forked from pool/python-plotly
Matej Cepl
3ff6df948c
- Update to version 5.11.0 * Add clustering options to scattermapbox [#5827], with thanks to @elben10 for the contribution! * Add bounds to mapbox suplots [6339] * Add angle, angleref and standoff to marker and add backoff to line; also introduce new arrow symbols to facilitate drawing networks [#6297] * Add minreducedwidth and minreducedheight to layout for increasing control over automargin [#6307] * Add entrywidth and entrywidthmode to legend [#6202, #6324] - Add patches for compatibility with numpy 1.24 * plotly-fix-sources-np1.24.patch * plotly-fix-tests-np1.24.patch OBS-URL: https://build.opensuse.org/request/show/1045226 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-plotly?expand=0&rev=51
82 lines
3.4 KiB
Diff
82 lines
3.4 KiB
Diff
Index: plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_streamline.py
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===================================================================
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--- plotly.py-5.11.0.orig/packages/python/plotly/plotly/figure_factory/_streamline.py
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+++ plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_streamline.py
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@@ -180,11 +180,11 @@ class _Streamline(object):
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Set up for RK4 function, based on Bokeh's streamline code
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"""
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if isinstance(xi, np.ndarray):
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- self.x = xi.astype(np.int)
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- self.y = yi.astype(np.int)
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+ self.x = xi.astype(int)
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+ self.y = yi.astype(int)
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else:
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- self.val_x = np.int(xi)
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- self.val_y = np.int(yi)
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+ self.val_x = int(xi)
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+ self.val_y = int(yi)
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a00 = a[self.val_y, self.val_x]
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a01 = a[self.val_y, self.val_x + 1]
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a10 = a[self.val_y + 1, self.val_x]
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Index: plotly.py-5.11.0/packages/python/plotly/plotly/express/imshow_utils.py
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===================================================================
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--- plotly.py-5.11.0.orig/packages/python/plotly/plotly/express/imshow_utils.py
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+++ plotly.py-5.11.0/packages/python/plotly/plotly/express/imshow_utils.py
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@@ -21,7 +21,6 @@ _integer_types = (
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_integer_ranges = {t: (np.iinfo(t).min, np.iinfo(t).max) for t in _integer_types}
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dtype_range = {
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np.bool_: (False, True),
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- np.bool8: (False, True),
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np.float16: (-1, 1),
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np.float32: (-1, 1),
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np.float64: (-1, 1),
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Index: plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_violin.py
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===================================================================
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--- plotly.py-5.11.0.orig/packages/python/plotly/plotly/figure_factory/_violin.py
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+++ plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_violin.py
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@@ -16,7 +16,7 @@ def calc_stats(data):
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"""
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Calculate statistics for use in violin plot.
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"""
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- x = np.asarray(data, np.float)
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+ x = np.asarray(data, float)
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vals_min = np.min(x)
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vals_max = np.max(x)
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q2 = np.percentile(x, 50, interpolation="linear")
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@@ -160,7 +160,7 @@ def violinplot(vals, fillcolor="#1f77b4"
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"""
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Refer to FigureFactory.create_violin() for docstring.
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"""
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- vals = np.asarray(vals, np.float)
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+ vals = np.asarray(vals, float)
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# summary statistics
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vals_min = calc_stats(vals)["min"]
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vals_max = calc_stats(vals)["max"]
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@@ -231,7 +231,7 @@ def violin_no_colorscale(
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)
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color_index = 0
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for k, gr in enumerate(group_name):
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- vals = np.asarray(gb.get_group(gr)[data_header], np.float)
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+ vals = np.asarray(gb.get_group(gr)[data_header], float)
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if color_index >= len(colors):
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color_index = 0
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plot_data, plot_xrange = violinplot(
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@@ -319,7 +319,7 @@ def violin_colorscale(
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min_value = min(group_stats_values)
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for k, gr in enumerate(group_name):
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- vals = np.asarray(gb.get_group(gr)[data_header], np.float)
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+ vals = np.asarray(gb.get_group(gr)[data_header], float)
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# find intermediate color from colorscale
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intermed = (group_stats[gr] - min_value) / (max_value - min_value)
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@@ -411,7 +411,7 @@ def violin_dict(
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)
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for k, gr in enumerate(group_name):
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- vals = np.asarray(gb.get_group(gr)[data_header], np.float)
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+ vals = np.asarray(gb.get_group(gr)[data_header], float)
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plot_data, plot_xrange = violinplot(vals, fillcolor=colors[gr], rugplot=rugplot)
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layout = graph_objs.Layout()
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