![]() update_layout ( margin = dict ( t = 200, r = 200, b = 200, l = 200 ), xaxis = axis_template, yaxis = axis_template, showlegend = False, width = 700, height = 700, autosize = False ) fig. MATLAB ® treats the array as a single column vector with each column appended to the bottom of the previous column. Scatter ( x = - x + x, y = y - y, line = dict ( color = 'white', width = 3 ))) axis_template = dict ( range =, autorange = False, showgrid = False, zeroline = False, linecolor = 'black', showticklabels = False, ticks = '' ) fig. This behavior would make sense for something that I would describe as 'An array of itself', but I doubt anyone in their right mind would choose that as a model for matrices in a scientific library. pi, 1000 ) # angle ( x, y ) = spiral ( theta ) fig. As you can imagine, this has not helped me develop a better understanding of matrix indexing in Numpy. ![]() sort ( ye ), z = z, type = 'heatmap', colorscale = 'Viridis' )) # Add spiral line plot def spiral ( th ): a = 1.120529 b = 0.306349 r = a * np. ![]() # golden ratio xe = ye = z =, ,, ] fig = go. You can base this type of indexing on either the values or. ![]() Import aph_objects as go import numpy as np # Build the rectangles as a heatmap # specify the edges of the heatmap squares phi = ( 1 + np. array indexing that uses one array as the index into another array. ![]()
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