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Remove old normalising code from plt.hist#9121
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -5988,13 +5988,6 @@ def hist(self, x, bins=None, range=None, density=None, weights=None, | ||
| -------- | ||
| hist2d : 2D histograms | ||
| """ | ||
| # Avoid shadowing the builtin. | ||
| bin_range = range | ||
| @@ -6087,38 +6080,37 @@ def hist(self, x, bins=None, range=None, density=None, weights=None, | ||
| else: | ||
| hist_kwargs = dict(range=bin_range) | ||
| # List to store all the top coordinates of the histograms | ||
| tops = [] | ||
| mlast = None | ||
| # Loop through datasets | ||
| for i in xrange(nx): | ||
| # this will automatically overwrite bins, | ||
| # so that each histogram uses the same bins | ||
| m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs) | ||
| m = m.astype(float) # causes problems later if it's an int | ||
| if mlast is None: | ||
| mlast = np.zeros(len(bins)-1, m.dtype) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others.Learn more. This is the old normalising code | ||
| if stacked: | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others.Learn more. This if statement is never used due to the same statement on line 6097 | ||
| m += mlast | ||
| mlast[:] = m | ||
| tops.append(m) | ||
| # If a stacked density plot, normalize so the area of all the stacked | ||
| # histograms together is 1 | ||
| if stacked and density: | ||
| db = np.diff(bins) | ||
| for m intops: | ||
| m[:] = (m.astype(float) / db) /tops[-1].sum() | ||
| if cumulative: | ||
| slc = slice(None) | ||
| if cbook.is_numlike(cumulative) and cumulative < 0: | ||
| slc = slice(None, None, -1) | ||
| if density: | ||
| tops = [(m * np.diff(bins))[slc].cumsum()[slc] for m intops] | ||
| else: | ||
| tops = [m[slc].cumsum()[slc] for m intops] | ||
| patches = [] | ||
| @@ -6136,7 +6128,7 @@ def hist(self, x, bins=None, range=None, density=None, weights=None, | ||
| if rwidth is not None: | ||
| dr = np.clip(rwidth, 0, 1) | ||
| elif (len(tops) > 1 and | ||
| ((not stacked) or rcParams['_internal.classic_mode'])): | ||
| dr = 0.8 | ||
| else: | ||
| @@ -6162,7 +6154,7 @@ def hist(self, x, bins=None, range=None, density=None, weights=None, | ||
| _barfunc = self.bar | ||
| bottom_kwarg = 'bottom' | ||
| for m, c in zip(tops, color): | ||
| if bottom is None: | ||
| bottom = np.zeros(len(m)) | ||
| if stacked: | ||
| @@ -6206,7 +6198,7 @@ def hist(self, x, bins=None, range=None, density=None, weights=None, | ||
| # For data that is normed to form a probability density, | ||
| # set to minimum data value / logbase | ||
| # (gives 1 full tick-label unit for the lowest filled bin) | ||
| ndata = np.array(tops) | ||
| minimum = (np.min(ndata[ndata > 0])) / logbase | ||
| else: | ||
| # For non-normed (density = False) data, | ||
| @@ -6229,7 +6221,7 @@ def hist(self, x, bins=None, range=None, density=None, weights=None, | ||
| fill = (histtype == 'stepfilled') | ||
| xvals, yvals = [], [] | ||
| for m intops: | ||
| if stacked: | ||
| # starting point for drawing polygon | ||
| y[0] = y[1] | ||
| @@ -6292,9 +6284,9 @@ def hist(self, x, bins=None, range=None, density=None, weights=None, | ||
| p.set_label('_nolegend_') | ||
| if nx == 1: | ||
| returntops[0], bins, cbook.silent_list('Patch', patches[0]) | ||
| else: | ||
| returntops, bins, cbook.silent_list('Lists of Patches', patches) | ||
| @_preprocess_data(replace_names=["x", "y", "weights"], label_namer=None) | ||
| def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None, | ||
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1464,6 +1464,14 @@ def test_hist_step_filled(): | ||
| assert all([p.get_facecolor() == p.get_edgecolor() for p in patches]) | ||
| @image_comparison(baseline_images=['hist_density'], extensions=['png']) | ||
| def test_hist_density(): | ||
| np.random.seed(19680801) | ||
| data = np.random.standard_normal(2000) | ||
| fig, ax = plt.subplots() | ||
| ax.hist(data, density=True) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others.Learn more. Does this actually need an image test, or can we just test that There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others.Learn more. I don't think there was ever any image test that used the 'density' or 'norm' There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others.Learn more. I think we are trying to keep image tests to things where the actual image appearance might change if code changes. So sure if there is no hist image test there should be one. If such a test does exist then this just tests the value of the bars, and I think you can do that w/o an image comparison. But I’m not passionate about it or anything. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others.Learn more. Beating a dead horse, but: np.random.seed(19680801)data=np.random.standard_normal(2000)fig,ax=plt.subplots()n,bins,patches=ax.hist(data,density=True)assertnp.isclose(np.sum(n*np.diff(bins)),1.0) | ||
| @image_comparison(baseline_images=['hist_step_log_bottom'], | ||
| remove_text=True, extensions=['png']) | ||
| def test_hist_step_log_bottom(): | ||