Synopsis
Take a data structure in Perl, and automatically write a Python3 script using matplotlib to generate an image. The Python3 script is saved in /tmp, to be edited at the user's discretion. Requires python3 and matplotlib installations.
Single Plots
Simplest use case: use Matplotlib::Simple 'plot'; plot({ 'output.filename' => '/tmp/gospel.word.counts.png', 'plot.type' => 'bar', data => { Matthew => 18345, Mark => 11304, Luke => 19482, John => 15635, } }); where xlabel, ylabel, title, etc. are axis methods in matplotlib itself. plot.type, data, input.file are all specific to MatPlotLib::Simple.
<img width="651" height="491" alt="gospel word counts" src="https://github.com/user-attachments/assets/a008dece-2e34-47bf-af0f-8603709f7d52" />
Multiple Plots
Having a plots argument as an array lets the module know to create subplots: use Matplotlib::Simple 'plot'; plot({ 'output.filename' => 'svg/pies.png', plots => [ { data => { Russian => 106_000_000, # Primarily European Russia German => 95_000_000, # Germany, Austria, Switzerland, etc. }, 'plot.type' => 'pie', title => 'Top Languages in Europe', suptitle => 'Pie in subplots', }, { data => { Russian => 106_000_000, # Primarily European Russia German => 95_000_000, # Germany, Austria, Switzerland, etc. }, 'plot.type' => 'pie', title => 'Top Languages in Europe', }, ], ncols => 2, }); which produces the following subplots image:
<img width="651" height="424" alt="pies" src="https://github.com/user-attachments/assets/49d3e28b-f897-4b01-9e72-38afa12fa538" />
bar, barh, boxplot, hexbin, hist, hist2d, imshow, pie, plot, scatter, and violinplot all match the methods in matplotlib itself. =head1 Examples/Plot Types
Consider the following helper subroutines to generate data to plot:
``` sub linspace { # mostly written by Grok my ($start, $stop, $num, $endpoint) = @_; # endpoint means include $stop $num = defined $num ? int($num) : 50; # Default to 50 points $endpoint = defined $endpoint ? $endpoint : 1; # Default to include endpoint return () if $num < 0; # Return empty array for invalid num return ($start) if $num == 1; # Return single value if num is 1 my (@result, $step);
if ($endpoint) {
$step = ($stop - $start) / ($num - 1) if $num > 1;
for my $i (0 .. $num - 1) {
$result[$i] = $start + $i * $step;
}
} else {
$step = ($stop - $start) / $num;
for my $i (0 .. $num - 1) {
$result[$i] = $start + $i * $step;
}
}
return @result;}
sub generate_normal_dist { my ($mean, $std_dev, $size) = @; $size = defined $size ? int $size : 100; # default to 100 points my @numbers; for (1 .. int($size / 2) + 1) {# Box-Muller transform my $u1 = rand(); my $u2 = rand(); my $z0 = sqrt(-2.0 * log($u1)) * cos(2.0 * 3.141592653589793 * $u2); my $z1 = sqrt(-2.0 * log($u1)) * sin(2.0 * 3.141592653589793 * $u2); # Scale and shift to match mean and stddev push @numbers, ($z0 * $std_dev + $mean, $z1 * $std_dev + $mean); } # Trim to exact size if needed @numbers = @numbers[0 .. $size - 1] if @numbers > $size; @numbers = map {sprintf '%.1f', $} @numbers; return \@numbers; } sub randbetween { my ($min, $max) = @_; return $min + rand($max - $min) } ``` =head2 Barplot/bar/barh
Plot a hash or a hash of arrays as a boxplot
Options
| Option | Description | Example | | -------- | ------- | ------- |color| :mpltype:color or list of :mpltype:color, optional; The colors of the bar faces. This is an alias for facecolor. If both are given, facecolor takes precedence # if entering multiple colors, quoting isn't needed|color => ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'fuchsia'], or a single color for all bars color => 'red' |edgecolor| :mpltype:color or list of :mpltype:color, optional; The colors of the bar edges|edgecolor => 'black' |key.order| define the keys in an order (an array reference)|'key.order' => ['Sun','Mon','Tue','Wed','Thu','Fri','Sat'], |linewidth| float or array, optional; Width of the bar edge(s). If 0, don't draw edges. Only does anything with defined edgecolor|linewidth => 2, |log| bool, default: False; If True, set the y-axis to be log scale.|log = 'True', |stacked| stack the groups on top of one another; default 0 = off|stacked => 1, |width| float only, default: 0.8; The width(s) of the bars. width will be deactivated with grouped, non-stacked bar plots |width => 0.4, |xerr| float or array-like of shape(N,) or shape(2, N), optional. If not None, add horizontal / vertical errorbars to the bar tips. The values are +/- sizes relative to the data: - scalar: symmetric +/- values for all bars # - shape(N,): symmetric +/- values for each bar # - shape(2, N): Separate - and + values for each bar. First row # contains the lower errors, the second row contains the upper # errors. # - None: No errorbar. (Default)|yerr => {'USA' => [15,29], 'Russia' => [199,1000],} |yerr|same as xerr, but better with bar|
an example of multiple plots, showing many options:
single, simple plot
use Matplotlib::Simple 'plot'; plot({ 'output.filename' => 'output.images/single.barplot.png', data => { # simple hash Fri => 76, Mon => 73, Sat => 26, Sun => 11, Thu => 94, Tue => 93, Wed => 77 }, 'plot.type' => 'bar', xlabel => '# of Days', ylabel => 'Count', title => 'Customer Calls by Days' });
where xlabel, ylabel, title, etc. are axis methods in matplotlib itself. plot.type, data, input.file are all specific to MatPlotLib::Simple. <img width="651" height="491" alt="single barplot" src="https://github.com/user-attachments/assets/eae009a8-5571-4608-abdb-1016e3cff5fd" />
multiple plots
plot({ 'input.file' => $tmp_filename, execute => 0, 'output.filename' => 'output.images/barplots.png', plots => [ { # simple plot data => { # simple hash Fri => 76, Mon => 73, Sat => 26, Sun => 11, Thu => 94, Tue => 93, Wed => 77 }, 'plot.type' => 'bar', 'key.order' => ['Sun','Mon','Tue','Wed','Thu','Fri','Sat'], suptitle => 'Types of Plots', # applies to all color => ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'fuchsia'], edgecolor => 'black', set_figwidth => 40/1.5, # applies to all plots set_figheight => 30/2, # applies to all plots title => 'bar: Rejections During Job Search', xlabel => 'Day of the Week', ylabel => 'No. of Rejections' }, { # grouped bar plot 'plot.type' => 'bar', data => { 1941 => { UK => 6.6, US => 6.2, USSR => 17.8, Germany => 26.6 }, 1942 => { UK => 7.6, US => 26.4, USSR => 19.2, Germany => 29.7 }, 1943 => { UK => 7.9, US => 61.4, USSR => 22.5, Germany => 34.9 }, 1944 => { UK => 7.4, US => 80.5, USSR => 27.0, Germany => 31.4 }, 1945 => { UK => 5.4, US => 83.1, USSR => 25.5, Germany => 11.2 #Rapid decrease due to war's end <br /> }, }, stacked => 0, title => 'Hash of Hash Grouped Unstacked Barplot', width => 0.23, xlabel => 'r"$\it{anno}$ $\it{domini}$"', # italic ylabel => 'Military Expenditure (Billions of $)' }, { # grouped bar plot 'plot.type' => 'bar', data => { 1941 => { UK => 6.6, US => 6.2, USSR => 17.8, Germany => 26.6 }, 1942 => { UK => 7.6, US => 26.4, USSR => 19.2, Germany => 29.7 }, 1943 => { UK => 7.9, US => 61.4, USSR => 22.5, Germany => 34.9 }, 1944 => { UK => 7.4, US => 80.5, USSR => 27.0, Germany => 31.4 }, 1945 => { UK => 5.4, US => 83.1, USSR => 25.5, Germany => 11.2 #Rapid decrease due to war's end <br /> }, }, stacked => 1, title => 'Hash of Hash Grouped Stacked Barplot', xlabel => 'r"$\it{anno}$ $\it{domini}$"', # italic ylabel => 'Military Expenditure (Billions of $)' }, {# grouped barplot: arrays indicate Union, Confederate which must be specified in options hash data => { # 4th plot: arrays indicate Union, Confederate which must be specified in options hash 'Antietam' => [ 12400, 10300 ], 'Gettysburg' => [ 23000, 28000 ], 'Chickamauga' => [ 16000, 18000 ], 'Chancellorsville' => [ 17000, 13000 ], 'Wilderness' => [ 17500, 11000 ], 'Spotsylvania' => [ 18000, 12000 ], 'Cold Harbor' => [ 12000, 5000 ], 'Shiloh' => [ 13000, 10700 ], 'Second Bull Run' => [ 10000, 8000 ], 'Fredericksburg' => [ 12600, 5300 ], }, 'plot.type' => 'barh', color => ['blue', 'gray'], # colors match indices of data arrays label => ['North', 'South'], # colors match indices of data arrays xlabel => 'Casualties', ylabel => 'Battle', title => 'barh: hash of array' }, { # 5th plot: barplot with groups data => { 1942 => [ 109867, 310000, 7700000 ], # US, Japan, USSR 1943 => [ 221111, 440000, 9000000 ], 1944 => [ 318584, 610000, 7000000 ], 1945 => [ 318929, 1060000, 3000000 ], }, color => ['blue', 'pink', 'red'], # colors match indices of data arrays label => ['USA', 'Japan', 'USSR'], # colors match indices of data arrays 'log' => 1, title => 'grouped bar: Casualties in WWII', ylabel => 'Casualties', 'plot.type' => 'bar' }, <br /> { # nuclear weapons barplot 'plot.type' => 'bar', data => { 'USA' => 5277, # FAS Estimate 'Russia' => 5449, # FAS Estimate 'UK' => 225, # Consistent estimate 'France' => 290, # Consistent estimate 'China' => 600, # FAS Estimate 'India' => 180, # FAS Estimate 'Pakistan' => 130, # FAS Estimate 'Israel' => 90, # FAS Estimate 'North Korea' => 50, # FAS Estimate }, title => 'Simple hash for barchart with yerr', xlabel => 'Country', yerr => { 'USA' => [15,29], 'Russia' => [199,1000], 'UK' => [15,19], 'France' => [19,29], 'China' => [200,159], 'India' => [15,25], 'Pakistan' => [15,49], 'Israel' => [90,50], 'North Korea' => [10,20], }, ylabel => '# of Nuclear Warheads', 'log' => 'True', # linewidth => 1, } ], ncols => 3, nrows => 4 }); which produces the plot:
<img width="2678" height="849" alt="barplots" src="https://github.com/user-attachments/assets/6d87d13b-dabd-485d-92f7-1418f4acc65b" />
boxplot
Plot a hash of arrays as a series of boxplots
options
| Option | Description | Example | | -------- | ------- | ------- | |color | a single color for all plots | color => 'pink'| |colors| a hash, where each data point and color is a hash pair |colors => { A => 'orange', E => 'yellow', B => 'purple' },| | key.order| order that the keys in the entry hash will be plotted | key.order = ['A', 'E', 'B'] | | orientation| orientation of the plot, by default vertical| orientation = 'horizontal' | |showcaps| Show the caps on the ends of whiskers; default True | showcaps => 'False', | | showfliers |Show the outliers beyond the caps; default True | showfliers => 'False' | |showmeans | show means; default = True | showmeans => 'False' | |whiskers| show whiskers, default = 1| whiskers => 0,|
single, simple plot
``` my $x = generate_normal_dist( 100, 15, 3 * 10 ); my $y = generate_normal_dist( 85, 15, 3 * 10 ); my $z = generate_normal_dist( 106, 15, 3 * 10 );
single plots are simple
plot( { 'output.filename' => 'output.images/single.boxplot.png', data => { # simple hash E => [ 55, @{$x}, 160 ], B => [ @{$y}, 140 ],
# A => @a
},
'plot.type' => 'boxplot',
title => 'Single Box Plot: Specified Colors',
colors => { E => 'yellow', B => 'purple' },
'input.file' => $tmp_filename,
execute => 0,
}); ``` which makes the following image:
<img width="651" height="491" alt="single boxplot" src="https://github.com/user-attachments/assets/19870fa2-fe36-4513-8cbb-23da3a0cf686" />
multiple plots
plot( { 'output.filename' => 'output.images/boxplot.png', execute => 0, 'input.file' => $tmp_filename, plots => [ { data => { A => [ 55, @{$z} ], E => [ @{$y} ], B => [ 122, @{$z} ], }, title => 'Simple Boxplot', ylabel => 'ylabel', xlabel => 'label', 'plot.type' => 'boxplot', suptitle => 'Boxplot examples' }, { color => 'pink', data => { A => [ 55, @{$z} ], E => [ @{$y} ], B => [ 122, @{$z} ], }, title => 'Specify single color', ylabel => 'ylabel', xlabel => 'label', 'plot.type' => 'boxplot' }, { colors => { A => 'orange', E => 'yellow', B => 'purple' }, data => { A => [ 55, @{$z} ], E => [ @{$y} ], B => [ 122, @{$z} ], }, title => 'Specify set-specific color; showfliers = False', ylabel => 'ylabel', xlabel => 'label', 'plot.type' => 'boxplot', showmeans => 'True', showfliers => 'False', set_figwidth => 12 }, { colors => { A => 'orange', E => 'yellow', B => 'purple' }, data => { A => [ 55, @{$z} ], E => [ @{$y} ], B => [ 122, @{$z} ], }, title => 'Specify set-specific color; showmeans = False', ylabel => 'ylabel', xlabel => 'label', 'plot.type' => 'boxplot', showmeans => 'False', }, { colors => { A => 'orange', E => 'yellow', B => 'purple' }, data => { A => [ 55, @{$z} ], E => [ @{$y} ], B => [ 122, @{$z} ], }, title => 'Set-specific color; orientation = horizontal', ylabel => 'ylabel', xlabel => 'label', orientation => 'horizontal', 'plot.type' => 'boxplot', }, { colors => { A => 'orange', E => 'yellow', B => 'purple' }, data => { A => [ 55, @{$z} ], E => [ @{$y} ], B => [ 122, @{$z} ], }, title => 'Notch = True', ylabel => 'ylabel', xlabel => 'label', notch => 'True', 'plot.type' => 'boxplot', }, { colors => { A => 'orange', E => 'yellow', B => 'purple' }, data => { A => [ 55, @{$z} ], E => [ @{$y} ], B => [ 122, @{$z} ], }, title => 'showcaps = False', ylabel => 'ylabel', xlabel => 'label', showcaps => 'False', 'plot.type' => 'boxplot', set_figheight => 12, }, ], ncols => 3, nrows => 3, } ); which makes the following plot:
<img width="1230" height="1211" alt="boxplot" src="https://github.com/user-attachments/assets/7e32e394-86fc-49e7-ad97-f48fd82fc8b0" />
hexbin
Plot a hash of arrays as a hexbin see https://matplotlib.org/stable/api/asgen/matplotlib.pyplot.hexbin.html
options
| Option | Description | Example | | -------- | ------- | ------- | cb_logscale | colorbar log scale from matplotlib.colors import LogNorm | default 0, any value > 0 enables | |cmap| The Colormap instance or registered colormap name used to map scalar data to colors | default gist_rainbow | |key.order| define the keys in an order (an array reference)|'key.order' => ['X-rays', 'Yak Butter'], | marginals | integer, by default off = 0 | marginals => 1 | | mincnt | int >= 0, default: None; If not None, only display cells with at least mincnt number of points in the cell. | mincnt => 2| | vmax | The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap | 'asinh', 'function', 'functionlog', 'linear', 'log', 'logit', 'symlog' default linear | | vmin | The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap | 'asinh', 'function', 'functionlog', 'linear', 'log', 'logit', 'symlog' default linear | | xbins | integer that accesses horizontal gridsize | default is 15 | | xscale.hexbin | 'linear', 'log'}, default: 'linear': Use a linear or log10 scale on the horizontal axis | 'xscale.hexbin' => 'log'| | ybins | integer that accesses vertical gridsize | default is 15 | | yscale.hexbin | 'linear', 'log'}, default: 'linear': Use a linear or log10 scale on the vertical axis | 'yscale.hexbin' => 'log'|
single, simple plot
plot({ data => { E => generate_normal_dist(100, 15, 3*210), B => generate_normal_dist(85, 15, 3*210) }, 'output.filename' => 'output.images/single.hexbin.png', 'plot.type' => 'hexbin', set_figwidth => 12, title => 'Simple Hexbin', }); which makes the following plot: <img width="1208" height="491" alt="single hexbin" src="https://github.com/user-attachments/assets/129c41cd-2d7d-43de-978a-2b9c441b8939" /> =head3 multiple plots
plot( { 'input.file' => $tmp_filename, execute => 0, 'output.filename' => 'output.images/hexbin.png', plots => [ { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'Simple Hexbin', }, { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'colorbar logscale', cb_logscale => 1 }, { cmap => 'jet', data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'cmap is jet', xlabel => 'xlabel', }, { data => { E => @e, B => @b }, 'key.order' => ['E', 'B'], 'plot.type' => 'hexbin', title => 'Switch axes with key.order', }, { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'vmax set to 25', vmax => 25 }, { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'vmin set to -4', vmin => -4 }, { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'mincnt set to 7', mincnt => 7 }, { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'xbins set to 9', xbins => 9 }, { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'ybins set to 9', ybins => 9 }, { data => { E => @e, B => @b }, 'plot.type' => 'hexbin', title => 'marginals = 1', marginals => 1 }, ], ncols => 2 } ); which produces the following image: <img width="2010" height="1511" alt="hexbin" src="https://github.com/user-attachments/assets/71412ab1-e869-4913-a8cf-e39df15c9590" /> =head2 hist
Plot a hash of arrays as a series of histograms
options
single, simple plot
``` my @e = generate_normal_dist( 100, 15, 3 * 200 ); my @b = generate_normal_dist( 85, 15, 3 * 200 ); my @a = generate_normal_dist( 105, 15, 3 * 200 );
plot({ 'input.file' => $tmp_filename, execute => 0, 'output.filename' => 'output.images/single.hist.png', data => { E => @e, B => @b, A => @a, }, 'plot.type' => 'hist' }); ``` <img width="651" height="491" alt="single hist" src="https://github.com/user-attachments/assets/fafcf787-6c4f-4998-88c4-77a15d878fa6" />
multiple plots
plot({ 'input.file' => $tmp_filename, execute => 0, 'output.filename' => 'output.images/histogram.png', suptitle => 'hist Examples', plots => [ { # 1st subplot data => { E => @e, B => @b, A => @a, }, 'plot.type' => 'hist', alpha => 0.25, bins => 50, title => 'alpha = 0.25', color => { B => 'Black', E => 'Orange', A => 'Yellow', }, scatter => '[' . join( ',', 22 .. 44 ) . '],[' # x coords . join( ',', 22 .. 44 ) # y coords . '], label = "scatter"', xlabel => 'Value', ylabel => 'Frequency', }, { # 2nd subplot data => { E => @e, B => @b, A => @a, }, 'plot.type' => 'hist', alpha => 0.75, bins => 50, title => 'alpha = 0.75', color => { B => 'Black', E => 'Orange', A => 'Yellow', }, xlabel => 'Value', ylabel => 'Frequency', suptitle => 'Types of Plots', # applies to all # 'log' => 1, }, { # 3rd subplot add => [ # add secondary plots/graphs/methods { # 1st additional plot/graph data => { 'Gaussian' => [ [40..150], [map {150 * exp(-0.5*($_-100)**2)} 40..150] ] }, 'plot.type' => 'plot', 'set.options' => { 'Gaussian' => 'color = "red", linestyle = "dashed"' } } ], data => { E => @e, B => @b, A => @a, }, 'plot.type' => 'hist', alpha => 0.75, bins => { A => 10, B => 25, E => 50 }, title => 'Varying # of bins', color => { B => 'Black', E => 'Orange', A => 'Yellow', }, xlabel => 'Value', ylabel => 'Frequency', set_figwidth => 15, suptitle => 'Types of Plots', # applies to all # 'log' => 1, }, {# 4th subplot data => { E => @e, B => @b, A => @a, }, 'plot.type' => 'hist', alpha => 0.75, color => { B => 'Black', E => 'Orange', A => 'Yellow', }, orientation => 'horizontal', # assign x and y labels smartly set_figwidth => 15, suptitle => 'Types of Plots', # applies to all title => 'Horizontal orientation', ylabel => 'Value', xlabel => 'Frequency', # 'log' => 1, }, ], ncols => 3, nrows => 2, });
<img width="1511" height="491" alt="histogram" src="https://github.com/user-attachments/assets/2fbeaacd-770f-4422-940c-53611679b5e8" />
hist2d
options
single, simple plot
multiple plots
imshow
Plot 2D array of numbers as an image
options
| Option | Description | Example | | -------- | ------- | ------- |cblabel| colorbar label | cblabel => 'sin(x) * cos(x)', |cbdrawedges |draw edges for colorbar | | |cblocation | 'left', 'right', 'top', 'bottom'| cblocation => 'left',| |cborientation| None, or 'vertical', 'horizontal' | |cmap| # The Colormap instance or registered colormap name used to map scalar data to colors.| |vmax| float | |vmin| float |
single, simple plot
my @imshow_data; foreach my $i (0..360) { foreach my $j (0..360) { push @{ $imshow_data[$i] }, sin($i * $pi/180)*cos($j * $pi/180); } } plot({ data => \@imshow_data, execute => 0, 'input.file' => $tmp_filename, 'output.filename' => 'output.images/imshow.single.png', 'plot.type' => 'imshow', set_xlim => '0, ' . scalar @imshow_data, set_ylim => '0, ' . scalar @imshow_data, }); <img width="599" height="491" alt="imshow single" src="https://github.com/user-attachments/assets/3fa4ffe6-4817-4133-9c91-b68099400377" />
multiple plots
pie
options
single, simple plot
multiple plots
plot
single, simple
plot( { 'input.file' => $tmp_filename, execute => 0, 'output.filename' => 'output.images/plot.single.png', data => { 'sin(x)' => [ [@x], # x [ map { sin($_) } @x ] # y ], 'cos(x)' => [ [@x], # x [ map { cos($_) } @x ] # y ], }, 'plot.type' => 'plot', title => 'simple plot', set_xticks => "[-2 * $pi, -3 * $pi / 2, -$pi, -$pi / 2, 0, $pi / 2, $pi, 3 * $pi / 2, 2 * $pi" . '], [r\'$-2\pi$\', r\'$-3\pi/2$\', r\'$-\pi$\', r\'$-\pi/2$\', r\'$0$\', r\'$\pi/2$\', r\'$\pi$\', r\'$3\pi/2$\', r\'$2\pi$\']', 'set.options' => { # set options overrides global settings 'sin(x)' => 'color="blue", linewidth=2', 'cos(x)' => 'color="red", linewidth=2' } } );
which makes the following "plot" plot: <img width="651" height="491" alt="plot single" src="https://github.com/user-attachments/assets/6cbd6aad-c464-4703-b962-b420ec08bb66" />
multiple sub-plots
my $pi = atan2( 0, -1 ); my @x = linspace( -2 * $pi, 2 * $pi, 100, 1 ); plot( { 'input.file' => $tmp_filename, execute => 0, 'output.filename' => 'output.images/plot.png', plots => [ { # plot 1 data => { 'sin(x)' => [ [@x], # x [ map { sin($_) } @x ] # y ], 'cos(x)' => [ [@x], # x [ map { cos($_) } @x ] # y ], }, 'plot.type' => 'plot', title => 'simple plot', set_xticks => "[-2 * $pi, -3 * $pi / 2, -$pi, -$pi / 2, 0, $pi / 2, $pi, 3 * $pi / 2, 2 * $pi" . '], [r\'$-2\pi$\', r\'$-3\pi/2$\', r\'$-\pi$\', r\'$-\pi/2$\', r\'$0$\', r\'$\pi/2$\', r\'$\pi$\', r\'$3\pi/2$\', r\'$2\pi$\']', 'set.options' => { # set options overrides global settings 'sin(x)' => 'color="blue", linewidth=2', 'cos(x)' => 'color="red", linewidth=2' }, set_xlim => "$x[0], $x[-1]", # set min and max as a string }, { # plot 2 data => { 'csc(x)' => [ [@x], # x [ map { 1 / sin($_) } @x ] # y ], 'sec(x)' => [ [@x], # x [ map { 1 / cos($_) } @x ] # y ], }, 'plot.type' => 'plot', title => 'simple plot', set_xticks => "[-2 * $pi, -3 * $pi / 2, -$pi, -$pi / 2, 0, $pi / 2, $pi, 3 * $pi / 2, 2 * $pi" . '], [r\'$-2\pi$\', r\'$-3\pi/2$\', r\'$-\pi$\', r\'$-\pi/2$\', r\'$0$\', r\'$\pi/2$\', r\'$\pi$\', r\'$3\pi/2$\', r\'$2\pi$\']', 'set.options' => { # set options overrides global settings 'csc(x)' => 'color="purple", linewidth=2', 'sec(x)' => 'color="green", linewidth=2' }, set_xlim => "$x[0], $x[-1]", # set min and max as a string set_ylim => '-9,9', }, ], ncols => 2, set_figwidth => 12, } ); which makes <img width="1211" height="491" alt="plot" src="https://github.com/user-attachments/assets/a8312147-e13d-4aa9-9997-49430bb5c74a" /> =head2 scatter
options
single, simple plot
multiple plots
violin
options
single, simple plot
multiple plots
wide
options
single, simple plot
multiple plots
Advanced
Notes in Files
all files that can have notes with them, give notes about how the file was written. For example, SVG files have the following: <dc:title>made/written by /mnt/ceph/dcondon/ui/gromacs/tut/dup.2puy/1.plot.gromacs.pl called using "plot" in /mnt/ceph/dcondon/perl5/perlbrew/perls/perl-5.42.0/lib/site_perl/5.42.0/x86_64-linux/Matplotlib/Simple.pm</dc:title> =head2 Speed
To improve speed, all data can be written into a single temp python3 file thus: ``` use File::Temp 'tempfile';
my ( $fh, $tmp_filename ) = tempfile( DIR => '/tmp', SUFFIX => '.py', UNLINK => 0 ); close $fh; =head1 all files will be written to $tmp_filename; be sure to put execute => 0
plot( { data => { Clinical => [ [ [@xw], # x [@y] # y ], [ [@xw], [ map { $_ + rand_between( -0.5, 0.5 ) } @y ] ], [ [@xw], [ map { $_ + rand_between( -0.5, 0.5 ) } @y ] ] ], HGI => [ [ [@xw], # x [ map { 1.9 - 1.1 / $_ } @xw ] # y ], [ [@xw], [ map { $_ + rand_between( -0.5, 0.5 ) } @y ] ], [ [@xw], [ map { $_ + rand_between( -0.5, 0.5 ) } @y ] ] ] }, 'output.filename' => 'output.images/single.wide.png', 'plot.type' => 'wide', color => { Clinical => 'blue', HGI => 'green' }, title => 'Visualization of similar lines plotted together', 'input.file' => $tmp_filename, execute => 0, } ); =head1 the last plot should have execute => 1
plot( { data => [ [ [@xw], # x [@y] # y ], [ [@xw], [ map { $_ + rand_between( -0.5, 0.5 ) } @y ] ], [ [@xw], [ map { $_ + rand_between( -0.5, 0.5 ) } @y ] ] ], 'output.filename' => 'output.images/single.array.png', 'plot.type' => 'wide', color => 'red', title => 'Visualization of similar lines plotted together', 'input.file' => $tmp_filename, execute => 1, } ); ```