Make HeatMap more general #849
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philippjfr
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tag: component: data
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@jlstevens The PR is now ready for review, I'll rebuild the test data shortly. The test data will have to be updated because |
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Still need to add thorough unit tests for the aggregation. I'm also now wondering whether I should add a warning when you pass non-aggregated data to a HeatMap, e.g. there are two different values for index ('A', 'a') in the heatmap, it would just silently ignore the second value. Really it should warn you that you should aggregate your data using some function (mean, max, min) before passing it to the HeatMap. |
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Also deprecates support for unpickling the original |
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| def get_2d_aggregate(obj): | ||
| """ |
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Perhaps this would be better expressed as an operation? Then maybe it could have a minimal docstring example in the class docstring?
| for k1, k2 in product(keys1, keys2)}) | ||
| return dense_map.dframe() | ||
| return super(HeatMap, self).dframe() | ||
| self.gridded = get_2d_aggregate(self) |
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Nice to see how much HeatMap has been simplified!
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That said, it isn't immediately obvious that gridded is now a Dataset. Not sure I am necessarily recommending changing the name as gridded_dataset is awkward...
| @@ -383,85 +381,18 @@ class HeatMap(Dataset, Element2D): | |||
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| vdims = param.List(default=[Dimension('z')]) | |||
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| def __init__(self, data, extents=None, **params): | |||
| depth = 1 | |||
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I might have forgotten...what is this depth class attribute?
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I think this may be wrong now, will have to look into it.
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Wasn't needed at all in the end, removed it.
| @@ -130,26 +136,31 @@ class HeatmapPlot(ColorbarPlot): | |||
| def _axes_props(self, plots, subplots, element, ranges): | |||
| dims = element.dimensions() | |||
| labels = self._get_axis_labels(dims) | |||
| xvals, yvals = [element.dimension_values(i, False) | |||
| agg = element.gridded | |||
| xvals, yvals = [unique_array(agg.dimension_values(i, False)) | |||
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I thought gridded Datasets have the 1D coordinate arrays available. Is the uniqueness being applied over the 2D set of samples or the 1D sequence?
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Yes, good point, no longer any need for the unique_array here.
| for i in range(2)] | ||
| data = {x: xvals, y: yvals, z: zvals} | ||
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| if 'hover' in self.tools+self.default_tools: | ||
| for vdim in element.vdims[1:]: | ||
| data[vdim.name] = ['' if is_nan(v) else v |
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Wondering if an empty string really suggests NaN. 'NaN' would be explicit but might look noisy.
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Good point, I'm now using masked arrays to represent the data, in matplotlib the NaNs are therefore represented by -, which might be better.
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Yes, I think - might be a good compromise.
| shape = data.shape | ||
| cmap_name = style.pop('cmap', None) | ||
| cmap = copy.copy(plt.cm.get_cmap('gray' if cmap_name is None else cmap_name)) | ||
| cmap.set_bad('w', 1.) |
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Might want to make this a plot option at some point instead of hard coding 'w'.
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Again good point, indeed we already expose this via clipping_colors, should hook that in here.
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I also find it curious that you are using copy.copy on a colormap - which suggests you are mutating it. I guess set_bad must have side-effects which explains the copying...
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Ok, I've made my comments for now (and you have already replied to most of them). The biggest suggestion is that |
Yes, |
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@jlstevens Once tests are passing this is ready for a second review and then merge. |
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@jlstevens Tests now passing on the PR build. |
| @@ -647,6 +647,30 @@ def walk_depth_first(name): | |||
| (names_by_level.get(i, None) | |||
| for i in itertools.count()))) | |||
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| def is_cyclic(graph): | |||
| """Return True if the directed graph g has a cycle.""" | |||
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What is the representation of the graph? A list of edges as tuples? Would be good to mention in the docstring.
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I'm guessing the representation is similar as in one_to_one...even so, probably worth mentioning..
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Right, all three methods here (sort_topologically, cyclical and one_to_one) use the same representation, which is mapping between nodes and edges, will add the docstring.
| return np.NaN | ||
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| class categorical_aggregate2d(ElementOperation): |
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Looks great! I was just wondering if you want to keep this class in util or move it to operation.element?
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It's imported there but can't be moved, cyclical imports again.
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Ok, having it available for operation.element is fine.
| Generates a categorical 2D aggregate by inserting NaNs at all | ||
| cross-product locations that do not already have a value assigned. | ||
| Returns a 2D gridded Dataset object. | ||
| """ |
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Quite a long method...if you see chunks that could be split up into helper methods, that might be sensible. Up to you though!
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I made three more comments for you to reply to. Otherwise looks good and I expect this will be merged very soon! |
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Latest comments addressed, ready to merge when tests pass. |
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Tests passed. Merging! |
The HeatMap Element has gone through a lot of redesign, initially being defined as a Raster type and then allowing columnar data. This PR refactors HeatMap to improve the simplify aggregation step and allow any number of value dimensions which can appear as hover information in bokeh. Still a WIP and I need to ensure the code is backward compatible (it should be).