What is the shortest Python code to get a maximum from the two discrete functions?
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For given two discrete functions like this:
y1 = lambda(x): x**2 y2 = lambda(x): (x-1.5)*10 x1 = np.linspace(0,12,50) x2 = np.linspace(1,10,12) plot(x1, y1(x1), '.-') plot(x2, y2(x2), '.-')
what is the shortest Python code to get the maximum of them?
x = np.sort(np.r_[x1, x2]) y = np.maximum(np.interp(x, x1, y1(x1)), np.interp(x, x2, y2(x2)))
statistics — Mathematical statistics functions — Python 3.8.5 , This module provides functions for calculating mathematical statistics of Single mode (most common value) of discrete or nominal data. mean([1, 2, 3, 4, 4]) 2.8 >>> mean([-1.0, 2.5, 3.25, 5.75]) 2.625 >>> from If the smallest or largest of those is desired instead, use min(multimode(data)) or max(multimode(data)) . In another Python Patterns column, I will try to analyze their running speed and improve their performance, at the cost of more code. UPDATE: Eryk Kopczyński pointed out that these functions are not optimal. To the contrary, "this program runs in exponential time, while find_shortest_path can be done in linear time using BFS [Breadth First
Well you just need to use the built-in
max function on the y values.
f1max = max([y1(x) for x in x1]) f2max = max([y2(x) for x in x2])
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I would do this as:
#!/usr/bin/env ipython # ------------------- import numpy as np import matplotlib as mpl mpl.use('TKAgg'); from pylab import plot,show # --------------------- y1 = lambda(x): x**2 y2 = lambda(x): (x-1.5)*10 x1 = np.linspace(0,12,50) x2 = np.linspace(1,10,12) # -------------------- ymax=np.max((y1(x1),y2(x1)),axis=0) plot(x1, y1(x1), '.-') plot(x2, y2(x2), '.-') plot(x1, ymax, 'k',lw=2.0) show()
max() and min() in Python, This function is used to compute the minimum of the values passed in its argument and lexicographically smallest value if strings are passed as� Distance between two Vertices: It is the number of edges in the shortest path between two vertices. Let us try to calculate the distance between vertices A and D: Possible paths between A and D are: AB -> BC -> CD AD AB -> BD Out of these three paths, AD is the shortest having only one edge. Hence, the distance between A and D is 1.
Python Advanced: Graph Theory and Graphs in Python, This code generates the following output, if combined with the previously defined graph The following Python function calculates the isolated nodes of a given graph: Edges are represented as sets with one (a loop back to the vertex) or two vertices We want to find now the shortest path from one node to another node. A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
Python Statistics Fundamentals: How to Describe Your Data – Real , You'll find out how to describe, summarize, and represent your data 5 Python + Matplotlib examples with full source code that you can use as a The function mean() and method .mean() from NumPy return the u = [2, 3, 2, 8, 12] >>> mode_ = max((u.count(item), item) for item in set(u)) >>> mode_ 2. A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
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- What is the one that you've tried?
- you mean the max for every point?
- Yes, in each point. Note, the functions defined at different points.
- @DirtyBit that will not work, because you have to use
maxon an iterable. You are using it on a function.
- Oh, yes iterate over it for each point!
- Thanks! Amazing python!