#==============================================================================
#==============================================================================
# 第4章 學(xué)習(xí)更多圖表和定制化 99
# 4．1 簡(jiǎn)介 99
#==============================================================================
#==============================================================================
# 4．2 設(shè)置坐標(biāo)軸標(biāo)簽的透明度和大小 100
#==============================================================================
4．2．1 準(zhǔn)備工作 100
4．2．2 操作步驟 100
4．2．3 工作原理 101
4．2．4 補(bǔ)充說(shuō)明 102
import matplotlib.pyplot as plt
from matplotlib import patheffects
import numpy as np
data = np.random.randn(70)
fontsize = 18
plt.plot(data)
title = "This is figure title";
x_label = "This is x axis label";y_label = "This is y axis label"
title_text_obj = plt.title(title, fontsize=fontsize, verticalalignment='bottom')
title_text_obj.set_path_effects([patheffects.withSimplePatchShadow()])
'''customize shadow properties
offset_xy -- set the 'angle' of the shadow
shadow_rgbFace -- set the color of the shadow
patch_alpha -- setup the transparaency of the shadow
亦可繼承patheffects._Base類,并重寫(xiě)draw_path方法
'''
pe = patheffects.withSimplePatchShadow(
? ? ? ? offset_xy = (1, -1),
? ? ? ? shadow_rgbFace = (1.0,0.0,0.0),
? ? ? ? patch_alpha =? 0.8)
# apply them to the xaxis and yaxis labels
xlabel_obj = plt.xlabel(x_label, fontsize=fontsize, alpha=0.5)
xlabel_obj.set_path_effects([pe])
ylabel_obj = plt.ylabel(y_label, fontsize=fontsize, alpha=0.5)
ylabel_obj.set_path_effects([pe])
plt.show()
#==============================================================================
# 4．3 為圖表線條添加陰影 102
#==============================================================================
4．3．1 準(zhǔn)備工作 103
4．3．2 操作步驟 103
4．3．3 工作原理 105
4．3．4 補(bǔ)充說(shuō)明 105
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
def setup(layout=None):
? ? assert layout is not None
? ? fig = plt.figure()
? ? ax = fig.add_subplot(layout)
? ? return fig, ax
def get_signal():
? ? t = np.arange(0., 2.5, 0.01)
? ? s = np.sin(5 * np.pi * t)
? ? return t, s?
def plot_signal(t, s):
? ? line, = axes.plot(t, s, linewidth=5, color='magenta')
? ? return line,
def make_shadow(fig, axes, line, t, s):
? ? delta = 2 / 72.? # how many points to move the shadow
? ? offset = transforms.ScaledTranslation(delta, -delta, fig.dpi_scale_trans)
? ? offset_transform = axes.transData + offset
? ? # We plot the same data, but now using offset transform
? ? # zorder -- to render it below the line
? ? axes.plot(t, s, linewidth=5, color='gray',
? ? ? ? ? ? ? transform=offset_transform,
? ? ? ? ? ? ? zorder=0.5 * line.get_zorder())
if __name__ == "__main__":
? ? fig,axes = setup(111)
? ? t, s = get_signal()
? ? line, = plot_signal(t, s)
? ? make_shadow(fig, axes, line, t, s)
? ? axes.set_title('Shadow effect using an offset transform')
? ? plt.show()
#==============================================================================
# 4．4 向圖表添加數(shù)據(jù)表 106
#==============================================================================
4．4．1 準(zhǔn)備工作 106
4．4．2 操作步驟 106
4．4．3 工作原理 107
4．4．4 補(bǔ)充說(shuō)明 107
import matplotlib.pylab as plt
import numpy as np
plt.figure()
axes=plt.gca()
y= np.random.randn(9)
col_labels=['col1','col2','col3']
row_labels=['row1','row2','row3']
table_vals=[[11,12,13],[21,22,23],[28,29,30]]
row_colors=['red','gold','green']
'''基本的函數(shù)簽名
table(? cellText=None, cellColours=None,
? ? ? ? colWidths = None,
? ? ? ? rowLabels=None, rowColours=None, rowLoc='left'
? ? ? ? colLabels=None, colColours=None, rowLoc='left'
? ? ? ? loc='upper right', bbox=None)
'''
the_table = plt.table(cellText=table_vals,
? ? ? ? ? ? ? ? ? colWidths = [0.1]*3,
? ? ? ? ? ? ? ? ? rowLabels=row_labels,
? ? ? ? ? ? ? ? ? colLabels=col_labels,
? ? ? ? ? ? ? ? ? rowColours=row_colors,
? ? ? ? ? ? ? ? ? loc='upper right')
plt.text(12,3.4,'Table Title',size=8)
plt.plot(y)
plt.show()
#==============================================================================
# 4．5 使用subplots(子區(qū)) 108
#==============================================================================
4．5．1 準(zhǔn)備工作 108
4．5．2 操作步驟 108
4．5．3 工作原理 110
4．5．4 補(bǔ)充說(shuō)明 110
import matplotlib.pyplot as plt
plt.figure(0)
'''
? ? fig,ax = plt.subplots 創(chuàng)建普通布局的子區(qū)
? ? plt.subplots_adjust調(diào)整子區(qū)的布局
'''
axes1 = plt.subplot2grid((3, 3), (0, 0), colspan=3)
axes2 = plt.subplot2grid((3, 3), (1, 0), colspan=2)
axes3 = plt.subplot2grid((3, 3), (1, 2))
axes4 = plt.subplot2grid((3, 3), (2, 0))
axes5 = plt.subplot2grid((3, 3), (2, 1), colspan=2)
# tidy up tick labels size
all_axes = plt.gcf().axes
for ax in all_axes:
? ? for ticklabel in ax.get_xticklabels() + ax.get_yticklabels():
? ? ? ? ticklabel.set_fontsize(10)
plt.suptitle("Demo of subplot2grid")
plt.show()
#==============================================================================
# 4．6 定制化網(wǎng)格 110
#==============================================================================
4．6．1準(zhǔn)備工作 110
4．6．2 操作步驟 112
4．6．3 工作原理 114
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
from matplotlib.cbook import get_sample_data
def get_grid(fig=None, layout=None, nrows_ncols=None):
? ? assert fig is not None;assert layout is not None;assert nrows_ncols is not None
? ? grid = ImageGrid(fig, layout, nrows_ncols=nrows_ncols, axes_pad=0.05, add_all=True, label_mode="L")
? ? return grid
def load_images_to_grid(grid, Z, *images):
? ? min,max = Z.min(),Z.max()
? ? for i, image in enumerate(images):
? ? ? ? axes = grid[i]
? ? ? ? axes.imshow(image, origin="lower", vmin=min, vmax=max,interpolation="nearest")
if __name__ == "__main__":
? ? fig = plt.figure(1, (8, 6)) ;? ? grid = get_grid(fig, 111, (1, 3))
? ? # z is a numpy array of 15x15
? ? Z = np.load(get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False))
? ? # Slice image
? ? image1 = Z ;? ? image2 = Z[:, :10];? ? image3 = Z[:, 10:]
? ? load_images_to_grid(grid, Z, image1, image2, image3)
? ? plt.draw()
? ? plt.show()
#==============================================================================
# 4．7 創(chuàng)建等高線圖 114
#==============================================================================
4．7．1 準(zhǔn)備工作 114
4．7．2 操作步驟 115
4．7．3 工作原理 117
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
'''
等高線顯示的是矩陣的等值線isolines
等值線是用數(shù)值相等的各點(diǎn)連成的曲線
'''
x = np.arange(-1.5, 1.5, 0.1)
y = np.arange(-1.5, 1.5, 0.1)
X, Y = np.meshgrid(x, y)# Make grids of points
Z = (1 - (X ** 2 + Y ** 2)) * np.exp(-Y ** 3 / 3)
N = np.arange(-1, 1, 0.5)# Number of isolines
'''
? ? contour()
? ? contour(Z)? 繪制Z數(shù)組的等高線,自動(dòng)選擇水平值
? ? contour(Z,N) 水平數(shù)由N指定,自動(dòng)選擇水平值
? ? contour(Z,V) 繪制Z數(shù)組的等高線,水平值在V中指定
? ? contour(X,Y,Z) 繪制X、Y和Z的等高線.X和Y數(shù)組為(x,y)平面坐標(biāo)(surface coordinates)
? ? contour(X,Y,Z,N)
'''
CS = plt.contour(Z, N, linewidths=2, cmap=mpl.cm.jet)
plt.clabel(CS, inline=True, fmt='%1.1f', fontsize=10)
plt.colorbar(CS)
plt.title('My function: $z=(1-x^2+y^2) e^{-(y^3)/3}$')
plt.show()
#==============================================================================
# 4．8 填充圖表底層區(qū)域 117
#==============================================================================
4．8．1 準(zhǔn)備工作 118
4．8．2 操作步驟 118
4．8．3 工作原理 120
import matplotlib.pyplot as plt
import numpy as np
from math import sqrt
t =range(1000)
y = [sqrt(i) for i in t]
plt.plot(t,y,color='red',lw=2)
plt.fill_between(t,y,color='silver')
plt.show()
----------------------------------------------
import matplotlib.pyplot as plt
import numpy as np
from math import sqrt
x = np.arange(0.0, 2, 0.01)
y1 = np.sin(np.pi*x)
y2 = 1.7*np.sin(4*np.pi*x)
fig = plt.figure()
axes1 = fig.add_subplot(211)
axes1.plot(x, y1, x, y2, color='grey')
axes1.fill_between(x, y1, y2, where=y2<=y1, facecolor='blue', interpolate=True)
axes1.fill_between(x, y1, y2, where=y2>=y1, facecolor='gold', interpolate=True)
axes1.set_title('Blue where y2 <= y1. Gold-color where y2 >= y1.')
axes1.set_ylim(-2,2)
#屏蔽數(shù)組中給定值的所有值
y2 = np.ma.masked_greater(y2, 1.0)
axes2 = fig.add_subplot(212, sharex=axes1)
axes2.plot(x, y1, x, y2, color='black')
axes2.fill_between(x, y1, y2, where=y2<=y1, facecolor='blue', interpolate=True)
axes2.fill_between(x, y1, y2, where=y2>=y1, facecolor='gold', interpolate=True)
axes2.set_title('Same as above, but mask')
axes2.set_ylim(-2,2)
axes2.grid('on')
plt.show()
#==============================================================================
# 4．9 繪制極線圖 121
#==============================================================================
4．9．1 準(zhǔn)備工作 121
4．9．2 操作步驟 121
4．9．3 工作原理 123
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
figsize = 7; N = 18
colormap = lambda r: cm.Set2(r / 20.)
# number of bars
fig = plt.figure(figsize=(figsize,figsize))
ax = fig.add_axes([0.2, 0.2, 0.7, 0.7], polar=True)
theta = np.arange(0.0, 2 * np.pi, 2 * np.pi/N)#角度theta集合
radii = 20 * np.random.rand(N)? ? ? ? ? #極線距離
width = np.pi / 4 * np.random.rand(N)? #每個(gè)極線條的寬度集合
bars = ax.bar(theta, radii, width=width, bottom=0.0)
for r, bar in zip(radii, bars):
? ? bar.set_facecolor(colormap(r))
? ? bar.set_alpha(0.6)
plt.show()
#==============================================================================
# 4．10 使用極線條可視化文件系統(tǒng)樹(shù) 123
#==============================================================================
4．10．1 準(zhǔn)備工作 123
4．10．2 操作步驟 123
4．10．3 工作原理 126
import os
import sys
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
def build_folders(start_path):
? ? folders = []
? ? for each in get_directories(start_path):
? ? ? ? size = get_size(each)
? ? ? ? if size >= 25 * 1024 * 1024:
? ? ? ? ? ? folders.append({'size': size, 'path': each})
? ? for each in folders:
? ? ? ? print "Path: " + os.path.basename(each['path'])
? ? ? ? print "Size: " + str(each['size'] / 1024 / 1024) + " MB"
? ? return folders
def get_size(path):
? ? assert path is not None
? ? total_size = 0
? ? for dirpath, dirnames, filenames in os.walk(path):
? ? ? ? for f in filenames:
? ? ? ? ? ? fp = os.path.join(dirpath, f)
? ? ? ? ? ? try:
? ? ? ? ? ? ? ? size = os.path.getsize(fp)
? ? ? ? ? ? ? ? total_size += size
? ? ? ? ? ? ? ? #print "Size of '{0}' is {1}".format(fp, size)
? ? ? ? ? ? except OSError as err:
? ? ? ? ? ? ? ? print str(err)
? ? ? ? ? ? ? ? pass
? ? return total_size
def get_directories(path):
? ? dirs = set()
? ? for dirpath, dirnames, filenames in os.walk(path):
? ? ? ? dirs = set([os.path.join(dirpath, x) for x in dirnames])
? ? ? ? break? # we just want the first one
? ? return dirs
def draw(folders):
? ? """ Draw folder size for given folder"""
? ? figsize = (8, 8)? # keep the figure square
? ? ldo, rup = 0.1, 0.8? # left down, right up coordinates, normalized
? ? fig = plt.figure(figsize=figsize)
? ? ax = fig.add_axes([ldo, ldo, rup, rup], polar=True)
? ? # transform data
? ? x = [os.path.basename(x['path']) for x in folders]
? ? y = [y['size'] / 1024 / 1024 for y in folders]
? ? theta = np.arange(0.0, 2 * np.pi, 2 * np.pi / len(x))
? ? radii = y
? ? bars = ax.bar(theta, radii)
? ? middle = 90 / len(x)
? ? theta_ticks = [t * (180 / np.pi) + middle for t in theta]
? ? lines, labels = plt.thetagrids(theta_ticks, labels=x, frac=0.5)
? ? for step, each in enumerate(labels):
? ? ? ? each.set_rotation(theta[step] * (180 / np.pi) + middle)
? ? ? ? each.set_fontsize(8)
? ? # configure bars
? ? colormap = lambda r: cm.Set2(r / len(x))
? ? for r, each in zip(radii, bars):
? ? ? ? each.set_facecolor(colormap(r))
? ? ? ? each.set_alpha(0.5)
? ? plt.show()
if __name__ == '__main__':
? ? if len(sys.argv) is not 2:
? ? ? ? print "ERROR: Please supply path to folder."
? ? ? ? sys.exit(-1)
? ? start_path = sys.argv[1]
? ? if not os.path.exists(start_path):
? ? ? ? print "ERROR: Path must exits."
? ? ? ? sys.exit(-1)
? ? folders = build_folders(start_path)
? ? if len(folders) < 1:
? ? ? ? print "ERROR: Path does not contain any folders."
? ? ? ? sys.exit(-1)
? ? draw(folders)
