pyplot不光支持线形坐标图, 还可以作对数图. 如果说数据跨了很大的数量级, 那么用plt.xscale('log')就可以更改其缩放. 给个例子: from matplotlib.ticker import NullFormatter # useful for `logit` scale # Fixing random state for reproducibility np.random.seed(19680801) # make up some data in the in...
plt.xscale(‘log’) 下面显示了具有相同数据和不同 y 轴比例的四个图的示例。 # Fixing random state for reproducibility np.random.seed(19680801) # make up some data in the open interval (0, 1) y = np.random.normal(loc=0.5, scale=0.4, size=1000) y = y[(y > 0) & (y < 1)] y...
plt.grid(True)# Format the minor tick labels of the y-axis into empty strings with# `NullFormatter`, to avoid cumbering the axis with too many labels.plt.gca().yaxis.set_minor_formatter(NullFormatter())# Adjust the subplot layout, because the logit one may take more space# than usual, ...
x, y = numpy.log(self.dnorm), numpy.log(self.mnorm)else: x, y = self.dnorm, self.mnormdefscale(a):vmin, vmax = a.min(), a.max() l, u =-10,10return(((u - l) / (vmax - vmin)) * (a - (u * vmin - l * vmax) / (u - l)))returnscale(x), scale(y) 开发者...
也可以获取plot返回后的对象,调用plt的setp函数对对象进行操作 importnumpyasnpx=np.linspace(0,1,20)plt.figure(figsize=(10,10))plt.subplot(2,2,1)lines=plt.plot(x,x*x,'--')##获取lines对象plt.setp(lines,color="r",linewidth=10.0,alpha=0.5)##调用方法对对象进行操作plt.subplot(2,2,2)line...
也可以获取plot返回后的对象,调用plt的setp函数对对象进行操作 import numpy as npx=np.linspace(0,1,20)plt.figure(figsize=(10,10))plt.subplot(2,2,1)lines=plt.plot(x,x*x,'--') ##获取lines对象plt.setp(lines,color="r",linewidth=10.0,alpha=0.5) ##调用方法对对象进行操作plt.subplot(2,2...
log : bool, optional If True, the histogram axis will be set to a log scale. If log is True and x is a 1D array, empty bins will be filtered out and only the non-empty (n, bins, patches) will be returned.(如果为True,则直方图轴将设置为对数刻度。如果log为True且x为1D数组,则将过...
log : bool, optional, default: False If True, set the y-axis to be log scale. orientation : {'vertical', 'horizontal'}, optional This is for internal use only. Please use barh for horizontal bar plots. Default: 'vertical'.(这仅供内部使用。请使用barh作为水平条形图。默认值:'vertical'...
** kwargs =接受不同的关键字参数,具体取决于比例尺(matplotlib.scale.LinearScale,LogScale,SymmetricalLogScale,LogitScale) 范例1: Python3 importnumpyasnpimportpandasaspdimportmatplotlib.pyplotaspltimporttime %matplotlib inline# Example 1y = np.random.randn(50) ...
plt.xscale('log') 下面顯示了具有相同資料和y軸不同比例的四個圖的範例。 from matplotlib.ticker import NullFormatter # useful for `logit` scale # Fixing random state for reproducibility np.random.seed(19680801) # make up some data in the interval ]0, 1[ ...