
  files                 files to plot

optional arguments:
  -h, --help            show this help message and exit
  --out OUT             path/filename where figure will be created. No extension needed.
                        default=my_plot
  --mode MODE           plotting mode. may be in (line, scatter, column, bar, hist, tick, barcode,
                        point, contour, density, matrix) default=line
  --columns COLUMNS     two numbers, comma separated, can be reverse order, indicates x,y for
                        plotting. 1-based.
  --downsample DOWNSAMPLE
                        Randomly sample only n values from each input. Can help cutdown on runtime
                        and output size for pdfs.
  --colors COLORS       color palatte mode. may be in (bostock, brewer, mono, hcl_ggplot2)
                        default=brewer
  --color_index_offset COLOR_INDEX_OFFSET
                        index offset value to shift the starting point of the selected color map.
                        default=0
  --alpha ALPHA         alpha value for markers in --mode scatter
  --dot_size MARKERSIZE, --markersize MARKERSIZE
                        value for markers in --mode scatter
  --marker MARKER       Marker to use.
  --linewidth LINEWIDTH
                        Line width for the plot. default=2.0
  --logy                Put the y-axis into log. default=False
  --logx                Put the x-axis into log. default=False
  --title TITLE         Plot title.
  --xlabel XLABEL       X-axis label.
  --ylabel YLABEL       Y-axis label.
  --xmin USER_XMIN      xmin value.
  --xmax USER_XMAX      xmax value.
  --ymin USER_YMIN      ymin value.
  --ymax USER_YMAX      ymax value.
  --height HEIGHT       height of image, in inches. default=4.0
  --width WIDTH         width of image, in inches. default=9.0
  --dpi DPI             dots per inch of raster outputs, i.e. if --outFormat is all or png.
                        default=300
  --out_format OUT_FORMAT
                        output format [pdf|png|eps|all]. default=pdf
  --no_legend           Turns off the filename / color legend. Helpful for large numbers of files.
  --regression          turn on a simple linear regression line
  --jitter              turn on jitter for certain plotting modes
  --random_seed RANDOM_SEED
                        Random seed for use with --jitter and --downsample flags.
  --aspect_equal        Turn on equal aspect ratio for the plot

contour mode:
  --contour_bin CONTOUR_BIN
                        Bin size of the contour plot. Smaller integers lead to smoother curves.
  --contour_logspace    Switch the contour lines from linear spacing to log spacing
  --contour_num_levels CONTOUR_NUM_LEVELS
                        The number of levels in the contour plot, default=6

density mode:
  --density_covariance DENSITY_COVARIANCE
                        Gaussian kernel density estimate covariance, raising the value leads to
                        smoother curves. This roughly corresponds to bandwidth in R. Default is to
                        discover the value automatically.
  --density_num_bins DENSITY_NUM_BINS
                        Number of "bins" for the density curve. default=200

matrix mode:
  --matrix_matshow      Switches the drawing call from pcolor() to matshow(). matshow() uses rasters,
                        pcolor() uses vectors. For very large matrices matshow() may be desirable.
  --matrix_cmap MATRIX_CMAP
                        The colormap to be used. default=binary. Possible values: Spectral, summer,
                        coolwarm, Set1, Set2, Set3, Dark2, hot, RdPu, YlGnBu, RdYlBu, gist_stern,
                        cool, gray, GnBu, gist_ncar, gist_rainbow, bone, RdYlGn, spring, terrain,
                        PuBu, spectral, gist_yarg, BuGn, bwr, cubehelix, YlOrRd, Greens, PRGn,
                        gist_heat, Paired, hsv, Pastel2, Pastel1, BuPu, copper, OrRd, brg, gnuplot2,
                        jet, gist_earth, Oranges, PiYG, YlGn, Accent, gist_gray, flag, BrBG, Reds,
                        RdGy, PuRd, Blues, Greys, autumn, pink, binary, winter, gnuplot, RdBu, prism,
                        YlOrBr, rainbow, seismic, Purples, ocean, PuOr, PuBuGn, afmhot
  --matrix_no_colorbar  turn off the colorbar.
  --matrix_discritize_colormap MATRIX_DISCRITIZE_COLORMAP
                        number of bins to discritize colormap

Examples

Plotting 2D scatter data, one file, no legend.

bin/quick_plot example/data_2d_1.txt --mode scatter --markersize 7.0 --out_format png --out img/example_01.png --title '2D scatter data from example/data_2d_1.txt' --xlabel 'The x-axis' --ylabel 'The y-axis' --no_legend

Plotting 2D scatter data, two files.

bin/quick_plot example/data_2d_1.txt example/data_2d_2.txt --mode scatter --markersize 7.0 --out_format png --out img/example_02.png

Plotting 2D line data, two files.

bin/quick_plot example/data_2d_3.txt example/data_2d_4.txt --mode line --out_format png --out img/example_03.png

Plotting 2D line data, three files.

bin/quick_plot example/data_2d_5.txt example/data_2d_6.txt example/data_2d_7.txt --mode line --out_format png --out img/example_04.png

Plotting 1D data as bars, two files.

bin/quick_plot example/data_1d_1.txt example/data_1d_2.txt --mode bar --out_format png --out img/example_05.png

Plotting 1D data as tick marks, two files.

bin/quick_plot example/data_1d_1.txt example/data_1d_2.txt --mode tick --out_format png --out img/example_06.png

Plotting 1D data as point marks, two files.

bin/quick_plot example/data_1d_1.txt example/data_1d_2.txt --mode point --out_format png --out img/example_07.png

Plotting 1D data as point clouds (using jitter), two files.

(Remove the --random_seed for production use).

bin/quick_plot example/data_1d_1.txt example/data_1d_2.txt --mode point --jitter --out_format png --out img/example_08.png --random_seed=127

Plotting 1D data as histogram, three files.

bin/quick_plot example/data_1d_3.txt example/data_1d_4.txt example/data_1d_5.txt --mode hist --out_format png --out img/example_09.png

Plotting 2D data as scatter plot, one file.

bin/quick_plot example/data_2d_8.txt --mode scatter --markersize 5.0 --out_format png --out img/example_10.png

Plotting 2D data as scatter plot with alpha transparency, one file.

bin/quick_plot example/data_2d_8.txt --mode scatter --markersize 5.0 --alpha 0.1 --out_format png --out img/example_11.png

Plotting 2D data as scatter plot with alpha transparency, fixing the aspect ratio, one file.

bin/quick_plot example/data_2d_8.txt --mode scatter --markersize 5.0 --alpha 0.1 --out_format png --out img/example_11_a.png --aspect_equal

Plotting 2D data as scatter plot using downsampling to 1000 points, fixing the aspect ratio, one file.

(Remove the --random_seed for production use).

bin/quick_plot example/data_2d_8.txt --mode scatter --markersize 5.0 --out_format png --out img/example_11_b.png --aspect_equal --random_seed=127 --downsample 1000 --title 'Downsampled to 1000 points'

Plotting 2D data as scatter plot using downsampling to 100 points, fixing the aspect ratio, one file.

(Remove the --random_seed for production use).

bin/quick_plot example/data_2d_8.txt --mode scatter --markersize 5.0 --alpha 0.1 --out_format png --out img/example_11_c.png --aspect_equal --random_seed=127 --downsample 100 --title 'Downsampled to 100 points'

Plotting 1D data as density curve, one file.

bin/quick_plot example/data_1d_7.txt --mode density --out_format png --out img/example_12.png --title 'data_2d_8.txt x marginal'

Plotting 1D data as density curve, one file, selecting column to plot.

bin/quick_plot example/data_2d_8.txt --mode density --out_format png --out img/example_12_a.png --title 'data_2d_8.txt x marginal' --columns 1

Plotting 1D data as density curve, one file.

bin/quick_plot example/data_1d_8.txt --mode density --out_format png --out img/example_13.png --title 'data_2d_8.txt y marginal'

Plotting 1D data as density curve, one file, selecting column to plot.

bin/quick_plot example/data_1d_8.txt --mode density --out_format png --out img/example_13_a.png --title 'data_2d_8.txt y marginal' --columns 2

Plotting 2D data as contour plot, one file.

bin/quick_plot example/data_2d_8.txt --mode contour --out_format png --out img/example_14.png --title 'A hard example for a contour plot'

Plotting 2D data as contour plot, one file.

bin/quick_plot example/data_2d_9.txt --mode contour --out_format png --out img/example_15.png --title 'An easier example for a contour plot'

Anscombe's quartet, plotting from a single file with many columns, mixing and matching columns

bin/quick_plot example/anscombe.txt --mode scatter --out_format png --out img/example_16.png --title 'Anscombe_i' --regression  --markersize 5.0 --ymin 3 --ymax 13 --xmin 3 --xmax 20 --no_legend

bin/quick_plot example/anscombe.txt --mode scatter --out_format png --out img/example_17.png --title 'Anscombe_ii' --regression  --markersize 5.0 --ymin 3 --ymax 13 --xmin 3 --xmax 20 --no_legend --columns 3,4

bin/quick_plot example/anscombe.txt --mode scatter --out_format png --out img/example_18.png --title 'Anscombe_iii' --regression  --markersize 5.0 --ymin 3 --ymax 13 --xmin 3 --xmax 20 --no_legend --columns 5,6

bin/quick_plot example/anscombe.txt --mode scatter --out_format png --out img/example_19.png --title 'Anscombe_iiv' --regression  --markersize 5.0 --ymin 3 --ymax 13 --xmin 3 --xmax 20 --no_legend --columns 7,8

Matrix plot (heatmap) using a continuous colormap

bin/quick_plot example/distance_matrix.txt --mode matrix --out_format png --out img/example_20.png --title 'Heatmap' --matrix_cmap Reds --width 6

Matrix plot (heatmap) using a continuous colormap, censoring colormap

bin/quick_plot example/distance_matrix.txt --mode matrix --out_format png --out img/example_20_a.png --title 'Heatmap' --matrix_cmap Reds --width 6 --matrix_colormap_max 0.20

Heatmap using a discritized colormap

bin/quick_plot example/distance_matrix_1.txt --mode matrix --out_format png --out img/example_21.png --title 'Heatmap 2' --width 6 --matrix_discritize_colormap 6

Heatmap using a discritized colormap without a colorbar

bin/quick_plot example/distance_matrix_2.txt --mode matrix --out_format png --out img/example_22.png --title 'Heatmap 3' --matrix_cmap Oranges --width 6 --matrix_discritize_colormap 10 --matrix_no_colorbar