Python绘制并保存指定大小图像的方法

绘制直线,三角形,正方形

import matplotlib.pyplot as plt

def plotLine():

x = [1,2,3,4,5]

y = [3,3,3,3,3]

plt.figure(figsize=(100,100),dpi=1)

plt.plot(x,y,linewidth=150)

plt.axis('off')

plt.savefig('C:\\Users\\Administrator\\Desktop\\分形图\\a.jpg',dpi=1)

plt.show()

plt.close()

def plotTriangle():

x = [1,3,1,1]

y = [1,1,3,1]

plt.figure(figsize=(100,100),dpi=1)

plt.plot(x,y,linewidth=150)

plt.axis('off')

plt.savefig('C:\\Users\\Administrator\\Desktop\\分形图\\b.jpg',dpi=1)

plt.show()

plt.close()

def plotSquare():

x = [1,3,3,1,1]

y = [1,1,3,3,1]

plt.figure(figsize=(100,100),dpi=1)

plt.plot(x,y,linewidth=150)

plt.axis('off')

plt.savefig('C:\\Users\\Administrator\\Desktop\\分形图\\c.jpg',dpi=1)

plt.show()

plt.close()

plotLine()

plotTriangle()

plotSquare()

from datetime import datetime

import os

import matplotlib.pyplot as plt

import numpy as np

import tensorflow as tf

from six.moves import xrange

data = np.load('data/final37.npy')

data_images = data

data_images = data_images.reshape(-1,3,61)

# data_images = data_images[500:1000,:,:]

for i in range(2000):

plt.figure(figsize=(100,100),dpi=1)

plt.plot(data_images[i][0][0:30],data_images[i][0][30:60],color='blue',linewidth=150)

plt.plot(data_images[i][1][0:30],data_images[i][1][30:60],color='red',linewidth=150)

plt.plot(data_images[i][2][0:30],data_images[i][2][30:60],color='green',linewidth=150)

plt.axis('off')

plt.savefig('C:\\Users\\Administrator\\Desktop\\调整分辨率\\原始图\\resouce%d.jpg' %(i),dpi=1)

plt.close()

#################################################################################

# 生成随机分叉图

# import random

# import numpy as np

# import operator

# import os

# import copy

# from matplotlib.font_manager import FontProperties

# from scipy.interpolate import lagrange

# import random

# import matplotlib.pyplot as plt

# np.set_printoptions(threshold=np.inf) #输出全部矩阵不带省略号

# # random.seed(10)

# finaldata = []

# for iy in range(100):

# #固定一个点,尽量使点固定在0-1正方形的中间 #小数点后16位

# pointx = random.uniform(0.3,0.7)

# pointy = random.uniform(0.3,0.7)

# #################################################

# #主分支在上方

# a1x = random.uniform(pointx,0.8)#使第二个点尽量不那么大

# a2x = random.uniform(a1x,1)

# a3x = random.uniform(a2x,1)

# a1y = random.uniform(pointy,0.8)

# a2y = random.uniform(a1y,1)

# a3y = random.uniform(a2y,1)

# ax = [pointx,a1x,a2x,a3x]

# ay = [pointy,a1y,a2y,a3y]

# # print(ax)

# # print(ay)

# #对主分支a段进行插值

# #在ax相同索引直接分别插两个点,最后a段长度由4变成10,既得final_ax

# # print(ay)

# final_ax = []

# final_ay = []

# for i in range(len(ax)-1):

# #round(data,8)小数点保留8位四舍五入

# f = lagrange([round(ax[i],8),round(ax[i+1],8)],[round(ay[i],8),round(ay[i+1],8)])

# insertax = np.linspace(ax[i],ax[i+1],4)#插入2个点,小数点后8位

# insertay = f(insertax)

# for axi in insertax:

# final_ax.append(axi)

# for ayi in insertay:

# final_ay.append(ayi)

# del final_ax[4]

# del final_ax[7]

# del final_ay[4]

# del final_ay[7]

# #################################################

# # #左下分支

# b1x = random.uniform(0.2,pointx)#使第二个点尽量不那么小

# b2x = random.uniform(0,b1x)

# b3x = random.uniform(0,b2x)

# b1y = random.uniform(0.2,pointy)

# b2y = random.uniform(0,b1y)

# b3y = random.uniform(0,b2y)

# bx = [b3x,b2x,b1x,pointx]

# by = [b3y,b2y,b1y,pointy]

# #对左下分支b段进行插值

# final_bx = []

# final_by = []

# for i in range(len(bx)-1):

# f = lagrange([round(bx[i],8),round(bx[i+1],8)],[round(by[i],8),round(by[i+1],8)])

# insertbx = np.linspace(bx[i],bx[i+1],4)

# insertby = f(insertbx)

# for bxi in insertbx:

# final_bx.append(bxi)

# for byi in insertby:

# final_by.append(byi)

# del final_bx[4]

# del final_bx[7]

# del final_by[4]

# del final_by[7]

#

# ##################################################

# #右下分支

# c1x = random.uniform(pointx,0.8)#使第二个点尽量不那么大

# c2x = random.uniform(c1x,1)

# c3x = random.uniform(c2x,1)

# c1y = random.uniform(0.2,pointy)

# c2y = random.uniform(0,c1y)

# c3y = random.uniform(0,c2y)

# cx = [pointx,c1x,c2x,c3x]

# cy = [pointy,c1y,c2y,c3y]

# #对右下分支段进行插值

# final_cx = []

# final_cy = []

# for i in range(len(cx)-1):

# f = lagrange([round(cx[i],8),round(cx[i+1],8)],[round(cy[i],8),round(cy[i+1],8)])

# insertcx = np.linspace(cx[i],cx[i+1],4)

# insertcy = f(insertcx)

# for cxi in insertcx:

# final_cx.append(cxi)

# for cyi in insertcy:

# final_cy.append(cyi)

# del final_cx[4]

# del final_cx[7]

# del final_cy[4]

# del final_cy[7]

# ####################################################

# x = [final_ax,final_bx,final_cx]#三分叉,上为a,左下b,右下c

# y = [final_ay,final_by,final_cy]

# diameter_a = round(random.uniform(0.2,0.25),8)

# diameter_b = round(random.uniform(0.1,0.2),8)

# diameter_c = round(random.uniform(0.1,0.2),8)

# final_a = []#长度为21前10个x坐标点,后面10个是y坐标点,最后一个是管径

# for ax in final_ax:

# final_a.append(ax)

# for ay in final_ay:

# final_a.append(ay)

# final_a.append(diameter_a)

# final_b = []

# for bx in final_bx:

# final_b.append(bx)

# for by in final_by:

# final_b.append(by)

# final_b.append(diameter_b)

# final_c = []

# for cx in final_cx:

# final_c.append(cx)

# for cy in final_cy:

# final_c.append(cy)

# final_c.append(diameter_c)

# finalabc = [final_a,final_b,final_c]

# finaldata.append(finalabc)

# finaldata = np.array(finaldata)

# #复制改变a,不改变b

# finaldata1 = finaldata.copy()

# finaldata2 = finaldata.copy()

# finaldata3 = finaldata.copy()

# #以定点为中心,进行镜像处理

# finaldata1[:,:,0:10] = 2 * pointx -finaldata[:,:,0:10]

# finaldata2[:,:,10:20] = 2 * pointx -finaldata[:,:,10:20]

# finaldata3[:,:,0:20] = 2 * pointx -finaldata[:,:,0:20]

# final = np.concatenate((finaldata,finaldata1,finaldata2,finaldata3),axis=0)

# np.random.shuffle(final)#随机打乱数据,若没有次句,将连续输出一个方向

# print(final.shape)

# # np.save('C:\\Users\\Administrator\\Desktop\\第9周\\80000.npy',final)

# ###########################################

# # 单个可视化图像

# for i in range(len(final)):

# abc = final[i]

# plt.plot(abc[0][0:10],abc[0][10:20],color='blue',linewidth=1.5)

# plt.plot(abc[1][0:10],abc[1][10:20],color='red',linewidth=1.5)

# plt.plot(abc[2][0:10],abc[2][10:20],color='green',linewidth=1.5)

# plt.axis('off')

# plt.savefig('C:\\Users\\Administrator\\Desktop\\ttt\\原图2\\random%d.jpg' %i,dpi=100)

# plt.close()

###########################################

# 分块可视化图像

# data = np.load('C:\\Users\\Administrator\\Desktop\\第8周\\10000.npy')

# print(data.shape)

# rows,cols = 5,5

# fig,axs = plt.subplots(rows,cols)

# cnt = 0

# for i in range(rows):

# for j in range(cols):

# xy = final[cnt]#第n个分叉图,有三个分支,每个分支21个数

# for k in range(len(xy)):

# x = xy[k][0:10]

# y = xy[k][10:20]

# if k == 0 :

# axs[i,j].plot(x,y,color='blue',linewidth=xy[k][20]*15)

# if k == 1:

# axs[i,j].plot(x,y,color='red',linewidth=xy[k][20]*15)

# if k == 2:

# axs[i,j].plot(x,y,color='green',linewidth=xy[k][20]*15)

# axs[i,j].axis('off')

# cnt +=1

# # plt.savefig('C:\\Users\\Administrator\\Desktop\\第9周\\')

# plt.show()

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