=head1 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 C</tmp>, to be edited at the user's discretion.
Requires python3 and matplotlib installations.

=head2 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 C<xlabel>, C<ylabel>, C<title>, etc. are axis methods in matplotlib itself. C<plot.type>, C<data>, C<input.file> are all specific to C<MatPlotLib::Simple>.


=for html
<p>
<img width="651" height="491" alt="gospel word counts" src="https://github.com/user-attachments/assets/a008dece-2e34-47bf-af0f-8603709f7d52" />
<p>


=head2 Multiple Plots

Having a C<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:


=for html
<p>
<img width="651" height="424" alt="pies" src="https://github.com/user-attachments/assets/49d3e28b-f897-4b01-9e72-38afa12fa538" />
<p>


C<bar>, C<barh>, C<boxplot>, C<hexbin>, C<hist>, C<hist2d>, C<imshow>, C<pie>, C<plot>, C<scatter>, and C<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 * $u2); # Scale and shift to match mean and std_dev
         push @numbers, ($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', $_} @numbers;
     return \@numbers;
 }
 sub rand_between {
     my ($min, $max) = @_;
     return $min + rand($max - $min)
 }

=head2 Barplot/bar/barh

Plot a hash or a hash of arrays as a boxplot

=head3 Options

=for html
<table>
<tbody>
<tr><td>Option</td><td>Description</td><td>Example</td></tr>
<tr><td>--------</td><td>-------</td><td>------- </td></tr>
<tr><td>color</td><td>: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</td><td>`color => ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'fuchsia'],` or a single color for all bars `color => 'red'`</td></tr>
<tr><td>edgecolor</td><td>:mpltype:`color` or list of :mpltype:`color`, optional; The colors of the bar edges</td><td>`edgecolor        => 'black'`</td></tr>
<tr><td>key.order</td><td>define the keys in an order (an array reference)</td><td>`'key.order'     => ['Sun','Mon','Tue','Wed','Thu','Fri','Sat'],`</td></tr>
<tr><td>linewidth</td><td>float or array, optional; Width of the bar edge(s). If 0, don't draw edges. Only does anything with defined `edgecolor`</td><td>`linewidth => 2,`</td></tr>
<tr><td>log</td><td>bool, default: False; If *True*, set the y-axis to be log scale.</td><td>`log = 'True',`</td></tr>
<tr><td>stacked</td><td>stack the groups on top of one another; default 0 = off</td><td>`stacked    => 1,`</td></tr>
<tr><td>width</td><td>float only, default: 0.8; The width(s) of the bars.  `width` will be deactivated with grouped, non-stacked bar plots</td><td>`width => 0.4,`</td></tr>
<tr><td>xerr</td><td>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)</td><td>`yerr                        => {'USA'               => [15,29], 'Russia'            => [199,1000],}`</td></tr>
<tr><td>yerr</td><td>same as xerr, but better with bar</td><td></td></tr>
</tbody>
</table>

an example of multiple plots, showing many options:

=head3 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 C<xlabel>, C<ylabel>, C<title>, etc. are axis methods in matplotlib itself. C<plot.type>, C<data>, C<input.file> are all specific to C<MatPlotLib::Simple>.

=for html
<p>
<img width="651" height="491" alt="single barplot" src="https://github.com/user-attachments/assets/eae009a8-5571-4608-abdb-1016e3cff5fd" />
<p>


=head3 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 $)'
         },
          { # grouped bar plot
             'plot.type' => 'bar',
             data    => {
                 1941 => {
                   UK      => 6.6,
                   US      => 6.2,
                   USSR    => 17.8,
                   Germany => 26.6
                 },
                 1942 => {
                   UK      => 7.6,
                   US      => 26.4,
                   USSR    => 19.2,
                   Germany => 29.7
                 },
                 1943 => {
                   UK      => 7.9,
                   US      => 61.4,
                   USSR    => 22.5,
                   Germany => 34.9
                 },
                 1944 => {
                   UK      => 7.4,
                   US      => 80.5,
                   USSR    => 27.0,
                   Germany => 31.4
                 },
                 1945 => {
                   UK      => 5.4,
                   US      => 83.1,
                   USSR    => 25.5,
                    Germany => 11.2 #Rapid decrease due to war's end 
                 },
             },
             stacked => 1,
             title       => 'Hash of Hash Grouped Stacked Barplot',
             xlabel  => 'r"$\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:


=for html
<p>
<img width="2678" height="849" alt="barplots" src="https://github.com/user-attachments/assets/6d87d13b-dabd-485d-92f7-1418f4acc65b" />
<p>


=head2 boxplot

Plot a hash of arrays as a series of boxplots

=head3 options

=for html
<table>
<tbody>
<tr><td>Option</td><td>Description</td><td>Example</td></tr>
<tr><td>--------</td><td>-------</td><td>-------</td></tr>
<tr><td>`color`</td><td>a single color for all plots</td><td>`color => 'pink'`</td></tr>
<tr><td>`colors`</td><td>a hash, where each data point and color is a hash pair</td><td>`colors => { A => 'orange', E => 'yellow', B => 'purple' },`</td></tr>
<tr><td>`key.order`</td><td>order that the keys in the entry hash will be plotted</td><td>`key.order = ['A', 'E', 'B']`</td></tr>
<tr><td>`orientation`</td><td>orientation of the plot, by default `vertical`</td><td>`orientation = 'horizontal'`</td></tr>
<tr><td>`showcaps`</td><td>Show the caps on the ends of whiskers; default `True`</td><td>`showcaps => 'False',`</td></tr>
<tr><td>`showfliers`</td><td>Show the outliers beyond the caps; default `True`</td><td>`showfliers  => 'False'`</td></tr>
<tr><td>`showmeans`</td><td>show means; default = `True`</td><td>`showmeans   => 'False'`</td></tr>
<tr><td>`whiskers`</td><td>show whiskers, default = 1</td><td>` whiskers    => 0,`</td></tr>
</tbody>
</table>

=head3 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:


=for html
<p>
<img width="651" height="491" alt="single boxplot" src="https://github.com/user-attachments/assets/19870fa2-fe36-4513-8cbb-23da3a0cf686" />
<p>


=head3 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:


=for html
<p>
<img width="1230" height="1211" alt="boxplot" src="https://github.com/user-attachments/assets/7e32e394-86fc-49e7-ad97-f48fd82fc8b0" />
<p>


=head2 hexbin

Plot a hash of arrays as a hexbin
see https://matplotlib.org/stable/api/I<as>gen/matplotlib.pyplot.hexbin.html

=head3 options

=for html
<table>
<tbody>
<tr><td>Option</td><td>Description</td><td>Example</td></tr>
<tr><td>--------</td><td>-------</td><td>------- </td></tr>
<tr><td>cb_logscale</td><td>colorbar log scale `from matplotlib.colors import LogNorm`</td><td>default 0, any value > 0 enables</td></tr>
<tr><td>cmap</td><td>The Colormap instance or registered colormap name used to map scalar data to colors</td><td>default `gist_rainbow`</td></tr>
<tr><td>key.order</td><td>define the keys in an order (an array reference)</td><td>`'key.order' => ['X-rays', 'Yak Butter'],`</td></tr>
<tr><td>marginals</td><td>integer, by default off = 0</td><td>`marginals => 1`</td></tr>
<tr><td>mincnt</td><td>int >= 0, default: None; If not None, only display cells with at least mincnt number of points in the cell.</td><td>`mincnt => 2`</td></tr>
<tr><td>vmax</td><td>The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap</td><td>`'asinh', 'function', 'functionlog', 'linear', 'log', 'logit', 'symlog'` default `linear`</td></tr>
<tr><td>vmin</td><td>The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap</td><td>`'asinh', 'function', 'functionlog', 'linear', 'log', 'logit', 'symlog'` default `linear`</td></tr>
<tr><td>xbins</td><td>integer that accesses horizontal gridsize</td><td>default is 15</td></tr>
<tr><td>xscale.hexbin</td><td>'linear', 'log'}, default: 'linear': Use a linear or log10 scale on the horizontal axis</td><td>`'xscale.hexbin' => 'log'`</td></tr>
<tr><td>ybins</td><td>integer that accesses vertical gridsize</td><td>default is 15</td></tr>
<tr><td>yscale.hexbin</td><td>'linear', 'log'}, default: 'linear': Use a linear or log10 scale on the vertical axis</td><td>`'yscale.hexbin' => 'log'`</td></tr>
</tbody>
</table>

=head3 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:

=for html
<p>
<img width="1208" height="491" alt="single hexbin" src="https://github.com/user-attachments/assets/129c41cd-2d7d-43de-978a-2b9c441b8939" />
<p>

=head3 multiple plots

 plot({
     'input.file'      => $tmp_filename,
     execute           => 0,
     'output.file' => '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
         },
         {
             data => {
                 E => @e,
                 B => @b
             },
             'plot.type'  => 'hexbin',
             title        => 'xscale.hexbin = 1',
             'xscale.hexbin' => 'log'
         },
         {
             data => {
                 E => @e,
                 B => @b
             },
             'plot.type'  => 'hexbin',
             title        => 'yscale.hexbin = 1',
             'yscale.hexbin' => 'log'
         },
     ],
     ncols        => 4,
     nrows        => 3,
     scale        => 5,
     suptitle     => 'Various Changes to Standard Hexbin: All data is the same'
 });

which produces the following image:

=for html
<p>
<img width="2409" height="3211" alt="hexbin" src="https://github.com/user-attachments/assets/0b23a0cb-8f9a-43fb-8da1-0debee13d540" />
<p>


=head2 hist

Plot a hash of arrays as a series of histograms

=head3 options

=for html
<table>
<tbody>
<tr><td>Option</td><td>Description</td><td>Example</td></tr>
<tr><td>--------</td><td>-------</td><td>-------</td></tr>
<tr><td>`alpha`</td><td>default 0.5; same for all sets</td><td></td></tr>
<tr><td>`bins`</td><td># nt or sequence or str, default: :rc:`hist.bins`If *bins* is an integer, it defines the number of equal-width bins in the range. If *bins* is a sequence, it defines the bin edges, including the left edge of the first bin and the right edge of the last bin; in this case, bins may be unequally spaced.  All but the last  (righthand-most) bin is half-open</td><td></td></tr>
<tr><td>`color`</td><td>a hash, where keys are the keys in data, and values are colors</td><td>`X => 'blue'`</td></tr>
<tr><td>`log`</td><td>if set to > 1, the y-axis will be logarithmic</td><td></td></tr>
<tr><td>`orientation`</td><td>{'vertical', 'horizontal'}, default: 'vertical'</td><td></td></tr>
</tbody>
</table>

=head3 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'
 });

which makes the following simple plot:


=for html
<p>
<img width="651" height="491" alt="single hist" src="https://github.com/user-attachments/assets/fafcf787-6c4f-4998-88c4-77a15d878fa6" />
<p>


=head3 multiple plots

 plot({
     'input.file'      => $tmp_filename,
     execute           => 0,
     'output.file' => 'output.images/histogram.png',
    set_figwidth => 15,
    suptitle          => 'hist Examples',
     plots             => [
         { # 1st subplot
             data => {
                 E => @e,
                 B => @b,
                 A => @a,
             },
             'plot.type' => 'hist',
             alpha       => 0.25,
             bins        => 50,
             title       => 'alpha = 0.25',
             color       => {
                 B => 'Black',
                 E => 'Orange',
                 A => 'Yellow',
             },
             scatter => '['
               . join( ',', 22 .. 44 ) . '],['  # x coords
               . join( ',', 22 .. 44 )          # y coords
               . '], label = "scatter"',
             xlabel   => 'Value',
             ylabel   => 'Frequency',
         },
         { # 2nd subplot
             data => {
                 E => @e,
                 B => @b,
                 A => @a,
             },
             'plot.type' => 'hist',
             alpha       => 0.75,
             bins        => 50,
             title       => 'alpha = 0.75',
             color       => {
                 B => 'Black',
                 E => 'Orange',
                 A => 'Yellow',
             },
             xlabel   => 'Value',
             ylabel   => 'Frequency',
         },
         { # 3rd subplot
             add               => [ # add secondary plots/graphs/methods
             { # 1st additional plot/graph
                 data              => {
                     'Gaussian'       => [
                         [40..150],
                         [map {150 * exp(-0.5*($_-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',
         },
         {# 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
             title        => 'Horizontal orientation',
             ylabel       => 'Value',
             xlabel       => 'Frequency',                #               'log'                   => 1,
         },
     ],
     ncols => 3,
     nrows => 2,
 });


=for html
<p>
<img width="1511" height="491" alt="histogram" src="https://github.com/user-attachments/assets/b13b4cc8-6e64-40b0-913d-6a5886cee0db" />
<p>


=head2 hist2d

=head3 options

=head3 single, simple plot

=head3 multiple plots

=head2 imshow

Plot 2D array of numbers as an image

=head3 options

=for html
<table>
<tbody>
<tr><td>Option</td><td>Description</td><td>Example</td></tr>
<tr><td>--------</td><td>-------</td><td>------- </td></tr>
<tr><td>`cblabel`</td><td>colorbar label</td><td>`cblabel => 'sin(x) * cos(x)',`</td></tr>
<tr><td>`cbdrawedges`</td><td>draw edges for colorbar</td><td></td></tr>
<tr><td>`cblocation`</td><td>'left', 'right', 'top', 'bottom'</td><td>`cblocation => 'left',`</td></tr>
<tr><td>`cborientation`</td><td>None, or 'vertical', 'horizontal'</td><td></td></tr>
<tr><td>`cmap`</td><td># The Colormap instance or registered colormap name used to map scalar data to colors.</td><td></td></tr>
<tr><td>`vmax`</td><td>float</td><td></td></tr>
<tr><td>`vmin`</td><td>float</td><td></td></tr>
</tbody>
</table>

=head3 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,
 });

which makes the following image:


=for html
<p>
<img width="599" height="491" alt="imshow single" src="https://github.com/user-attachments/assets/3fa4ffe6-4817-4133-9c91-b68099400377" />
<p>


=head3 multiple plots

 plot({
     plots  => [
         {
             data => \@imshow_data,
             'plot.type'       => 'imshow',
             set_xlim          => '0, ' . scalar @imshow_data,
             set_ylim          => '0, ' . scalar @imshow_data,
             title             => 'basic',
         },
         {
             cblabel           => 'sin(x) * cos(x)',
             data => \@imshow_data,
             'plot.type'       => 'imshow',
             set_xlim          => '0, ' . scalar @imshow_data,
             set_ylim          => '0, ' . scalar @imshow_data,
             title             => 'cblabel',
         },
         {
             cblabel           => 'sin(x) * cos(x)',
             cblocation        => 'left',
             data              => \@imshow_data,
             'plot.type'       => 'imshow',
             set_xlim          => '0, ' . scalar @imshow_data,
             set_ylim          => '0, ' . scalar @imshow_data,
             title             => 'cblocation = left',
         },
         {
             cblabel           => 'sin(x) * cos(x)',
             data              => \@imshow_data,
             add               => [ # add secondary plots
             { # 1st additional plot
                 data              => {
                     'sin(x)'       => [
                         [0..360],
                         [map {180 + 180*sin($_ * $pi/180)} 0..360]
                     ],
                     'cos(x)'       => [
                         [0..360],
                         [map {180 + 180*cos($_ * $pi/180)} 0..360]
                     ],
                 },
                 'plot.type' => 'plot',
                 'set.options' => {
                     'sin(x)'    =>  'color = "red", linestyle = "dashed"',
                     'cos(x)'    =>  'color = "blue", linestyle = "dashed"',
                 }
             }
             ],
             'plot.type'       => 'imshow',
             set_xlim          => '0, ' . scalar @imshow_data,
             set_ylim          => '0, ' . scalar @imshow_data,
             title             => 'auxiliary plots',
         },
     ],
     execute         => 0,
    'input.file'    => $tmp_filename,
     'output.file'   => 'output.images/imshow.multiple.png',
     ncols           => 2,
     nrows           => 2,
     set_figheight   => 6*3,# 4.8
     set_figwidth    => 6*4 # 6.4
 });

which makes the following image:


=for html
<p>
<img width="2416" height="1811" alt="imshow multiple" src="https://github.com/user-attachments/assets/091acccb-151c-47ca-82cc-99c19d2bff91" />
<p>


=head2 pie

=head3 options

=head3 single, simple plot

 plot({
     'output.file' => 'output.images/single.pie.png',
     data              => {                                 # simple hash
         Fri => 76,
         Mon => 73,
         Sat => 26,
         Sun => 11,
         Thu => 94,
         Tue => 93,
         Wed => 77
     },
     'plot.type'  => 'pie',
     title        => 'Single Simple Pie',
     'input.file' => $tmp_filename,
     execute      => 0,
 });

which makes the image:


=for html
<p>
<img width="469" height="491" alt="single pie" src="https://github.com/user-attachments/assets/a0bc3212-d013-463a-9be6-f96829ac7dba" />
<p>


=head3 multiple plots

 plot({
     'output.file' => 'output.images/pie.png',
     plots             => [
         {
             data => {
                 'Russian' => 106_000_000,    # Primarily European Russia
                 'German'  =>
                   95_000_000,    # Germany, Austria, Switzerland, etc.
                 'English' => 70_000_000,      # UK, Ireland, etc.
                 'French' => 66_000_000, # France, Belgium, Switzerland, etc.
                 'Italian'   => 59_000_000,    # Italy, Switzerland, etc.
                 'Spanish'   => 45_000_000,    # Spain
                 'Polish'    => 38_000_000,    # Poland
                 'Ukrainian' => 32_000_000,    # Ukraine
                 'Romanian'  => 24_000_000,    # Romania, Moldova
                 'Dutch'     => 22_000_000     # Netherlands, Belgium
             },
             '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.
                 'English' => 70_000_000,      # UK, Ireland, etc.
                 'French' => 66_000_000, # France, Belgium, Switzerland, etc.
                 'Italian'   => 59_000_000,    # Italy, Switzerland, etc.
                 'Spanish'   => 45_000_000,    # Spain
                 'Polish'    => 38_000_000,    # Poland
                 'Ukrainian' => 32_000_000,    # Ukraine
                 'Romanian'  => 24_000_000,    # Romania, Moldova
                 'Dutch'     => 22_000_000     # Netherlands, Belgium
             },
             'plot.type' => 'pie',
             title       => 'Top Languages in Europe',
             autopct     => '%1.1f%%',
         },
         {
             data => {
                 'United States'  => 86,
                 'United Kingdom' => 33,
                 'Germany'        => 29,
                 'France'         => 10,
                 'Japan'          => 7,
                 'Israel'         => 6,
             },
             title         => 'Chem. Nobels: swap text positions',
             'plot.type'   => 'pie',
             autopct       => '%1.1f%%',
             pctdistance   => 1.25,
             labeldistance => 0.6,
         }
     ],
     'input.file' => $tmp_filename,
     execute      => 0,
    set_figwidth  => 12,
     ncols        => 3,
 });


=for html
<p>
<img width="1210" height="444" alt="pie" src="https://github.com/user-attachments/assets/4c44d300-fd84-49bc-9a32-b73af54286cf" />
<p>


=head2 plot

=head3 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:


=for html
<p>
<img width="651" height="491" alt="plot single" src="https://github.com/user-attachments/assets/6cbd6aad-c464-4703-b962-b420ec08bb66" />
<p>


=head3 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


=for html
<p>
<img width="1211" height="491" alt="plot" src="https://github.com/user-attachments/assets/a8312147-e13d-4aa9-9997-49430bb5c74a" />
<p>


=head2 scatter

=head3 options

=head3 single, simple plot

=head3 multiple plots

 plot({
     'input.file'      => $tmp_filename,
     'output.file' => 'output.images/scatterplots.png',
     execute           => 0,
     nrows             => 2,
     ncols             => 3,
     set_figheight     => 8,
     set_figwidth      => 16,
     suptitle          => 'Scatterplot Examples',            # applies to all
     plots             => [
         {    # single-set scatter; no label
             data => {
                 X => @e,    # x-axis
                 Y => @b,    # y-axis
                 Z => @a     # color
             },
             title     => '"Single Set Scatterplot: Random Distributions"',
             color_key => 'Z',
             'set.options' => 'marker = "v"'
             , # arguments to ax.scatter: there's only 1 set, so "set.options" is a scalar
             text        => [ '100, 100, "text1"', '100, 100, "text2"', ],
             'plot.type' => 'scatter',
         },
         {     # multiple-set scatter, labels are "X" and "Y"
             data => {
                 X => {    # 1st data set; label is "X"
                     A => @a,    # x-axis
                     B => @b,    # y-axis
                 },
                 W => {    # 2nd data set; label is "Y"
                     A => generate_normal_dist( 100, 15, 210 ),    # x-axis
                     B => generate_normal_dist( 100, 15, 210 ),    # y-axis
                 }
             },
             'plot.type'   => 'scatter',
             title         => 'Multiple Set Scatterplot',
             'set.options' =>
             {    # arguments to ax.scatter, for each set in data
               X => 'marker = ".", color = "red"',
               W => 'marker = "d", color = "green"'
             },
         },
         {          # multiple-set scatter, labels are "X" and "Y"
             data => {    # 8th plot,
                 X => {    # 1st data set; label is "X"
                     A => @e,    # x-axis
                     B => @b,    # y-axis
                     C => @a,    # color
                 },
                 Y => {    # 2nd data set; label is "Y"
                     A => generate_normal_dist( 100, 15, 210 ),    # x-axis
                     B => generate_normal_dist( 100, 15, 210 ),    # y-axis
                     C => generate_normal_dist( 100, 15, 210 ),    # color
                 },
             },
             'plot.type'   => 'scatter',
             title         => 'Multiple Set Scatter w/ colorbar',
             'set.options' => {    # arguments to ax.scatter, for each set in data
                 X => 'marker = "."',    # diamond
                 Y => 'marker = "d"'     # diamond
             },
             color_key => 'Z',
         }
     ]
 });

which makes the following figure:


=for html
<p>
<img width="1610" height="461" alt="scatterplots" src="https://github.com/user-attachments/assets/b8a90f9f-acb3-4cf2-a423-6ad18686ab8c" />
<p>


=head2 violin

=head3 options

=head3 single, simple plot

 plot({
     'output.file' => 'output.images/single.violinplot.png',
     data              => {                                     # simple hash
         A => [ 55, @{$z} ],
         E => [ @{$y} ],
         B => [ 122, @{$z} ],
     },
     'plot.type'  => 'violinplot',
     title        => 'Single Violin Plot: Specified Colors',
     colors       => { E => 'yellow', B => 'purple', A => 'green' },
     'input.file' => $tmp_filename,
     execute      => 0,
 });

which makes:


=for html
<p>
<img width="651" height="491" alt="single violinplot" src="https://github.com/user-attachments/assets/989650fd-c947-45b0-91c8-c7f71c075cf3" />
<p>


=head3 multiple plots

 plot({
     'input.file'      => $tmp_filename,
     execute           => 0,
     'output.file' => 'output.images/violin.png',
     plots             => [
         {
             data => {
                 E => @e,
                 B => @b
             },
             'plot.type'  => 'violinplot',
             title        => 'Basic',
             xlabel       => 'xlabel',
             set_figwidth => 12,
             suptitle     => 'Violinplot'
         },
         {
             data => {
                 E => @e,
                 B => @b
             },
             'plot.type' => 'violinplot',
             color       => 'red',
             title       => 'Set Same Color for All',
         },
         {
             data => {
                 E => @e,
                 B => @b
             },
             'plot.type' => 'violinplot',
             colors      => {
                 E => 'yellow',
                 B => 'black'
             },
             title => 'Color by Key',
         },
         {
             data => {
                 E => @e,
                 B => @b
             },
             orientation => 'horizontal',
             'plot.type' => 'violinplot',
             colors      => {
                 E => 'yellow',
                 B => 'black'
             },
             title => 'Horizontal orientation',
         },
         {
             data => {
                 E => @e,
                 B => @b
             },
             whiskers    => 0,
             'plot.type' => 'violinplot',
             colors      => {
                 E => 'yellow',
                 B => 'black'
             },
             title => 'Whiskers off',
         },
     ],
     ncols => 3,
     nrows => 2,
 });


=for html
<p>
<img width="1211" height="491" alt="violin" src="https://github.com/user-attachments/assets/248df5e4-fd57-45d6-96da-956af0a7dbfb" />
<p>


=head2 wide

=head3 options

=head3 single, simple plot

=head3 multiple plots

=head1 Advanced

=head2 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;

all files will be written to $tmp_filename; be sure to put C<< execute =E<gt> 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,
 });
 # the last plot should have C<< execute =E<gt> 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,
 });
