annoviko /
pyclustering
| @@ 642-646 (lines=5) @@ | ||
| 639 | if (data is None): |
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| 640 | axes.plot(item[0], item[1], 'w' + marker_descr); |
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| 641 | else: |
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| 642 | axes.plot(data[item][0], data[item][1], 'w' + marker_descr); |
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| 643 | ||
| 644 | elif (dimension == 3): |
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| 645 | if (data is None): |
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| 646 | axes.scatter(item[0], item[1], item[2], c = 'w', marker = marker_descr); |
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| 647 | else: |
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| 648 | axes.scatter(data[item][0], data[item][1], data[item][2], c = 'w', marker = marker_descr); |
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| 649 | ||
| @@ 621-625 (lines=5) @@ | ||
| 618 | if (data is None): |
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| 619 | axes.plot(item[0], item[1], color = color, marker = marker_descr); |
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| 620 | else: |
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| 621 | axes.plot(data[item][0], data[item][1], color = color, marker = marker_descr); |
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| 622 | ||
| 623 | elif (dimension == 3): |
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| 624 | if (data is None): |
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| 625 | axes.scatter(item[0], item[1], item[2], c = color, marker = marker_descr); |
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| 626 | else: |
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| 627 | axes.scatter(data[item][0], data[item][1], data[item][2], c = color, marker = marker_descr); |
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| 628 | ||
| @@ 252-256 (lines=5) @@ | ||
| 249 | canvas_shift = 0; |
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| 250 | cluster_figure = None; |
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| 251 | if (figure is not None): |
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| 252 | canvas_shift = len(figure.get_axes()); |
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| 253 | cluster_figure = figure; |
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| 254 | else: |
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| 255 | cluster_figure = plt.figure(); |
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| 256 | ||
| 257 | maximum_cols = self.__size_row; |
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| 258 | maximum_rows = math.ceil( (self.__number_canvases + canvas_shift) / maximum_cols); |
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| 259 | ||
| @@ 255-258 (lines=4) @@ | ||
| 252 | canvas_shift = len(figure.get_axes()); |
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| 253 | cluster_figure = figure; |
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| 254 | else: |
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| 255 | cluster_figure = plt.figure(); |
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| 256 | ||
| 257 | maximum_cols = self.__size_row; |
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| 258 | maximum_rows = math.ceil( (self.__number_canvases + canvas_shift) / maximum_cols); |
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| 259 | ||
| 260 | grid_spec = gridspec.GridSpec(maximum_rows, maximum_cols); |
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| 261 | ||
