#matplotlib.use("GTKCairo") import matplotlib.pyplot as pp import numpy as np import os import shutil import smithplot import time from smithplot.smithaxes import update_scParams from matplotlib.transforms import Affine2D from multiprocessing.pool import Pool from types import FunctionType from utils import parseCSV # sample data data = parseCSV("data/s11", startRow=1, steps=10) s11 = data[:, 1] + data[:, 2] * 1j data = parseCSV("data/s22", startRow=1, steps=10) s22 = data[:, 1] + data[:, 2] * 1j line = np.array([0.4 + 0.7j, 0.4 + 1.8j, 2 + 1j, 2]) def plot_example(ss=True, poly=True, circ=True, rescale=1, **kwargs): if ss: pp.plot(rescale * s11, rescale * s22, markevery=5, **kwargs) if poly: if not "path_interpolation" in kwargs: kwargs["path_interpolation"] = 0 pp.plot(rescale * line, **kwargs)
#matplotlib.use("GTKCairo") import matplotlib.pyplot as pp import numpy as np import os import shutil import smithplot import time from smithplot.smithaxes import update_scParams from matplotlib.transforms import Affine2D from multiprocessing.pool import Pool from types import FunctionType from utils import parseCSV # sample data data = parseCSV("data/s11", startRow=1, steps=10) s11 = data[:, 1] + data[:, 2] * 1j data = parseCSV("data/s22", startRow=1, steps=10) s22 = data[:, 1] + data[:, 2] * 1j line = np.array([0.4 + 0.7j, 0.4 + 1.8j, 2 + 1j, 2]) def plot_example(ss=True, poly=True, circ=True, rescale=1, **kwargs): if ss: pp.plot(rescale * s11, rescale * s22, markevery=5, **kwargs) if poly: if not "path_interpolation" in kwargs: kwargs["path_interpolation"] = 0 pp.plot(rescale * line, **kwargs) if circ:
def __init__(self, id, cards, nrCards=40): self.fullDeck = utils.parseCSV() self.network = NeuralNetwork() NFQPlayer.__init__(self, id, cards, nrCards)
def initDeck(self): self.baralho = parseCSV('csv/cards.csv')
def __init__(self,id, cards, nrCards=40): self.fullDeck = utils.parseCSV() self.network = NeuralNetwork() NFQPlayer.__init__(self, id, cards, nrCards)