# If fewer than 2 neighbors, cell is dead.īoard[neighbor_sums 3 neighbors, cell dies Neighbor_sums = sp.nvolve2d(game_board, kernel, mode='same', boundary="wrap") I was reading about Conway's ( Rules) the other day, and it occurred to me that all the constraints in the game are linear constraints which means that Game of Life should fit into a linear program form since future board states must follow the following linear constraints: def life_step(game_board):
#Scipy solve how to#
Tl dr - how does scipy's convolve2d actually do the convolution operation? I found my way to Toeplitz matrices, but I am confused about how to actually create the Toeplitz matrix. If I to to fill it with a color, for instance, that doesn't work. How do I declare game_screen as a global in the module in a way that works? In a way that can have set_mode used on it after initial declaration? In a way that other modules can use that variable appropriately?ĭo I need to somehow declare it as a pygame Surface? If so, how? I tried doing that, making it = to a Surface object, but that Surface object doesn't behave properly. How do I declare it as a type that will work? I assumed, wrongly it looks like, that declaring a variable with None doesn't work. It declares it as a type that isn't compatible with _mode((blah, blah)). I declare a variable game_screen which can be set and returned with set and return functions within its module. How do I declare a surface variable with a default value that will later be replaced by another value using set_mode to create the main game screen/window? and is there some orphaned Surface floating somewhere in memory since the Surface has been redefined with set_mode? So, I cannot declare the game_screen initially with set_mode because that will be done later with a function, and I've found that if I do it with bogus values (1,1) for height and width and then later redefine, it puts the screen window with the top left in the center of my monitor. I want the player to be able to change and save the size of the game screen/window. I declare the variable as a global in the module and then want to call the set_mode function in a function later using values for height and width that are in a text file. I am trying to create a module which will act kind of like a singleton for important functions and variables which can be accessed by various other modules.Īmong them is a surface object I want to contain the game main screen. However, this correctly retrieves all the columns with the companies and the sales volume for 31st December, but I do not know how to retrieve the most recent possible values when there is no value on the 31st of December for a certain company in certain year.
#Scipy solve code#
Currently I have the following code to retrieve the entries belonging to every 31st December every year: end_of_year_sales = df.loc For example, if there is no entry for Amazon belonging to 12-31-2015, but there is one for 12-30-2015, I want to retrieve that entry. I would like to select all the values belonging to 31 December for every year, and if no entry is existent for that date, I want to select the previous closest date that has a value and return a data frame with the companies and their entries for 31st December for every year or the most recent if not available. The df is indexed by dates in datetime format. I have a data frame(df) with as the columns company names, and as the entries their sales volume for a certain day in a certain year up until that point, cumulative. Print("Method: ".format(solution, (solution - x))) We consider the equation: b = A x, where A is Toeplitz, b and x are matrices and we wish to Linear equation involving a Toeplitz matrix and determine which one is """This script serves to benchmark several methods for solving a What are my options for speeding up the process and perhaps utilizing the Toeplitz structure?Ī possible explanation for _toeplitz being slow is that it uses a slow for-loop for matrix inputs to solve the individual linear systems with x, b being vectors (solving each column at a time). However, when x, b are matrices it is much slower than both and (see output from my test-script)Įxecution time is critical in my application. The Durbin-Levinson implemented in Scipy as _toeplitz should efficiently solve the above system utilizing the structure of A, and indeed it does this when x,b are vectors. Where A is an N x N Toeplitz matrix (that is, the left-to-right diagonals are constant) and x, b are N x N matrices. I am trying to efficiently solve the following linear system in Python 3.6:
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