Index: plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_streamline.py =================================================================== --- plotly.py-5.11.0.orig/packages/python/plotly/plotly/figure_factory/_streamline.py +++ plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_streamline.py @@ -180,11 +180,11 @@ class _Streamline(object): Set up for RK4 function, based on Bokeh's streamline code """ if isinstance(xi, np.ndarray): - self.x = xi.astype(np.int) - self.y = yi.astype(np.int) + self.x = xi.astype(int) + self.y = yi.astype(int) else: - self.val_x = np.int(xi) - self.val_y = np.int(yi) + self.val_x = int(xi) + self.val_y = int(yi) a00 = a[self.val_y, self.val_x] a01 = a[self.val_y, self.val_x + 1] a10 = a[self.val_y + 1, self.val_x] Index: plotly.py-5.11.0/packages/python/plotly/plotly/express/imshow_utils.py =================================================================== --- plotly.py-5.11.0.orig/packages/python/plotly/plotly/express/imshow_utils.py +++ plotly.py-5.11.0/packages/python/plotly/plotly/express/imshow_utils.py @@ -21,7 +21,6 @@ _integer_types = ( _integer_ranges = {t: (np.iinfo(t).min, np.iinfo(t).max) for t in _integer_types} dtype_range = { np.bool_: (False, True), - np.bool8: (False, True), np.float16: (-1, 1), np.float32: (-1, 1), np.float64: (-1, 1), Index: plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_violin.py =================================================================== --- plotly.py-5.11.0.orig/packages/python/plotly/plotly/figure_factory/_violin.py +++ plotly.py-5.11.0/packages/python/plotly/plotly/figure_factory/_violin.py @@ -16,7 +16,7 @@ def calc_stats(data): """ Calculate statistics for use in violin plot. """ - x = np.asarray(data, np.float) + x = np.asarray(data, float) vals_min = np.min(x) vals_max = np.max(x) q2 = np.percentile(x, 50, interpolation="linear") @@ -160,7 +160,7 @@ def violinplot(vals, fillcolor="#1f77b4" """ Refer to FigureFactory.create_violin() for docstring. """ - vals = np.asarray(vals, np.float) + vals = np.asarray(vals, float) # summary statistics vals_min = calc_stats(vals)["min"] vals_max = calc_stats(vals)["max"] @@ -231,7 +231,7 @@ def violin_no_colorscale( ) color_index = 0 for k, gr in enumerate(group_name): - vals = np.asarray(gb.get_group(gr)[data_header], np.float) + vals = np.asarray(gb.get_group(gr)[data_header], float) if color_index >= len(colors): color_index = 0 plot_data, plot_xrange = violinplot( @@ -319,7 +319,7 @@ def violin_colorscale( min_value = min(group_stats_values) for k, gr in enumerate(group_name): - vals = np.asarray(gb.get_group(gr)[data_header], np.float) + vals = np.asarray(gb.get_group(gr)[data_header], float) # find intermediate color from colorscale intermed = (group_stats[gr] - min_value) / (max_value - min_value) @@ -411,7 +411,7 @@ def violin_dict( ) for k, gr in enumerate(group_name): - vals = np.asarray(gb.get_group(gr)[data_header], np.float) + vals = np.asarray(gb.get_group(gr)[data_header], float) plot_data, plot_xrange = violinplot(vals, fillcolor=colors[gr], rugplot=rugplot) layout = graph_objs.Layout()