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[2010/12/15 00:59:24] 登録
■ 名前
■ ステータス
HP | SP | 攻撃力 | 集中力 | 防御力 | 素早さ | 運 |
---|---|---|---|---|---|---|
157 | 91 | 49 | 18 | 5 | 1 | 15 |
■ 必殺技
名前 | タイプ | レベル | 消費 SP |
---|---|---|---|
ダンシングフラッシュ | MultiAttackType | 3 | 14 |
北斗十字斬 | SuicideAttackType | 2 | 9 |
■ コード
#! /usr/bin/env python # $Id: funcutils.py,v 2.4 2001/01/07 21:35:12 mhagger Exp $ # Copyright (C) 1998-2001 Michael Haggerty <mhagger@alum.mit.edu> # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. This program is distributed in # the hope that it will be useful, but WITHOUT ANY WARRANTY; without # even the implied warranty of MERCHANTABILITY or FITNESS FOR A # PARTICULAR PURPOSE. See the GNU General Public License for more # details; it is available at <http://www.fsf.org/copyleft/gpl.html>, # or by writing to the Free Software Foundation, Inc., 59 Temple Place # - Suite 330, Boston, MA 02111-1307, USA. """funcutils.py -- Subroutines that tabulate a function's values. Convenience functions that evaluate a python function on a grid of points and tabulate the output to be used with Gnuplot. """ __cvs_version__ = '$Revision: 2.4 $' import Numeric import Gnuplot, utils def tabulate_function(f, xvals, yvals=None, typecode=None, ufunc=0): """Evaluate and tabulate a function on a 1- or 2-D grid of points. f should be a function taking one or two floating-point parameters. If f takes one parameter, then xvals should be a 1-D array and yvals should be None. The return value is a Numeric array '[f(x[0]), f(x[1]), ..., f(x[-1])]'. If f takes two parameters, then 'xvals' and 'yvals' should each be 1-D arrays listing the values of x and y at which 'f' should be tabulated. The return value is a matrix M where 'M[i,j] = f(xvals[i],yvals[j])', which can for example be used in the 'GridData' constructor. If 'ufunc=0', then 'f' is evaluated at each point using a Python loop. This can be slow if the number of points is large. If speed is an issue, you should write 'f' in terms of Numeric ufuncs and use the 'ufunc=1' feature described next. If called with 'ufunc=1', then 'f' should be a function that is composed entirely of ufuncs (i.e., a function that can operate element-by-element on whole matrices). It will be passed the xvals and yvals as rectangular matrices. """ if yvals is None: # f is a function of only one variable: xvals = Numeric.asarray(xvals, typecode) if ufunc: return f(xvals) else: if typecode is None: typecode = xvals.typecode() m = Numeric.zeros((len(xvals),), typecode) for xi in range(len(xvals)): x = xvals[xi] m[xi] = f(x) return m else: # f is a function of two variables: xvals = Numeric.asarray(xvals, typecode) yvals = Numeric.asarray(yvals, typecode) if ufunc: return f(xvals[:,Numeric.NewAxis], yvals[Numeric.NewAxis,:]) else: if typecode is None: # choose a result typecode based on what '+' would return # (yecch!): typecode = (Numeric.zeros((1,), xvals.typecode()) + Numeric.zeros((1,), yvals.typecode())).typecode() m = Numeric.zeros((len(xvals), len(yvals)), typecode) for xi in range(len(xvals)): x = xvals[xi] for yi in range(len(yvals)): y = yvals[yi] m[xi,yi] = f(x,y) return m # For backwards compatibility: grid_function = tabulate_function def compute_Data(xvals, f, ufunc=0, **keyw): """Evaluate a function of 1 variable and store the results in a Data. Computes a function f of one variable on a set of specified points using 'tabulate_function', then store the results into a 'Data' so that it can be plotted. After calculation, the data are written to a file; no copy is kept in memory. Note that this is quite different than 'Func' (which tells gnuplot to evaluate the function). Arguments: 'xvals' -- a 1-d array with dimension 'numx' 'f' -- the function to plot--a callable object for which f(x) returns a number. 'ufunc=<bool>' -- evaluate 'f' as a ufunc? Other keyword arguments are passed through to the Data constructor. 'f' should be a callable object taking one argument. 'f(x)' will be computed at all values in xvals. If called with 'ufunc=1', then 'f' should be a function that is composed entirely of ufuncs, and it will be passed the 'xvals' and 'yvals' as rectangular matrices. Thus if you have a function 'f', a vector 'xvals', and a Gnuplot instance called 'g', you can plot the function by typing 'g.splot(compute_Data(xvals, f))'. """ xvals = utils.float_array(xvals) # evaluate function: data = tabulate_function(f, xvals, ufunc=ufunc) return apply(Gnuplot.Data, (xvals, data), keyw) def compute_GridData(xvals, yvals, f, ufunc=0, **keyw): """Evaluate a function of 2 variables and store the results in a GridData. Computes a function 'f' of two variables on a rectangular grid using 'tabulate_function', then store the results into a 'GridData' so that it can be plotted. After calculation the data are written to a file; no copy is kept in memory. Note that this is quite different than 'Func' (which tells gnuplot to evaluate the function). Arguments: 'xvals' -- a 1-d array with dimension 'numx' 'yvals' -- a 1-d array with dimension 'numy' 'f' -- the function to plot--a callable object for which 'f(x,y)' returns a number. 'ufunc=<bool>' -- evaluate 'f' as a ufunc? Other keyword arguments are passed to the 'GridData' constructor. 'f' should be a callable object taking two arguments. 'f(x,y)' will be computed at all grid points obtained by combining elements from 'xvals' and 'yvals'. If called with 'ufunc=1', then 'f' should be a function that is composed entirely of ufuncs, and it will be passed the 'xvals' and 'yvals' as rectangular matrices. Thus if you have a function 'f' and two vectors 'xvals' and 'yvals' and a Gnuplot instance called 'g', you can plot the function by typing 'g.splot(compute_GridData(f, xvals, yvals))'. """ xvals = utils.float_array(xvals) yvals = utils.float_array(yvals) # evaluate function: data = tabulate_function(f, xvals, yvals, ufunc=ufunc) return apply(Gnuplot.GridData, (data, xvals, yvals), keyw) # For backwards compatibility: def GridFunc(f, xvals, yvals, **keyw): return apply(compute_GridData, (xvals, yvals, f,), keyw)