ParaMonte MATLAB 3.0.0
Parallel Monte Carlo and Machine Learning Library
See the latest version documentation.
Subplot.m
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1%> \brief
2%> This is the abstract class for generating instances of axes
3%> with various types of plots from one or more columns of data.<br>
4%>
5%> \details
6%> While it can be directly used for visualization tasks,
7%> this class primarily serves as the superclass for the
8%> visualization subclasses accessible to the end users.<br>
9%>
10%> \note
11%> In case of [pm.vis.SubplotContour](@ref SubplotContour), [pm.vis.SubplotContour3](@ref SubplotContour3), and
12%> [pm.vis.SubplotContourf](@ref SubplotContourf) visualization objects, the density of the input data
13%> is first computed and smoothed by a Gaussian kernel density estimator and then passed to the
14%> MATLAB intrinsic plotting functions ``contour``, ``contourf``, ``contour3``.<br>
15%>
16%> Dynamic class attributes
17%> ------------------------
18%>
19%> This class contains a set of attributes that are defined dynamically at runtime
20%> for the output object depending on its subclass (plot type it represents).<br>
21%> The following is the list of all class attributes that are dynamically added
22%> to the instantiated class objects based on the specified input plot type.<br>
23%> See also the explicit class and superclass attributes not listed below.<br>
24%>
25%> <ol>
26%> <li> ``colx`` (standing for x-columns; available for all axes types)<br>
27%>
28%> Optional property that determines the columns of
29%> the specified dataframe to serve as the x-values.
30%> It can have multiple forms:<br>
31%> <ol>
32%> <li> a numeric or cell array of column indices in the input ``dfref``.
33%> <li> a string or cell array of column names in ``dfref.Properties.VariableNames``.
34%> <li> a cell array of a mix of the above two.
35%> <li> a numeric range.
36%> </ol>
37%> If ``colx`` is empty,<br>
38%> <ol>
39%> <li> it will be set to the row indices of ``dfref`` for line/scatter axes types.
40%> <li> it will be set to all columns of ``dfref`` for density axes types.
41%> </ol>
42%>
43%> \warning
44%> In all cases, ``colx`` must have a length that is either
45%> 0 (empty), 1, or equal to the length of ``coly`` or ``colz``.<br>
46%> If the length is 1, then ``colx`` will be plotted against
47%> data corresponding to each element of ``coly`` and ``colz``.<br>
48%>
49%> \example{colx}
50%> \code{.m}
51%>
52%> Subplot.colx = [7, 8, 9]
53%> Subplot.colx = ["sampleLogFunc", "sampleVariable1"]
54%> Subplot.colx = {"sampleLogFunc", 9, "sampleVariable1"}
55%> Subplot.colx = 7:9 # every column in the data frame starting from column #7 to #9
56%> Subplot.colx = 7:2:20 # every other column in the data frame starting from column #7 to #20
57%>
58%> \endcode
59%> <br>
60%>
61%> <li> ``coly`` (standing for y-columns; available for all axes types except
62%> [pm.vis.SubplotHeatmap](@ref SubplotHeatmap), [pm.vis.SubplotHistogram](@ref SubplotHistogram), [pm.vis.SubplotHistfit](@ref SubplotHistfit))<br>
63%>
64%> Optional property that determines the columns of
65%> the specified dataframe to serve as the z-values.<br>
66%> It can have multiple forms:<br>
67%> <ol>
68%> <li> a numeric or cell array of column indices in the input ``dfref``.
69%> <li> a string or cell array of column names in ``dfref.Properties.VariableNames``.
70%> <li> a cell array of a mix of the above two.
71%> <li> a numeric range.
72%> </ol>
73%> If ``coly`` is empty,<br>
74%> <ol>
75%> <li> it will be set to the row indices of ``dfref`` for line/scatter axes types.
76%> <li> it will be set to all columns of ``dfref`` for density axes types.
77%> </ol>
78%>
79%> \warning
80%> In all cases, ``coly`` must have a length that is either
81%> 0 (empty), 1, or equal to the length of ``colx`` or ``colz``.<br>
82%> If the length is 1, then ``coly`` will be plotted against
83%> data corresponding to each element of ``colx`` and ``colz``.<br>
84%>
85%> \example{coly}
86%> \code{.m}
87%>
88%> Subplot.coly = [7, 8, 9]
89%> Subplot.coly = ["sampleLogFunc", "sampleVariable1"]
90%> Subplot.coly = {"sampleLogFunc", 9, "sampleVariable1"}
91%> Subplot.coly = 7:9 # every column in the data frame starting from column #7 to #9
92%> Subplot.coly = 7:2:20 # every other column in the data frame starting from column #7 to #20
93%>
94%> \endcode
95%> <br>
96%>
97%> <li> ``colz`` (standing for z-columns; available only for 3D plots, e.g.,
98%> [pm.vis.SubplotLine3](@ref SubplotLine3), [pm.vis.SubplotScatter3](@ref SubplotScatter3),
99%> [pm.vis.SubplotLineScatter3](@ref SubplotLineScatter3))<br>
100%>
101%> Optional property that determines the columns of
102%> the specified dataframe to serve as the z-values.<br>
103%> It can have multiple forms:<br>
104%> <ol>
105%> <li> a numeric or cell array of column indices in the input ``dfref``.
106%> <li> a string or cell array of column names in ``dfref.Properties.VariableNames``.
107%> <li> a cell array of a mix of the above two.
108%> <li> a numeric range.
109%> </ol>
110%> If ``colz`` is empty,<br>
111%> <ol>
112%> <li> it will be set to the row indices of ``dfref`` for line/scatter axes types.
113%> <li> it will be set to all columns of ``dfref`` for density axes types.
114%> </ol>
115%>
116%> \warning
117%> In all cases, ``colz`` must have a length that is either
118%> 0 (empty), 1, or equal to the length of ``colx`` or ``coly``.<br>
119%> If the length is 1, then ``colz`` will be plotted against
120%> data corresponding to each element of ``colx`` and ``coly``.<br>
121%>
122%> \example{colz}
123%> \code{.m}
124%>
125%> Subplot.colz = [7, 8, 9]
126%> Subplot.colz = ["sampleLogFunc", "sampleVariable1"]
127%> Subplot.colz = {"sampleLogFunc", 9, "sampleVariable1"}
128%> Subplot.colz = 7:9 % every column in the data frame starting from column #7 to #9
129%> Subplot.colz = 7:2:20 % every other column in the data frame starting from column #7 to #20
130%>
131%> \endcode
132%> <br>
133%>
134%> <li> ``colc`` (standing for color-columns; available only for 2D/3D line/scatter axes types, e.g.,
135%> [pm.vis.SubplotLine3](@ref SubplotLine3), [pm.vis.SubplotScatter3](@ref SubplotScatter3),
136%> [pm.vis.SubplotLineScatter3](@ref SubplotLineScatter3), [pm.vis.SubplotLine](@ref SubplotTileLine),
137%> [pm.vis.SubplotScatter](@ref SubplotScatter), [pm.vis.SubplotLineScatter](@ref SubplotLineScatter))<br>
138%>
139%> Optional property that determines the columns of the input ``dfref`` to
140%> use as the color mapping values for each line/point element in the plot.<br>
141%> It can have multiple forms:<br>
142%> <ol>
143%> <li> a numeric or cell array of column indices in the input ``dfref``.
144%> <li> a string or cell array of column names in ``dfref.Properties.VariableNames``.
145%> <li> a cell array of a mix of the above two.
146%> <li> a numeric range.
147%> </ol>
148%> The default value is the indices of the rows of the input ``dfref``.<br>
149%> \example{colc}
150%> \code{.m}
151%>
152%> Subplot.colc = [7,8,9]
153%> Subplot.colc = ["sampleLogFunc", "sampleVariable1"]
154%> Subplot.colc = {"sampleLogFunc", 9, "sampleVariable1"}
155%> Subplot.colc = 7:9 # every column in the data frame starting from column #7 to #9
156%> Subplot.colc = 7:2:20 # every other column in the data frame starting from column #7 to #20
157%>
158%> \endcode
159%> <br>
160%> </ol>
161%>
162%> \note
163%> For example usage, see the documentation of the constructor of
164%> the class [pm.vis.Subplot::Subplot](@ref Subplot::Subplot).<br>
165%>
166%> \devnote
167%> While dynamic addition of class attributes is not ideal, the current
168%> design was deemed unavoidable and best, given the constraints of the
169%> MATLAB language and visualization tools.<br>
170%>
171%> \see
172%> [pm.vis](@ref \psldir/main/+pm/+vis)<br>
173%> [pm.vis.axes.Axes](@ref Axes)<br>
174%> [pm.matlab.Handle](@ref Handle)<br>
175%> [pm.vis.Cascade](@ref Cascade)<br>
176%> [pm.vis.Subplot](@ref Subplot)<br>
177%> [pm.vis.Figure](@ref Figure)<br>
178%> [pm.vis.Corner](@ref Corner)<br>
179%> [pm.vis.Plot](@ref Plot)<br>
180%> [pm.vis.Tile](@ref Tile)<br>
181%>
182%> \final
183%>
184%> \author
185%> \FatemehBagheri, May 20 2024, 1:25 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
186%> \AmirShahmoradi, May 16 2016, 9:03 AM, Oden Institute for Computational Engineering and Sciences (ICES), UT Austin<br>
187classdef Subplot < pm.vis.axes.Axes
188
189 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
190
191 properties(Access = public)
192 %>
193 %> ``df``
194 %>
195 %> A scalar object of class [pm.data.DataFrame](@ref DataFrame)
196 %> containing the user-specified data to visualize.<br>
197 %>
198 df = [];
199 %>
200 %> ``fout``
201 %>
202 %> A MATLAB ``struct`` whose fields are the outputs of
203 %> various plotting tools used to make the current axis.<br>
204 %>
205 fout = struct();
206 %>
207 %> ``rows``
208 %>
209 %> A numeric vector that serves as a storage for an arbitrary subset of indices
210 %> of the rows of the input dataframe reference ``dfref`` to the class constructor .<br>
211 %> It can be either:<br>
212 %> <ol>
213 %> <li> a numeric range, or,
214 %> <li> a list of row indices of the ``dfref``.
215 %> </ol>
216 %>
217 %> \example{rows}
218 %> \code{fout}
219 %>
220 %> s = pm.vis.Subplot();
221 %>
222 %> s.rows = 15 : -2 : 8;
223 %> s.rows = [12, 46, 7, 8, 9, 4, 7, 163];
224 %>
225 %> \endcode
226 %>
227 %> \warning
228 %> If ``rows`` is empty, the default will be all rows of the ``dfref``.<br>
229 %>
230 %> \note
231 %> The [pm.data.DataFrame.rowslog()](@ref DataFrame::rowslog) method of
232 %> this class can be used to generate logarithmically-spaced
233 %> row indices of the target dataframe.<br>
234 %>
235 rows = [];
236 end
237
238 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
239
240 methods(Access = public)
241
242 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
243
244 %> \brief
245 %> Construct and return an object of class [pm.vis.Subplot](@ref Subplot).<br>
246 %>
247 %> \details
248 %> This is the custom constructor of the class [pm.vis.Subplot](@ref Subplot).<br>
249 %>
250 %> \param[in] ptype : See the documentation of the corresponding input argument of the
251 %> superclass constructor [pm.vis.axes.Axes::Axes](@ref Axes::Axes).<br>
252 %> \param[in] dfref : The input MATLAB matrix or table containing the data to plot or
253 %> a function handle that returns such a MATLAB matrix or table.<br>
254 %> Specifying a function handle is superior to specifying the
255 %> data directly, because the function handle will always use
256 %> the most updated version of the user table or matrix.<br>
257 %> (**optional**. The default is an empty table.)
258 %>
259 %> \return
260 %> ``self`` : The output scalar object of class [pm.vis.Subplot](@ref Subplot).<br>
261 %>
262 %> \interface{Subplot}
263 %> \code{.m}
264 %>
265 %> s = pm.vis.Subplot(ptype, dfref);
266 %> s = pm.vis.Subplot(ptype, dfref, varargin);
267 %>
268 %> \endcode
269 %>
270 %> \warning
271 %> In all cases, ``colc`` must have a length that is either
272 %> 0, or 1, or equal to the maximum lengths of ``(colx, coly, colz)``.<br>
273 %> If the length is 1, then all data will be plotted with the same color
274 %> mapping determined by values specified by the elements of ``colc``.<br>
275 %> If it is an empty object having length 0, then the default value will be used.<br>
276 %>
277 %> \note
278 %> In case of [pm.vis.SubplotContour](@ref SuplotContour)/[pm.vis.SubplotContourf](@ref SuplotContourf)/[pm.vis.SubplotContour3](@ref SuplotContour3)
279 %> visualization objects, the density of the input data is first computed and smoothed
280 %> by a Gaussian kernel density estimator and then passed to the MATLAB intrinsic
281 %> plotting functions , ``contour``, ``contourf``, ``contour3``.<br>
282 %>
283 %> \example{Subplot}
284 %> \include{lineno} example/vis/Subplot/main.m
285 %> \vis{Subplot}
286 %> <br>\image html example/vis/Subplot/SubplotLine.1.png width=700
287 %> <br>\image html example/vis/Subplot/SubplotLine3.1.png width=700
288 %> <br>\image html example/vis/Subplot/SubplotScatter.1.png width=700
289 %> <br>\image html example/vis/Subplot/SubplotScatter3.1.png width=700
290 %> <br>\image html example/vis/Subplot/SubplotLineScatter.1.png width=700
291 %> <br>\image html example/vis/Subplot/SubplotLineScatter3.1.png width=700
292 %> <br>\image html example/vis/Subplot/SubplotHistfit.1.png width=700
293 %> <br>\image html example/vis/Subplot/SubplotHistogram.1.png width=700
294 %> <br>\image html example/vis/Subplot/SubplotHistogram2.1.png width=700
295 %> <br>\image html example/vis/Subplot/SubplotContour.1.png width=700
296 %> <br>\image html example/vis/Subplot/SubplotContourf.1.png width=700
297 %> <br>\image html example/vis/Subplot/SubplotContour3.1.png width=700
298 %> <br>\image html example/vis/Subplot/SubplotHeatmap.1.png width=700
299 %> <br>\image html example/vis/Subplot/SubplotEllipse3.1.png width=700
300 %> <br>\image html example/vis/Subplot/SubplotEllipse.1.png width=700
301 %>
302 %> \endcode
303 %>
304 %> \final{Subplot}
305 %>
306 %> \author
307 %> \JoshuaOsborne, May 22 2024, 6:45 PM, University of Texas at Arlington<br>
308 %> \AmirShahmoradi, July 5 2024, 1:07 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
309 function self = Subplot(ptype, dfref, varargin)
310 if nargin < 2
311 dfref = [];
312 end
313 if nargin < 1
314 ptype = [];
315 end
316 self@pm.vis.axes.Axes(ptype, varargin{:});
317 self.df = pm.data.DataFrame(dfref);
318 end
319
320 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
321
322 %> \brief
323 %> Generate a plot from the selected columns
324 %> of the parent object component ``df``.<br>
325 %>
326 %> \param[inout] self : The input/output parent object of class [pm.vis.Subplot](@ref Subplot)
327 %> which is **implicitly** passed to this dynamic method (not by the user).<br>
328 %> \param[in] varargin : Any ``property, value`` pair of the parent object.<br>
329 %> If the property is a ``struct()``, then its value must be given as a cell array,
330 %> with consecutive elements representing the struct ``property-name, property-value`` pairs.<br>
331 %> Note that all of these property-value pairs can be also directly set via the
332 %> parent object attributes, before calling the ``make()`` method.<br>
333 %>
334 %> \interface{make}
335 %> \code{.m}
336 %>
337 %> s = pm.vis.Subplot(ptype, dfref)
338 %>
339 %> s.make(varargin);
340 %> s.make();
341 %>
342 %> \endcode
343 %>
344 %> \warning
345 %> This method has side-effects by manipulating
346 %> the existing attributes of the parent object.<br>
347 %>
348 %> \example{make}
349 %> \code{.m}
350 %>
351 %> dfref = rand(1000, 3);
352 %> s = pm.vis.Subplot("scatter", dfref);
353 %> s.make("colx", 1, "coly", 2, "colc", 3)
354 %>
355 %> \endcode
356 %>
357 %> \example{Subplot}
358 %> \include{lineno} example/vis/Subplot/main.m
359 %> \vis{Subplot}
360 %> <br>\image html example/vis/Subplot/SubplotLine.1.png width=700
361 %> <br>\image html example/vis/Subplot/SubplotLine3.1.png width=700
362 %> <br>\image html example/vis/Subplot/SubplotScatter.1.png width=700
363 %> <br>\image html example/vis/Subplot/SubplotScatter3.1.png width=700
364 %> <br>\image html example/vis/Subplot/SubplotLineScatter.1.png width=700
365 %> <br>\image html example/vis/Subplot/SubplotLineScatter3.1.png width=700
366 %> <br>\image html example/vis/Subplot/SubplotHistfit.1.png width=700
367 %> <br>\image html example/vis/Subplot/SubplotHistogram.1.png width=700
368 %> <br>\image html example/vis/Subplot/SubplotHistogram2.1.png width=700
369 %> <br>\image html example/vis/Subplot/SubplotContour.1.png width=700
370 %> <br>\image html example/vis/Subplot/SubplotContourf.1.png width=700
371 %> <br>\image html example/vis/Subplot/SubplotContour3.1.png width=700
372 %> <br>\image html example/vis/Subplot/SubplotHeatmap.1.png width=700
373 %> <br>\image html example/vis/Subplot/SubplotEllipse3.1.png width=700
374 %> <br>\image html example/vis/Subplot/SubplotEllipse.1.png width=700
375 %>
376 %> \final{make}
377 %>
378 %> \author
379 %> \JoshuaOsborne, May 22 2024, 6:36 PM, University of Texas at Arlington<br>
380 %> \FatemehBagheri, May 20 2024, 1:25 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
381 %> \AmirShahmoradi, July 5 2024, 1:07 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
382 function make(self, varargin)
383
384 self.premake(varargin{:});
385
386 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
387 %%%% RULE 0: No component of ``self`` is allowed to appear to the left of assignment operator, except ``fout``.
388 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
389
390 %%%% Set what to plot.
391
392 noPlotEnabled = false;
393 noPlotEnabled = noPlotEnabled || (self.type.is.scatter && ~self.scatter.enabled);
394 noPlotEnabled = noPlotEnabled || (self.type.is.scatter3 && ~self.scatter3.enabled);
395 noPlotEnabled = noPlotEnabled || (self.type.is.line && ~self.plot.enabled && ~self.surface.enabled);
396 noPlotEnabled = noPlotEnabled || (self.type.is.line3 && ~self.plot3.enabled && ~self.surface.enabled);
397 noPlotEnabled = noPlotEnabled || (self.type.is.lineScatter && ~self.plot.enabled && ~self.surface.enabled && ~self.scatter.enabled);
398 noPlotEnabled = noPlotEnabled || (self.type.is.lineScatter3 && ~self.plot3.enabled && ~self.surface.enabled && ~self.scatter3.enabled);
399 noPlotEnabled = noPlotEnabled || (self.type.is.histogram2 && ~self.histogram2.enabled);
400 noPlotEnabled = noPlotEnabled || (self.type.is.histogram && ~self.histogram.enabled);
401 noPlotEnabled = noPlotEnabled || (self.type.is.contourf && ~self.contourf.enabled);
402 noPlotEnabled = noPlotEnabled || (self.type.is.contour3 && ~self.contour3.enabled);
403 noPlotEnabled = noPlotEnabled || (self.type.is.histfit && ~self.histfit.enabled);
404 noPlotEnabled = noPlotEnabled || (self.type.is.contour && ~self.contour.enabled);
405 noPlotEnabled = noPlotEnabled || (self.type.is.heatmap && ~self.heatmap.enabled);
406 if noPlotEnabled
407 error ( newline ...
408 + "All plot types are deactivated by the user. There is nothing to display." + newline ...
409 + "Enable at least one the following plotting components of the parent object." + newline ...
410 + newline ...
411 );
412 end
413
414 dfcopy = self.df.copy();
415 if isempty(dfcopy)
416 help("pm.vis.Subplot");
417 error ( newline ...
418 + "There is no data to plot." + newline ...
419 + "Without any input data, visualizations are impossible." + newline ...
420 + "The input argument ``dfref`` to the object constructor was likely empty." + newline ...
421 + "If you merely want to create a template of visualization specifications," + newline ...
422 + "then use the class [pm.vis.axes.Axes](@ref Axes) which is the superclass of this class." + newline ...
423 + "For more information, see the class documentation displayed above." + newline ...
424 + newline ...
425 );
426 end
427
428 %%%%
429 %%%% check rows presence
430 %%%%
431
432 if pm.array.len(self.rows)
433 rowsindex = self.rows(:);
434 else
435 rowsindex = [1 : self.df.nrow()]';
436 end
437
438 %%%%%%%%%%%%%%%%%%%%%%%%%%%
439 %%%% check columns presence
440 %%%%%%%%%%%%%%%%%%%%%%%%%%%
441
442 coldatx = []; colindx = []; colnamx = [];
443 if isprop(self, "colx") && pm.array.len(self.colx)
444 [colindx, colnamx] = pm.str.locname(dfcopy.Properties.VariableNames, self.colx);
445 elseif self.type.is.heatmap || self.type.is.d1
446 colnamx = dfcopy.Properties.VariableNames;
447 colindx = 1 : length(colnamx);
448 else
449 coldatx = rowsindex;
450 colnamx = "Row Index";
451 end
452
453 coldaty = []; colindy = []; colnamy = [];
454 if isprop(self, "coly") && pm.array.len(self.coly)
455 [colindy, colnamy] = pm.str.locname(dfcopy.Properties.VariableNames, self.coly);
456 elseif self.type.is.density && ~self.type.is.histogram2
457 if isfield(self.(self.type.name), "normalization") && ~isempty(self.(self.type.name).normalization)
458 colnamy = string(self.(self.type.name).normalization);
459 elseif self.type.is.d1
460 colnamy = "Count";
461 else
462 colnamy = "Density";
463 end
464 elseif self.type.is.heatmap
465 if isempty(dfcopy.Properties.RowNames)
466 dfcopy.Properties.RowNames = string(rowsindex);
467 end
468 colnamy = dfcopy.Properties.RowNames;
469 else
470 coldaty = rowsindex;
471 colnamy = "Row Index";
472 end
473
474 coldatz = []; colindz = []; colnamz = [];
475 if isprop(self, "colz") && pm.array.len(self.colz)
476 [colindz, colnamz] = pm.str.locname(dfcopy.Properties.VariableNames, self.colz);
477 elseif self.type.has.line || self.type.has.scatter
478 if ~self.type.is.d3
479 % This is necessary for 2D surface plot.
480 coldatz = zeros(length(rowsindex), 1);
481 else
482 coldatz = rowsindex;
483 colnamz = "Row Index";
484 end
485 elseif self.type.is.density && self.type.is.triaxes
486 colnamz = "Density";
487 end
488
489 coldatc = []; colindc = []; colnamc = [];
490 if isprop(self, "colc") && pm.array.len(self.colc)
491 [colindc, colnamc] = pm.str.locname(dfcopy.Properties.VariableNames, self.colc);
492 elseif self.type.has.line || self.type.has.scatter
493 if ~isempty(colnamz) && ~(isempty(coldatz) && isempty(colindz))
494 coldatc = coldatz;
495 colindc = colindz;
496 colnamc = colnamz;
497 else
498 coldatc = rowsindex;
499 colnamc = "Row Index";
500 end
501 elseif self.type.is.density && ~self.type.is.d1
502 colnamc = "Density";
503 end
504
505 %%%% check the lengths are consistent.
506
507 colindlen = max([ length(colindc) ...
508 , length(colindz) ...
509 , length(colindy) ...
510 , length(colindx) ...
511 ]);
512
513 if length(colindc) ~= colindlen && 1 < length(colindc); error("length of colx must be either 1 or equal to the maximum of the lengths of coly, colz, colc."); end
514 if length(colindz) ~= colindlen && 1 < length(colindz); error("length of coly must be either 1 or equal to the maximum of the lengths of colx, colz, colc."); end
515 if length(colindy) ~= colindlen && 1 < length(colindy); error("length of colz must be either 1 or equal to the maximum of the lengths of colx, coly, colc."); end
516 if length(colindx) ~= colindlen && 1 < length(colindx); error("length of colc must be either 1 or equal to the maximum of the lengths of colx, coly, colz."); end
517
518 %%%% assign data in case of single column assignments.
519
520 if length(colindx) == 1; coldatx = dfcopy{rowsindex, colindx}; end
521 if length(colindy) == 1; coldaty = dfcopy{rowsindex, colindy}; end
522 if length(colindz) == 1; coldatz = dfcopy{rowsindex, colindz}; end
523 if length(colindc) == 1; coldatc = dfcopy{rowsindex, colindc}; end
524
525 %%%% get keyword arguments.
526
527 kws = struct();
528 for prop = [ "axes" ...
529 , "colorbar" ...
530 , "colormap" ...
531 , "contour" ...
532 , "contour3" ...
533 , "contourf" ...
534 , "legend" ...
535 , "heatmap" ...
536 , "histfit" ...
537 , "histogram" ...
538 , "histogram2" ...
539 , "plot" ...
540 , "plot3" ...
541 , "scatter" ...
542 , "scatter3" ...
543 , "surface" ...
544 , "title" ...
545 , "xlabel" ...
546 , "ylabel" ...
547 , "zlabel" ...
548 ]
549 if isprop(self, prop)
550 kws.(prop) = self.comp2hash(prop);
551 end
552 end
553
554 for prop = ["scatter", "scatter3"]
555 if isprop(self, prop) && self.(prop).filled
556 kws.(prop) = [{"filled"}; kws.(prop)(:)];
557 end
558 end
559
560 %%%% generate the kde2d density estimates for the contour plots.
561
562 kde2dUpdateNeeded = self.type.is.diffusion && (1 < length(colindx) || 1 < length(colindy));
563 if self.type.is.diffusion
564 kde2d = struct();
565 if ~kde2dUpdateNeeded
566 [kde2d.bandwidth, kde2d.density, kde2d.crdx, kde2d.crdy] = pm.stats.hist.kde2d([coldatx(:), coldaty(:)], self.resolution);
567 kde2d.density(kde2d.density < self.maxnoise) = NaN;
568 end
569 end
570
571 %%%% determine the multicolor nature of the plots.
572
573 isMultiColorPlot = false;
574 if ~self.cenabled && (self.type.has.scatter || self.type.is.diffusion)
575 if self.type.is.diffusion
576 prop = self.type.name;
577 elseif self.type.is.d2
578 prop = "scatter";
579 elseif self.type.is.d3
580 prop = "scatter3";
581 else
582 error("Internal error occurred. A line/scatter plot must be either 2D or 3D.");
583 end
584 if pm.array.len(self.(prop).color)
585 if all(size(self.(prop).color) == [colindlen, 3])
586 isMultiColorPlot = true;
587 multiColorList = self.(prop).color;
588 elseif all(size(self.(prop).color) == [1, 3]) || self.type.is.diffusion
589 coldatc = self.(prop).color;
590 else
591 error ( newline ...
592 + "The value specified for the 'color' property of the " + prop + " component" + newline ...
593 + "must be either an RGB triplet vector of size [1, 3], or a matrix of size [" + string(colindlen) + ", 3]" + newline ...
594 + "for the current set of variables that are selected to plot. " + newline ...
595 + "It can also be an empty object, in which case, the colors" + newline ...
596 + "of the objects in the plot will be chosen automatically." + newline ...
597 + newline ...
598 );
599 end
600 else
601 multiColorList = lines(colindlen);
602 isMultiColorPlot = true;
603 end
604 elseif self.type.is.diffusion && ~pm.array.len(self.(self.type.name).color)
605 coldatc = self.(self.type.name).color;
606 end
607
608 %%%% initiate the legend.
609
610 legendary = isprop(self, "legend") && self.legend.enabled;
611 if legendary
612 legempty = pm.array.len(self.legend.labels) == 0;
613 lglabels = strings(colindlen, 1);
614 icollgx = 1;
615 icollgy = 1;
616 icollgz = 1;
617 end
618
619 %%%% generate axes and set axes properties.
620
621 if isprop(self, "axes")
622 self.fout.axes = gca;
623 if self.axes.enabled
624 % This setting must happen here, before any
625 % individual axes component settings below.
626 set(gca, kws.axes{:});
627 end
628 if self.type.is.triaxes
629 view(3);
630 end
631 hold on;
632 end
633
634 %%%%
635 %%%% Ensure points and lines are scaled properly.
636 %%%% It is not clear whether it's worth doing so because
637 %%%% most figure resizing happen after making it,
638 %%%% which makes the following solution useless.
639 %%%%
640
641 % temp = [];
642 % if ~strcmpi(self.fout.axes.Units, "normalized")
643 % temp = self.fout.axes.Units;
644 % self.fout.axes.Units = "normalized";
645 % end
646 % defaultSizeFig = [560, 420] % width, height in pixels.
647 % defaultSizeAxes = [0.775, 0.815] % width, height in pixels (assuming no colorbar).
648 % self.fout.axes.Position
649 % if ~isempty(temp)
650 % self.fout.axes.Units = temp;
651 % end
652
653 %%%% Make plots.
654
655 if self.type.is.heatmap && self.heatmap.enabled
656
657 if ~isempty(self.precision)
658 self.fout.heatmap = heatmap(colnamx, colnamy, round(dfcopy{colnamy, colnamx}, self.precision), kws.heatmap{:});
659 else
660 self.fout.heatmap = heatmap(colnamx, colnamy, dfcopy{colnamy, colnamx}, kws.heatmap{:});
661 end
662
663 else
664
665 if ~self.type.has.line && ~self.type.has.scatter
666 % line/scatter plots must be taken care of separately.
667 self.fout.(self.type.name) = cell(colindlen, 1);
668 end
669
670 for icol = 1 : colindlen
671
672 %%%% set the data to plot.
673
674 if 1 < length(colindx); if legendary; icollgx = icol; end; coldatx = dfcopy{rowsindex, colindx(icol)}; end
675 if 1 < length(colindy); if legendary; icollgy = icol; end; coldaty = dfcopy{rowsindex, colindy(icol)}; end
676 if 1 < length(colindz); if legendary; icollgz = icol; end; coldatz = dfcopy{rowsindex, colindz(icol)}; end
677
678 if isMultiColorPlot
679 coldatc = multiColorList(icol, :);
680 elseif 1 < length(colindc)
681 coldatc = dfcopy{rowsindex, colindc(icol)};
682 end
683
684 if self.type.is.diffusion
685 if ~isempty(coldatc)
686 kws.(self.type.name) = pm.matlab.hashmap.repKeyVal("color", coldatc, kws.(self.type.name));
687 end
688 if kde2dUpdateNeeded
689 [kde2d.bandwidth, kde2d.density, kde2d.crdx, kde2d.crdy] = pm.stats.hist.kde2d([coldatx(:), coldaty(:)], self.resolution);
690 kde2d.density(kde2d.density < self.maxnoise) = NaN;
691 end
692 end
693
694 %%%% set the default legend.
695
696 if legendary && legempty
697 if 1 < length(colindz)
698 suffix = "-" + colnamz(icollgz);
699 else
700 suffix = "";
701 end
702 if length(colindx) < 2 && 1 < length(colindy)
703 lglabels(icol) = colnamy(icollgy) + suffix;
704 elseif 1 < length(colindx) && length(colindy) < 2
705 lglabels(icol) = colnamx(icollgx) + suffix;
706 else
707 lglabels(icol) = colnamx(icollgx) + "-" + colnamy(icollgy) + suffix;
708 end
709 end
710
711 %%%% add density plot.
712
713 if self.type.is.contour
714 self.fout.contour{icol} = struct();
715 [self.fout.contour{icol}.matrix, self.fout.contour{icol}.handle] = contour ( kde2d.crdx ...
716 , kde2d.crdy ...
717 , kde2d.density ...
718 , self.contour.levels ...
719 , kws.contour{:} ...
720 );
721 elseif self.type.is.contour3
722 self.fout.contour3{icol} = struct();
723 [self.fout.contour3{icol}.matrix, self.fout.contour3{icol}.handle]= contour3( kde2d.crdx...
724 , kde2d.crdy...
725 , kde2d.density...
726 , self.contour3.levels ...
727 , kws.contour3{:} ...
728 );
729 elseif self.type.is.contourf
730 self.fout.contourf{icol} = struct();
731 [self.fout.contourf{icol}.matrix, self.fout.contourf{icol}.handle]= contourf( kde2d.crdx ...
732 , kde2d.crdy ...
733 , kde2d.density ...
734 , self.contourf.levels ...
735 , kws.contourf{:} ...
736 );
737 elseif self.type.is.histfit
738 self.fout.histfit{icol} = histfit(coldatx, self.histfit.nbins, self.histfit.dist, kws.histfit{:});
739 self.fout.histfit{icol}(1).FaceAlpha = 0.6; % make histogram face transparent 60%
740 self.fout.histfit{icol}(1).EdgeAlpha = 0; % make histogram lines invisible
741 self.fout.histfit{icol}(2).Color = "black"; % make the fitted line black
742 elseif self.type.is.histogram
743 if ~isempty(self.histogram.nbins)
744 self.fout.histogram{icol} = histogram(coldatx, self.histogram.nbins, kws.histogram{:});
745 elseif ~isempty(self.histogram.edges)
746 self.fout.histogram{icol} = histogram(coldatx, self.histogram.edges, kws.histogram{:});
747 else
748 self.fout.histogram{icol} = histogram(coldatx, kws.histogram{:});
749 end
750 elseif self.type.is.histogram2
751 self.fout.histogram2{icol} = histogram2(coldatx, coldaty, kws.histogram2{:});
752 end
753
754 %%%% add line plot.
755
756 if self.type.has.line
757 if self.type.is.d2 && self.plot.enabled
758 self.fout.plot{icol} = plot ( coldatx ...
759 , coldaty ...
760 , kws.plot{:} ...
761 );
762 elseif self.type.is.d3 && self.plot3.enabled
763 self.fout.plot3{icol} = plot3 ( coldatx ...
764 , coldaty ...
765 , coldatz ...
766 , kws.plot3{:} ...
767 );
768 end
769 if self.surface.enabled && self.colormap.enabled
770 self.fout.surface{icol} = surface ( "XData", [coldatx(:), coldatx(:)] ...
771 , "YData", [coldaty(:), coldaty(:)] ...
772 , "ZData", [coldatz(:), coldatz(:)] ...
773 , "CData", [coldatc(:), coldatc(:)] ...
774 , kws.surface{:} ...
775 );
776 end
777 end
778
779 %%%% add scatter plot.
780
781 if self.type.has.scatter
782 if self.type.is.d3 && self.scatter3.enabled
783 self.fout.scatter3{icol} = scatter3 ( coldatx ...
784 , coldaty ...
785 , coldatz ...
786 , self.scatter3.size ...
787 , coldatc ...
788 , self.scatter3.marker ...
789 , kws.scatter3{:} ...
790 );
791 elseif self.type.is.d2 && self.scatter.enabled
792 self.fout.scatter{icol} = scatter ( coldatx ...
793 , coldaty ...
794 , self.scatter.size ...
795 , coldatc ...
796 , self.scatter.marker ...
797 , kws.scatter{:} ...
798 );
799 end
800 end
801
802 end % loop over plots
803
804 end % if heatmap plot.
805
806 % add axis labels.
807 if ~self.type.is.heatmap
808 if isprop(self, "xlabel") && self.xlabel.enabled; if ~pm.array.len(self.xlabel.txt); txt = colnamx; else; txt = self.xlabel.txt; end; self.fout.xlabel = xlabel(txt, kws.xlabel{:}); end
809 if isprop(self, "ylabel") && self.ylabel.enabled; if ~pm.array.len(self.ylabel.txt); txt = colnamy; else; txt = self.ylabel.txt; end; self.fout.ylabel = ylabel(txt, kws.ylabel{:}); end
810 if isprop(self, "zlabel") && self.zlabel.enabled; if ~pm.array.len(self.zlabel.txt); txt = colnamz; else; txt = self.zlabel.txt; end; self.fout.zlabel = zlabel(txt, kws.zlabel{:}); end
811 else
812 if isprop(self, "xlabel") && self.xlabel.enabled; xlabel(self.xlabel.txt, kws.xlabel{:}); end
813 if isprop(self, "ylabel") && self.ylabel.enabled; ylabel(self.ylabel.txt, kws.ylabel{:}); end
814 end
815
816 % add the colormap and colorbar.
817
818 if ~self.cenabled && self.type.is.heatmap
819 colormap(flipud(gray)); % self.fout.colormap =
820 elseif ~self.cenabled && self.type.is.contourf
821 colormap(self.fout.axes, flipud(gray)); % self.fout.colormap =
822 elseif self.cenabled
823 if ~isempty(self.colormap.map) || (isstring(self.colormap.map) && self.colormap.map ~= "")
824 cmap = self.colormap.map;
825 else
826 if self.type.has.line || self.type.has.scatter
827 cmap = "winter";
828 %if self.type.is.d3
829 % self.colormap.map = "winter";
830 %else
831 % self.colormap.map = "autumn";
832 %end
833 elseif self.type.is.heatmap
834 cmap = pm.vis.cmap.redblue();
835 elseif self.type.is.density
836 cmap = "parula";
837 end
838 end
839 if ~self.type.is.heatmap
840 colormap(self.fout.axes, cmap); % self.fout.colormap =
841 else
842 colormap(cmap); % self.fout.colormap =
843 end
844 end
845
846 if isprop(self, "colorbar")
847 if self.colorbar.enabled && (self.cenabled || self.type.is.contourf)
848 if isempty(self.colorbar.fontSize) %|| ~isa(self.colorbar.fontSize, "numeric")
849 kws.colorbar = [kws.colorbar(:); {"fontSize"}; {self.fout.axes.FontSize + 1}];
850 end
851 self.fout.colorbar = colorbar(kws.colorbar{:});
852 ylabel(self.fout.colorbar, colnamc(1));%, "fontSize", self.colorbar.fontSize, "interpreter", "none"
853 else
854 colorbar('off');
855 self.fout.colorbar = [];
856 end
857 end
858
859 % add legend.
860
861 if legendary && 0 < colindlen
862 self.fout.legend = [];
863 if ~legempty
864 lglabels = self.legend.labels;
865 end
866 if ~self.legend.enabled
867 legend(self.fout.axes, "off");
868 elseif isa(self.legend.labels, "cell") || isa(self.legend.labels, "string")
869 if isempty(self.legend.fontSize)
870 kws.legend = [kws.legend(:); {"fontSize"}; {self.fout.axes.FontSize + 1}];
871 end
872 subset = [];
873 if self.type.has.scatter && self.type.is.d2 && self.scatter.enabled
874 subset = [self.fout.scatter{:}];
875 elseif self.type.has.scatter && self.type.is.d3 && self.scatter3.enabled
876 subset = [self.fout.scatter3{:}];
877
878 elseif self.type.is.histfit && self.histfit.enabled
879 nhandle = length(self.fout.histfit);
880 subset = cell(nhandle, 1);
881 for i = 1 : nhandle
882 subset{i} = self.fout.histfit{i}(1); % get the handle to the histogram component of histfit.
883 end
884 subset = [subset{:}];
885 end
886 if ~isempty(subset)
887 self.fout.legend = legend(subset, lglabels{:}, kws.legend{:});
888 else
889 self.fout.legend = legend(lglabels{:}, kws.legend{:});
890 end
891 else
892 error ( newline ...
893 + "The specified ""legend.labels"" must be a cell array of string values." ...
894 + newline ...
895 );
896 end
897 end
898
899 %if self.type.is.targetable
900 % self.target.fout.axes = self.fout.axes;
901 %end
902
903 %%%% add title.
904
905 if self.title.enabled
906 titletxt = {};
907 for field = ["titletext", "subtitletext"] % do not change the order of elements here.
908 if isfield(self.title, field) && pm.array.len(self.title.(field))
909 titletxt = [titletxt(:); self.title.(field)(:)];
910 end
911 end
912 if ~isempty(titletxt)
913 if ~self.type.is.heatmap
914 %if ~isempty(kws)
915 % kws.title = {titletxt{:}, kws.title(:)};
916 %end
917 self.fout.title = title(self.fout.axes, titletxt{:}, kws.title{:});
918 else
919 %%%% Neither input nor output arguments are not supported when using title with heatmap.
920 title(titletxt);
921 end
922 end
923 end
924
925 %%%% set limits.
926
927 for prop = ["xlim", "ylim", "zlim"]
928 if isprop(self, prop) && ~isempty(self.(prop))
929 limit = get(self.fout.axes, prop);
930 for i = 1 : 2
931 if ~isnan(self.(prop)(i))
932 limit(i) = self.(prop)(i);
933 end
934 end
935 set(self.fout.axes, prop, limit);
936 end
937 end
938
939 %%%% set axes scales.
940
941 for prop = ["xscale", "yscale", "zscale"]
942 if isprop(self, prop) && ~isempty(self.(prop))
943 set(self.fout.axes, prop, self.(prop));
944 end
945 end
946
947 if ~self.type.is.heatmap
948 hold off;
949 %grid on;
950 %box on;
951 end
952
953 end % function
954
955 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
956
957 end
958
959 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
960
961 methods(Access = public, Hidden)
962
963 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
964
965 %> \brief
966 %> Prepare the subplot for visualization.<br>
967 %>
968 %> \param[inout] self : The input/output parent object of class [pm.vis.Subplot](@ref Subplot)
969 %> which is **implicitly** passed to this dynamic method (not by the user).<br>
970 %> \param[in] varargin : Any ``property, value`` pair of the parent object.<br>
971 %> If the property is a ``struct()``, then its value must be given as a cell array,
972 %> with consecutive elements representing the struct ``property-name, property-value`` pairs.<br>
973 %> Note that all of these property-value pairs can be also directly set via the
974 %> parent object attributes, before calling the ``premake()`` method.<br>
975 %>
976 %> \interface{premake}
977 %> \code{.m}
978 %>
979 %> s = pm.vis.Subplot(ptype, dfref);
980 %>
981 %> s.premake(varargin);
982 %> s.premake();
983 %>
984 %> \endcode
985 %>
986 %> \warning
987 %> This method has side-effects by manipulating
988 %> the existing attributes of the parent object.<br>
989 %>
990 %> \example{premake}
991 %> \code{.m}
992 %>
993 %> dfref = rand(1000, 3);
994 %> s = pm.vis.Subplot("scatter", dfref);
995 %> s.premake("colx", 1, "coly", 2, "colc", 3)
996 %>
997 %> \endcode
998 %>
999 %> \final{premake}
1000 %>
1001 %> \author
1002 %> \JoshuaOsborne, May 22 2024, 6:41 PM, University of Texas at Arlington<br>
1003 %> \FatemehBagheri, May 20 2024, 1:25 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
1004 %> \AmirShahmoradi, July 5 2024, 1:07 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
1005 function premake(self, varargin)
1006 premake@pm.vis.axes.Axes(self, varargin{:});
1007 end
1008
1009 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1010
1011 %> \brief
1012 %> Reset the properties of the plot to the original default settings.<br>
1013 %>
1014 %> \brief
1015 %> Use this method when you change many attributes of the plot and
1016 %> you want to clean up and go back to the default settings.<br>
1017 %>
1018 %> \param[inout] self : The input/output parent object of class [pm.vis.Subplot](@ref Subplot)
1019 %> which is **implicitly** passed to this dynamic method (not by the user).<br>
1020 %> \param[in] varargin : Any ``property, value`` pair of the parent object.<br>
1021 %> If the property is a ``struct()``, then its value must be given as a cell array,
1022 %> with consecutive elements representing the struct ``property-name, property-value`` pairs.<br>
1023 %> Note that all of these property-value pairs can be also directly set via the
1024 %> parent object attributes, before calling the ``make()`` method.<br>
1025 %>
1026 %> \interface{reset}
1027 %> \code{.m}
1028 %>
1029 %> pm.vis.Subplot.reset() % reset the plot to the default settings.
1030 %>
1031 %> \endcode
1032 %>
1033 %> \final{reset}
1034 %>
1035 %> \author
1036 %> \JoshuaOsborne, May 22 2024, 6:43 PM, University of Texas at Arlington<br>
1037 %> \FatemehBagheri, May 20 2024, 1:25 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
1038 %> \AmirShahmoradi, July 5 2024, 1:07 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.<br>
1039 function reset(self, varargin)
1040 self.rows = [];
1041 self.fout = struct();
1042 self.newprop("colx", {});
1043 if self.type.is.d2 || self.type.is.d3
1044 self.newprop("coly", {});
1045 if self.type.is.d3
1046 self.newprop("colz", {});
1047 end
1048 end
1049 reset@pm.vis.axes.Axes(self, varargin{:});
1050 end
1051
1052 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1053
1054 end
1055
1056end
name
function name(in vendor)
Return the MPI library name as used in naming the ParaMonte MATLAB shared libraries.
list
function list()
Return a list of MATLAB strings containing the names of OS platforms supported by the ParaMonte MATLA...
version
function version(in silent)
Return a scalar MATLAB string containing the latest available ParaMonte MATLAB version newer than the...
Axes
This is the class for generating instances of objects that contain the specifications of various type...
Definition: Axes.m:622
Axes::Axes
function Axes(in ptype, in varargin)
Construct and return an object of class pm.vis.axes.Axes.
Cascade
This is the abstract class for generating instances of objects that contain the specifications of a c...
Definition: Cascade.m:32
Corner
This is the base class for generating instances of figures containing a symmetric square grid or corn...
Definition: Corner.m:19
DataFrame
This is the abstract class for generating instances of objects that can contain basic attributes requ...
Definition: DataFrame.m:25
DataFrame::rowslog
function rowslog(in self, in count, in start, in stop)
Generate and return a natural logarithmically-spaced range of indices from the row indices of the inp...
Figure
This is the abstract class for generating instances of objects that contain the specifications of var...
Definition: Figure.m:27
Handle
This is the base class for generating subclass of MATLAB handle superclass whose annoying methods are...
Definition: Handle.m:24
Plot
This is the base class for generating instances of objects that contain the specifications of various...
Definition: Plot.m:29
SubplotContour3
This is the SubplotContour3 class for generating instances of 3-dimensional Contour Subplot visualiza...
Definition: SubplotContour3.m:30
SubplotContour
This is the SubplotContour class for generating instances of 2-dimensional Contour Subplot visualizat...
Definition: SubplotContour.m:30
SubplotContourf
This is the SubplotContourf class for generating instances of 2-dimensional Contour Subplot visualiza...
Definition: SubplotContourf.m:30
SubplotEllipse3
This is the SubplotEllipse3 class for generating instances of 3-dimensional Ellipse Subplot visualiza...
Definition: SubplotEllipse3.m:28
SubplotEllipse
This is the SubplotEllipse class for generating instances of 2-dimensional Ellipse Subplot visualizat...
Definition: SubplotEllipse.m:29
SubplotHeatmap
This is the SubplotHeatmap class for generating instances of 2-dimensional Heatmap Subplot visualizat...
Definition: SubplotHeatmap.m:26
SubplotHistfit
This is the SubplotHistfit class for generating instances of 2-dimensional Histfit Subplot visualizat...
Definition: SubplotHistfit.m:26
SubplotHistogram2
This is the SubplotHistogram2 class for generating instances of 2-dimensional Histogram2 Subplot visu...
Definition: SubplotHistogram2.m:26
SubplotHistogram
This is the SubplotHistogram class for generating instances of 1-dimensional Histogram Subplot visual...
Definition: SubplotHistogram.m:26
SubplotLine3
This is the SubplotLine3 class for generating instances of 3-dimensional Line Subplot visualizations ...
Definition: SubplotLine3.m:26
SubplotLineScatter3
This is the SubplotLineScatter3 class for generating instances of 3-dimensional Line-Scatter Subplot ...
Definition: SubplotLineScatter3.m:26
SubplotLineScatter
This is the SubplotLineScatter class for generating instances of 2-dimensional Line-Scatter Subplot v...
Definition: SubplotLineScatter.m:26
SubplotLine
This is the SubplotLine class for generating instances of 2-dimensional Line Subplot visualizations b...
Definition: SubplotLine.m:26
SubplotScatter3
This is the SubplotScatter3 class for generating instances of 3-dimensional Scatter Subplot visualiza...
Definition: SubplotScatter3.m:26
SubplotScatter
This is the SubplotScatter class for generating instances of 3-dimensional Scatter Subplot visualizat...
Definition: SubplotScatter.m:26
Subplot
This is the abstract class for generating instances of axes with various types of plots from one or m...
Definition: Subplot.m:188
Subplot::df
Property df
Definition: Subplot.m:201
Subplot::premake
function premake(in self, in varargin)
Prepare the subplot for visualization.
Subplot::Subplot
function Subplot(in ptype, in dfref, in varargin)
Construct and return an object of class pm.vis.Subplot.
Subplot::reset
function reset(in self, in varargin)
Reset the properties of the plot to the original default settings.
Subplot::rows
Property rows
Definition: Subplot.m:240
Subplot::make
function make(in self, in varargin)
Generate a plot from the selected columns of the parent object component df.
Subplot::fout
Property fout
Definition: Subplot.m:209
Tile
This is the abstract class for generating instances of objects that contain the specifications of var...
Definition: Tile.m:9
clean
function clean()
Remove all paths that contain the ParaMonte lib directory from the MATLAB path variable.
kde2d
function kde2d(in data, in resol, in xymin, in xymax)
Compute the Gaussian kernel density estimate of the input bivariate data.
which
function which(in vendor)
Return the a MATLAB string containing the path to the first mpiexec executable binary found in system...