from ActiveShapeModels import ASM, Point, Shape import matplotlib.pyplot as plt import seaborn as sns import math import numpy as np s1 = Shape( [ Point(200,300), Point(100, 200), Point(300, 50 ) ] ) s2 = Shape( [ Point(150,250), Point(50, 100 ), Point(250, 0) ] ) f, ((ax1,ax2),(ax3,ax4)) = plt.subplots(2,2, sharex =True, sharey = True) s1.draw( sns.xkcd_palette( ["light blue" ]), ax1) s2.draw( sns.xkcd_palette( ["light blue"] ), ax2) cmShape = ASM.centroid( s1) cmMeanShape = ASM.centroid( s2 ) ax1.scatter( cmShape.x, cmShape.y, c='r') ax2.scatter( cmMeanShape.x, cmMeanShape.y, c='r') ax1.plot( [s1.shapePoints[0].x, s1.shapePoints[1].x], [s1.shapePoints[0].y, s1.shapePoints[1].y], color= 'r', ls = '-') ax2.plot( [s2.shapePoints[0].x, s2.shapePoints[1].x], [s2.shapePoints[0].y, s2.shapePoints[1].y], color= 'r', lw = 1, ls = '-')
import numpy as np #s1 = Shape( [ Point(200,300), Point(100, 200), Point(300, 50 ) ] ) #s2 = Shape( [ Point(150,250), Point(50, 100 ), Point(250, 0) ] ) s1 = Shape([ Point(857, -129), Point(89, -409), Point(-404, 254), Point(96, 957), Point(877, 712) ]) f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) s1.draw(sns.xkcd_palette(["light blue"]), 0, ax1) #s2.draw( sns.xkcd_palette( ["light blue"] ), ax2) cmShape = ASM.centroid(s1) #cmMeanShape = ASM.centroid( s2 ) ax1.scatter(cmShape.x, cmShape.y, c='r') #ax2.scatter( cmMeanShape.x, cmMeanShape.y, c='r') ax1.plot([s1.shapePoints[0].x, s1.shapePoints[1].x], [s1.shapePoints[0].y, s1.shapePoints[1].y], color='r', ls='-') #ax2.plot( [s2.shapePoints[0].x, s2.shapePoints[1].x], # [s2.shapePoints[0].y, s2.shapePoints[1].y], # color= 'r', lw = 1, ls = '-')
from ActiveShapeModels import ASM, Point, Shape import matplotlib.pyplot as plt import seaborn as sns import math import numpy as np s1 = Shape([Point(200, 300), Point(100, 200), Point(300, 50)]) s2 = Shape([Point(150, 250), Point(50, 100), Point(250, 0)]) f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex=True, sharey=True) s1.draw(sns.xkcd_palette(["light blue"]), ax1) s2.draw(sns.xkcd_palette(["light blue"]), ax2) cmShape = ASM.centroid(s1) cmMeanShape = ASM.centroid(s2) ax1.scatter(cmShape.x, cmShape.y, c='r') ax2.scatter(cmMeanShape.x, cmMeanShape.y, c='r') ax1.plot([s1.shapePoints[0].x, s1.shapePoints[1].x], [s1.shapePoints[0].y, s1.shapePoints[1].y], color='r', ls='-') ax2.plot([s2.shapePoints[0].x, s2.shapePoints[1].x], [s2.shapePoints[0].y, s2.shapePoints[1].y], color='r', lw=1, ls='-') t = [[cmShape.x - cmMeanShape.x], [cmShape.y - cmMeanShape.y]]
from ActiveShapeModels import ASM, Point, Shape import matplotlib.pyplot as plt import seaborn as sns import math import numpy as np #s1 = Shape( [ Point(200,300), Point(100, 200), Point(300, 50 ) ] ) #s2 = Shape( [ Point(150,250), Point(50, 100 ), Point(250, 0) ] ) s1 = Shape( [ Point(857, -129), Point(89,-409), Point(-404,254), Point( 96,957), Point(877,712) ]) f, ((ax1,ax2),(ax3,ax4)) = plt.subplots(2,2) s1.draw( sns.xkcd_palette( ["light blue" ]), 0, ax1) #s2.draw( sns.xkcd_palette( ["light blue"] ), ax2) cmShape = ASM.centroid( s1 ) #cmMeanShape = ASM.centroid( s2 ) ax1.scatter( cmShape.x, cmShape.y, c='r') #ax2.scatter( cmMeanShape.x, cmMeanShape.y, c='r') ax1.plot( [s1.shapePoints[0].x, s1.shapePoints[1].x], [s1.shapePoints[0].y, s1.shapePoints[1].y], color= 'r', ls = '-') #ax2.plot( [s2.shapePoints[0].x, s2.shapePoints[1].x], # [s2.shapePoints[0].y, s2.shapePoints[1].y], # color= 'r', lw = 1, ls = '-')