Coverage for src/colorspace/demos.py: 100%
270 statements
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2def demoplot(colors, type_, n = 7, ax = None, **kwargs):
3 """Create Demo Plots
5 This function is intended to be used by the GUI
6 (:py:func:`choose_palette <colorspace.choose_palette.choose_palette>`)
7 to visualize the color palette selected for a series of different
8 types of plots. It can, however, also be used directly if needed.
11 Arguments:
12 colors: The colors, any type which can be handled by
13 :py:func:`palette <colorspace.palettes.palette>`.
14 type_ (str): Name of the demo function to be called.
15 Not case sensitive.
16 n (int): Number of colors for the plot. Only used if argument `colors`
17 is a palette where a dedicated number of colors must be drawn first.
18 Defaults to 7.
19 title (None, str): used to draw the figure title, if specified (str).
20 Forwarded to different plot types.
21 ax (None, matplotlib.axes.Axes): If `None` a new matplotlib figure will
22 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
23 will be used to create the demoplot. Handy to create multiple subplots.
24 Forwarded to different plot types.
25 **kwargs: Forwarded to the corresponding demo plot functions.
27 Examples:
29 >>> # Importing modules
30 >>> from colorspace import *
31 >>> from colorspace.colorlib import *
32 >>>
33 >>> # Custom list of hex colors (n = 5)
34 >>> hexlist = ["#BCBE57", "#DEDFC0", "#F1F1F1", "#F7D3E7", "#FB99D7"]
35 >>> hexlist
36 >>> #: A (HCL based) colorobject with (n = 3)
37 >>> colorobj = HCL([0, 90, 180], [60, 60, 60], [60, 60, 60])
38 >>> colorobj
39 >>> #: Default diverging HCL palette
40 >>> hclpalette = diverging_hcl()
41 >>> hclpalette
42 >>> #: Default color palette shipped with the package
43 >>> berlin = hcl_palettes(name = "Berlin").get_palettes()[0]
44 >>> berlin
45 >>> #: Demoplots
46 >>> demoplot(hexlist, "Bar");
47 >>> #:
48 >>> demoplot(colorobj, "Lines");
49 >>> #:
50 >>> demoplot(hclpalette, "Pie", n = 4);
51 >>> #:
52 >>> demoplot(berlin.colors(), "Matrix", n = 11);
53 >>>
54 >>> #: Using custom subplots and plot titles
55 >>> from matplotlib import pyplot as plt
56 >>> from colorspace import protan, deutan, desaturate
57 >>> fig, axes = plt.subplots(2, 2)
58 >>> colors = diverging_hcl("Green-Orange").colors(7)
59 >>> demoplot(colors, "Bar",
60 >>> title = "Original", ax = axes[0, 0]);
61 >>> demoplot(protan(colors), "Bar",
62 >>> title = "Protanope vision", ax = axes[0, 1]);
63 >>> demoplot(deutan(colors), "Bar",
64 >>> title = "Deuteranope vision", ax = axes[1, 0]);
65 >>> demoplot(desaturate(colors), "Bar",
66 >>> title = "Desaturated", ax = axes[1, 1]);
67 >>> plt.show()
70 Raises:
71 TypeError: If `type_` is not a str.
72 ValueError: If `type_` is not an available demo plot type.
73 TypeError: If `n` is not int.
74 ValueError: `n` must be a positive int.
75 """
77 from .palettes import palette
78 from . import demos
79 from re import match, compile, IGNORECASE
81 # Sanity checks
82 if not isinstance(type_, str):
83 raise TypeError("argument `type_` must be str")
84 if not isinstance(n, int):
85 raise TypeError("argument `n` must be int")
86 if not n > 0:
87 raise ValueError("argument `n` must be a positive int (number of colors)")
89 # The palette class does all the checks and conversions for different
90 # types of objects such as a single string hex color, lists of hex colors,
91 # colorobjects, palette objects, and hclpalettes.
92 colors = palette(colors, n = n).colors()
94 # Replace missing values with white
95 colors = ["#FFFFFF" if x is None else x for x in colors]
97 # Loading available demo plot types (functions)
98 available_types = []
99 for rec in dir(demos):
100 if not rec == "demoplot" and match("^[A-Za-z]*$", rec):
101 available_types.append(rec)
103 # Is the user asking for an available demo plot?
104 fun = None
105 check = compile(f"^{type_}$", IGNORECASE)
106 for avtype in available_types:
107 if not check.match(avtype): continue
108 fun = avtype
110 # Not found?
111 if fun is None:
112 raise ValueError(f"no demoplot available for {type_}. Available: {', '.join(available_types)}")
114 # Calling the required plotting function
115 fun = getattr(demos, fun)
116 if ax is None:
117 return fun(colors, **kwargs)
118 else:
119 return fun(colors, ax = ax, **kwargs)
122def _demoplot_set_labels(ax, **kwargs):
123 """Setting axis and labels for demoplots.
125 Args:
126 **kwargs: named arguments to set different labels of the demoplots.
127 Considered are `title`, `xlable`, and `ylabel` only.
129 Returns:
130 No return.
131 """
133 from matplotlib import pyplot as plt
135 # Hide axis ticks and frame (box)
136 ax.axes.xaxis.set_ticks([])
137 ax.axes.yaxis.set_ticks([])
138 ax.set_frame_on(False)
140 # In case the user specified title, xlabel, or ylabel as a string
141 # we will call ax.set_title, ax.set_xlabel, and ax.set_ylabel respectively.
142 # For the title boldface font will be used.
143 for x in ["title", "xlabel", "ylabel"]:
144 if x in kwargs.keys():
145 if isinstance(kwargs[x], str):
146 fn = getattr(ax, "set_{:s}".format(x))
147 fn(kwargs[x], fontweight = "bold" if x == "title" else "regular")
150def Bar(colors, ax = None, **kwargs):
151 """Bar Plot Demo
153 Args:
154 colors (list of str): List of hex colors.
155 ax (None or matplotlib.axes.Axes): If none a new matplotlib figure will
156 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
157 will be used to create the demoplot. Handy to create multiple subplots.
158 **kwargs: Optional; Strings can be set for `title = "My title"`,
159 `xlabel = "My x label"` and `ylabel = "My y label"`.
161 Returns:
162 Returns a new figure object if `ax` equals `None`, else the
163 same object as provided on `ax` is returned.
165 Raises:
166 ValueError: If `ax` is neither none nor an object which inherits from
167 `matplotlib.axes.Axes`.
168 """
170 import matplotlib.pyplot as plt
171 import numpy as np
172 from matplotlib.axes import Axes
174 if not isinstance(ax, (Axes, type(None))):
175 raise TypeError("argument `ax` must be None or inherit from matplotlib.axes.Axes")
177 # Replace missing values with white
178 colors = ["#FFFFFF" if x is None else x for x in colors]
180 # Open new figure in case the user has not specified the `ax`
181 # input argument (matplotlib.axes.Axes) but use `ax = None` (default).
182 # In this case this function will also auto-show the image at the end
183 # of the function.
184 if ax is None:
185 fig = plt.figure()
186 ax = plt.gca()
187 showfig = True
188 else:
189 showfig = False
191 # Get random data
192 np.random.seed(1)
193 width = 0.9 / len(colors)
195 lower = [1.1, 1.9, 0.7, 0.3]
196 offset = [0.5, 1.1, 1.5, 0.8]
198 # Creating the plot
199 for i in range(0, len(lower)):
200 x = i + np.arange(0, len(colors)) * width
201 y = lower[i] + np.abs(np.sin(offset[i] + 1 + \
202 np.arange(0, len(colors), dtype = float))) / 3
203 ax.bar(x, y, color = colors, width = width)
206 # Set and draw axis and labels for the demoplots
207 _demoplot_set_labels(ax, **kwargs)
209 if not showfig:
210 return ax
211 else:
212 plt.show()
213 return fig
216def Pie(colors, ax = None, **kwargs):
217 """Pie Chart Demo
219 Args:
220 colors (list of str): List of hex colors.
221 ax (None or matplotlib.axes.Axes): If none a new matplotlib figure will
222 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
223 will be used to create the demoplot. Handy to create multiple subplots.
224 **kwargs: Optional; Strings can be set for `title = "My title"`,
225 `xlabel = "My x label"` and `ylabel = "My y label"`.
227 Returns:
228 Returns a new figure object if `ax` equals `None`, else the
229 same object as provided on `ax` is returned.
231 Raises:
232 ValueError: If `ax` is neither none nor an object which inherits from
233 `matplotlib.axes.Axes`.
234 """
236 import matplotlib.pyplot as plt
237 import numpy as np
238 from matplotlib.axes import Axes
240 if not isinstance(ax, (Axes, type(None))):
241 raise TypeError("argument `ax` must be None or inherit from matplotlib.axes.Axes")
243 # Replace missing values with white
244 colors = ["#FFFFFF" if x is None else x for x in colors]
246 # Open new figure in case the user has not specified the `ax`
247 # input argument (matplotlib.axes.Axes) but use `ax = None` (default).
248 # In this case this function will also auto-show the image at the end
249 # of the function.
250 if ax is None:
251 fig = plt.figure()
252 ax = plt.gca()
253 showfig = True
254 else:
255 showfig = False
257 # Generate pie plot
258 x = 0.01 + np.abs(np.sin(1.5 + np.arange(0, len(colors))))
259 ax.pie(x, colors = colors,
260 wedgeprops = {"edgecolor": "0", "linewidth": 1, "antialiased": True})
262 # Set and draw axis and labels for the demoplots
263 _demoplot_set_labels(ax, **kwargs)
265 if not showfig:
266 return ax
267 else:
268 plt.show()
269 return fig
272def Spine(colors, ax = None, **kwargs):
273 """Spine Plot Demo
275 Args:
276 colors (list of str): List of hex colors.
277 ax (None or matplotlib.axes.Axes): If none a new matplotlib figure will
278 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
279 will be used to create the demoplot. Handy to create multiple subplots.
280 **kwargs: Optional; Strings can be set for `title = "My title"`,
281 `xlabel = "My x label"` and `ylabel = "My y label"`.
283 Returns:
284 Returns a new figure object if `ax` equals `None`, else the
285 same object as provided on `ax` is returned.
287 Raises:
288 ValueError: If `ax` is neither none nor an object which inherits from
289 `matplotlib.axes.Axes`.
290 """
292 import matplotlib.pyplot as plt
293 from matplotlib.patches import Rectangle
294 import numpy as np
295 from matplotlib.axes import Axes
297 if not isinstance(ax, (Axes, type(None))):
298 raise TypeError("argument `ax` must be None or inherit from matplotlib.axes.Axes")
300 # Replace missing values with white
301 colors = ["#FFFFFF" if x is None else x for x in colors]
303 # Open new figure in case the user has not specified the `ax`
304 # input argument (matplotlib.axes.Axes) but use `ax = None` (default).
305 # In this case this function will also auto-show the image at the end
306 # of the function.
307 if ax is None:
308 fig = plt.figure()
309 ax = plt.gca()
310 showfig = True
311 else:
312 showfig = False
314 # Data
315 offset = 0.015
316 widths = [0.05, 0.1, 0.15, 0.1, 0.2, 0.08, 0.12, 0.16, 0.04]
317 k = len(widths)
318 n = len(colors)
319 heights = [np.power(np.arange(1, n + 1, dtype = float) / n, 1. / p) for p in \
320 [2.5, 1.2, 2.7, 1, 1.3, 0.7, 0.4, 0.2, 1.7]]
322 # Plot
323 x = 0.
324 for i in range(0,k):
325 y = 0.
326 heights[i] = heights[i] / sum(heights[i]) # Scale
327 for j in range(0,n):
328 rect = Rectangle((x,y), widths[i], heights[i][j], color = colors[j])
329 ax.add_patch(rect)
330 y += heights[i][j]
331 x += offset + widths[i]
333 # Set and draw axis and labels for the demoplots
334 _demoplot_set_labels(ax, **kwargs)
336 if not showfig:
337 return ax
338 else:
339 plt.show()
340 return fig
343def Heatmap(colors, ax = None, **kwargs):
344 """Heat Map Demo
346 Dataset source: Digitized from a topographic map by Ross Ihaka. These data
347 should not be regarded as accurate.
349 Dataset description: Maunga Whau (Mt Eden) is one of about 50
350 volcanos in the Auckland volcanic field. This data set gives topographic
351 information for Maunga Whau on a 10m by 10m grid. A matrix with 87 rows
352 and 61 columns, rows corresponding to grid lines running east to west and
353 columns to grid lines running south to north.
355 Args:
356 colors (list of str): List of hex colors.
357 ax (None or matplotlib.axes.Axes): If none a new matplotlib figure will
358 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
359 will be used to create the demoplot. Handy to create multiple subplots.
360 **kwargs: Optional; Strings can be set for `title = "My title"`,
361 `xlabel = "My x label"` and `ylabel = "My y label"`.
363 Returns:
364 Returns a new figure object if `ax` equals `None`, else the
365 same object as provided on `ax` is returned.
367 Raises:
368 ValueError: If `ax` is neither none nor an object which inherits from
369 `matplotlib.axes.Axes`.
370 """
372 import matplotlib.pyplot as plt
373 import numpy as np
374 from matplotlib.axes import Axes
376 from matplotlib.colors import LinearSegmentedColormap
377 from .colorlib import hexcols
379 if not isinstance(ax, (Axes, type(None))):
380 raise TypeError("argument `ax` must be None or inherit from matplotlib.axes.Axes")
382 # Replace missing values with white
383 colors = ["#FFFFFF" if x is None else x for x in colors]
385 # Open new figure in case the user has not specified the `ax`
386 # input argument (matplotlib.axes.Axes) but use `ax = None` (default).
387 # In this case this function will also auto-show the image at the end
388 # of the function.
389 if ax is None:
390 fig = plt.figure()
391 ax = plt.gca()
392 showfig = True
393 else:
394 showfig = False
396 # Get coordinates
397 cobj = hexcols(colors)
398 cobj.to("sRGB")
399 r = cobj.get("R"); g = cobj.get("G"); b = cobj.get("B")
401 # Create cmap
402 pos = np.linspace(0, 1, len(colors), dtype = float)
403 cdict = {'red':[], 'green':[], 'blue':[]}
404 for i in range(0, len(colors)):
405 cdict['red'].append( (pos[i], r[i], r[i]) )
406 cdict['green'].append( (pos[i], g[i], g[i]) )
407 cdict['blue'].append( (pos[i], b[i], b[i]) )
408 cmap = LinearSegmentedColormap("custom", cdict, len(colors))
410 # Loading vulcano
411 data = get_volcano_data()
413 # Plotting data
414 ax.imshow(data, cmap = cmap, aspect = "auto")
416 #ax.axis("off")
417 ax.axes.xaxis.set_ticks([])
418 ax.axes.yaxis.set_ticks([])
419 ax.set_frame_on(False)
421 # Set and draw axis and labels for the demoplots
422 _demoplot_set_labels(ax, **kwargs)
424 if not showfig:
425 return ax
426 else:
427 plt.show()
428 return fig
432def Matrix(colors, ax = None, **kwargs):
433 """Matrix (Image) Demo Plot
435 Args:
436 colors (list of str): List of hex colors.
437 ax (None or matplotlib.axes.Axes): If none a new matplotlib figure will
438 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
439 will be used to create the demoplot. Handy to create multiple subplots.
440 **kwargs: Optional; Strings can be set for `title = "My title"`,
441 `xlabel = "My x label"` and `ylabel = "My y label"`.
443 Returns:
444 Returns a new figure object if `ax` equals `None`, else the
445 same object as provided on `ax` is returned.
447 Raises:
448 ValueError: If `ax` is neither none nor an object which inherits from
449 `matplotlib.axes.Axes`.
450 """
452 import matplotlib.pyplot as plt
453 import numpy as np
454 from matplotlib.axes import Axes
456 from matplotlib.colors import LinearSegmentedColormap
457 from .colorlib import hexcols
459 if not isinstance(ax, (Axes, type(None))):
460 raise TypeError("argument `ax` must be None or inherit from matplotlib.axes.Axes")
462 # Replace missing values with white
463 colors = ["#FFFFFF" if x is None else x for x in colors]
465 # Open new figure in case the user has not specified the `ax`
466 # input argument (matplotlib.axes.Axes) but use `ax = None` (default).
467 # In this case this function will also auto-show the image at the end
468 # of the function.
469 if ax is None:
470 fig = plt.figure()
471 ax = plt.gca()
472 showfig = True
473 else:
474 showfig = False
476 # Get coordinates
477 cobj = hexcols(colors)
478 cobj.to("sRGB")
479 r = cobj.get("R"); g = cobj.get("G"); b = cobj.get("B")
481 # Create cmap
482 pos = np.linspace(0, 1, len(colors), dtype = float)
483 cdict = {'red':[], 'green':[], 'blue':[]}
484 for i in range(0, len(colors)):
485 cdict['red'].append( (pos[i], r[i], r[i]) )
486 cdict['green'].append( (pos[i], g[i], g[i]) )
487 cdict['blue'].append( (pos[i], b[i], b[i]) )
488 cmap = LinearSegmentedColormap("custom", cdict, len(colors))
490 # Get random data
491 np.random.seed(1)
492 data = np.random.uniform(0., float(len(colors)), 100).reshape((10,10))
494 # Plotting data
495 ax.imshow(data, cmap = cmap)
497 # Set and draw axis and labels for the demoplots
498 _demoplot_set_labels(ax, **kwargs)
500 if not showfig:
501 return ax
502 else:
503 plt.show()
504 return fig
506#def Scatter(colors, fig = None):
507#
508# import matplotlib.pyplot as plt
509# import numpy as np
510#
511# # Open figure if input "fig" is None, else use
512# # input "fig" handler.
513# if fig is None:
514# fig = plt.figure()
515# showfig = True
516# else:
517# showfig = False
518#
519# # Data
520# x0 = np.sin(np.pi * np.arange(1,61) / 30) / 5
521# y0 = np.cos(np.pi * np.arange(1,61) / 30) / 5
522# xr = [0.1, -0.6, -0.7, -0.9, 0.4, 1.3, 1.0]
523# yr = [0.3, 1.0, 0.1, -0.9, -0.8, -0.4, 0.6]
524#
525# # Requires scipy
526#
527# x = 0.01 + np.abs(np.sin(1.5 + np.arange(0, len(colors))))
528# plt.pie(x, colors = colors)
529# plt.axis("off")
530#
531# if not showfig: return fig
532# else: plt.show()
534def Lines(colors, ax = None, **kwargs):
535 """Line Plot Demo
537 Args:
538 colors (list of str): List of hex colors.
539 ax (None or matplotlib.axes.Axes): If none a new matplotlib figure will
540 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
541 will be used to create the demoplot. Handy to create multiple subplots.
542 **kwargs: Optional; Strings can be set for `title = "My title"`,
543 `xlabel = "My x label"` and `ylabel = "My y label"`.
545 Returns:
546 Returns a new figure object if `ax` equals `None`, else the
547 same object as provided on `ax` is returned.
549 Raises:
550 ValueError: If `ax` is neither none nor an object which inherits from
551 `matplotlib.axes.Axes`.
552 """
554 import matplotlib.pyplot as plt
555 import numpy as np
556 from matplotlib.axes import Axes
558 if not isinstance(ax, (Axes, type(None))):
559 raise TypeError("argument `ax` must be None or inherit from matplotlib.axes.Axes")
561 # Replace missing values with white
562 colors = ["#FFFFFF" if x is None else x for x in colors]
564 # Open new figure in case the user has not specified the `ax`
565 # input argument (matplotlib.axes.Axes) but use `ax = None` (default).
566 # In this case this function will also auto-show the image at the end
567 # of the function.
568 if ax is None:
569 fig = plt.figure()
570 ax = plt.gca()
571 showfig = True
572 else:
573 showfig = False
575 # Data
576 n = len(colors)
577 s = range(2, n + 2)
579 lwd = 6
580 if n > 5: lwd -= 1
581 if n > 15: lwd -= 1
582 if n > 25: lwd -= 1
584 for i in range(0, len(colors)):
585 j = n - 1 - i
586 # Plotting two lines to get the overlays correctly
587 ax.plot([1 / s[i], 2. + 1. / s[j]],
588 [s[i], s[j]],
589 color = colors[i], linewidth = lwd,
590 solid_capstyle = "round")
591 ax.plot([2. + 1. / s[i], 4. - 1. / s[i], 6. - 1 / s[i]],
592 [s[i], s[i], s[j]],
593 color = colors[j], linewidth = lwd,
594 solid_capstyle = "round")
596 # Set and draw axis and labels for the demoplots
597 _demoplot_set_labels(ax, **kwargs)
599 if not showfig:
600 return ax
601 else:
602 plt.show()
603 return fig
606def Map(colors, ax = None, **kwargs):
607 """Map Demo Plot
609 Args:
610 colors (list of str): List of hex colors.
611 ax (None or matplotlib.axes.Axes): If none a new matplotlib figure will
612 be created. If `ax` inherits from `matplotlib.axes.Axes` this object
613 will be used to create the demoplot. Handy to create multiple subplots.
614 **kwargs: Optional; Strings can be set for `title = "My title"`,
615 `xlabel = "My x label"` and `ylabel = "My y label"`. In addition
616 `edgecolor = <color>` can be used to specify custom edge color of the
617 polygons.
619 Returns:
620 Returns a new figure object if `ax` equals `None`, else the
621 same object as provided on `ax` is returned.
623 Raises:
624 ValueError: If `ax` is neither none nor an object which inherits from
625 `matplotlib.axes.Axes`.
626 """
628 import matplotlib.pyplot as plt
629 import numpy as np
630 from matplotlib.axes import Axes
632 if not isinstance(ax, (Axes, type(None))):
633 raise TypeError("argument `ax` must be None or inherit from matplotlib.axes.Axes")
635 # Replace missing values with white
636 colors = ["#FFFFFF" if x is None else x for x in colors]
638 # Open new figure in case the user has not specified the `ax`
639 # input argument (matplotlib.axes.Axes) but use `ax = None` (default).
640 # In this case this function will also auto-show the image at the end
641 # of the function.
642 if ax is None:
643 fig = plt.figure()
644 ax = plt.gca()
645 showfig = True
646 else:
647 showfig = False
650 # Returns a PatchCollection with the polygons for the map and
651 # a numpy array with the values used for the color coding.
652 collection,vals = get_map_data()
654 # Convert the numeric values into int [0, n-1] to pick
655 # the correct colors for each polygon given the user input
656 # object `colors`.
657 n = len(colors)
658 vals = np.floor((vals - np.min(vals)) / (np.max(vals) - np.min(vals)) * (n - 1))
659 vals = np.fmin(vals, n - 1)
660 cols = [colors[int(x)] for x in vals]
662 # Setting facecolor of the polygons
663 collection.set_facecolor(cols)
664 edgecolor = "black" if not "edgecolor" in kwargs.keys() else kwargs["edgecolor"]
665 collection.set_edgecolor(edgecolor)
667 # Draw map
668 ax.add_collection(collection)
669 ax.autoscale_view()
670 ax.set_aspect("equal")
672 # Set and draw axis and labels for the demoplots
673 _demoplot_set_labels(ax, **kwargs)
675 if not showfig:
676 return ax
677 else:
678 plt.show()
679 return fig
682def Spectrum(*args, **kwargs):
683 """Color Spectrum Demo Plot
685 Plotting example. Simply interfaces the specplot function.
687 Args:
688 colors (list of str): List of hex colors.
689 """
691 from colorspace import specplot
692 return specplot(rgb = True, *args, **kwargs)
695def get_volcano_data(array = False):
696 """Topographic Information on Auckland's Maunga Whau Volcano
698 Maunga Whau (Mt Eden) is one of about 50 volcanos in the Auckland
699 volcanic field. This data set gives topographic information for
700 Maunga Whau on a 10m by 10m grid.
702 Args:
703 array (bool): should the return be a list (default) or 2d
704 numpy array?
706 Returns:
707 Returns a list of length 67 where each entry is a list of int
708 of lenth 87 if `asarray = False` (default). If `asarray = True`
709 an int numpy array of shape `(67, 87)` will be returned.
711 Raises:
712 ValueError: If input `asarray` is not bool.
713 """
715 import os
716 from numpy import asarray
718 if not isinstance(array, bool):
719 raise ValueError("argument `asarray` must be bool")
721 # Loading the data set
722 resource_package = os.path.dirname(__file__)
723 volcano = os.path.join(resource_package, "data", "volcano.dat")
725 # Reading the data set; create recursive list
726 data = []
727 with open(volcano, "r") as fid:
728 for line in fid.readlines():
729 data.append([int(x) for x in line.split()])
731 # Return data
732 if array:
733 return asarray(data)
734 else:
735 data.reverse()
736 return(data)
738def get_map_data():
739 """Load Map Data
741 Reading a file called `map.json` shipped with the package which
742 contains the definition of the different areas (polygons) and
743 values to draw the map.
745 Contains polygons representing the southern US states
746 Alabama, Georgia, and South Carolona with simulated data.
748 Returns:
749 list: List of length `2`. The first entry is a `PatchCollection` object
750 (`matplotlib.collections`) which sonsists of a series of `Polygon`s
751 for the different districts. The second entry is a `numpy.ndarray`
752 (float) containing the values used to color-code the areas.
753 """
754 import os
755 import json
757 from matplotlib import pyplot as plt
758 from matplotlib.collections import PatchCollection
759 from matplotlib.patches import Polygon
760 from colorspace.demos import get_map_data
761 from numpy import column_stack, asarray
764 # Loading the data set
765 resource_package = os.path.dirname(__file__)
766 mapdata = os.path.join(resource_package, "data", "map.json")
768 with open(mapdata, "r") as fid: mapdata = json.loads(fid.readline())
770 patches = []
771 values = []
773 # Prepare the data for return
774 for key,vals in mapdata.items():
775 polygon = Polygon(column_stack((vals["x"], vals["y"])))
776 patches.append(polygon)
777 values.append(vals["value"][0])
779 return [PatchCollection(patches), asarray(values)]