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- fig,ax = plt.subplots(figsize = (20,16))
- b=ax.contourf(dfE,4,cmap='Greens', alpha=0.5, linewidths=(3,))
- cbax2 = fig.add_axes([0.91, 0.41, 0.02, 0.2])
- cb2 = plt.colorbar(b, cax=cbax2)
- d = ax.contourf(dfH,4,cmap='Reds', linewidths=(3,), alpha=0.5)
- cbax4 = fig.add_axes([0.91, 0.19, 0.02, 0.2])
- cb4 = plt.colorbar(d, cax=cbax4)
- f = ax.contourf(dfS,3,cmap='Wistia', linewidths=(3,), alpha=0.5)
- cbax6 = fig.add_axes([0.97, 0.41, 0.02, 0.2])
- cb6 = plt.colorbar(f, cax=cbax6)
- g = ax.contourf(dfT,4,cmap='Purples', linewidths=(2,), alpha=0.5)
- cbax7 = fig.add_axes([0.97, 0.63, 0.02, 0.2])
- cb7 = plt.colorbar(g, cax=cbax7)
- h = ax.contourf(dfC,4,cmap='Blues', linewidths=(3,), alpha=0.5)
- cbax8 = fig.add_axes([0.91, 0.63, 0.02, 0.2])
- cb8 = plt.colorbar(h, cax=cbax8)
- ax.set_ylim([0, 16])
- ax.set_xlim([0, 16])
- ax.set_xlabel('Principal Component 1', size = 25)
- ax.set_ylabel('Principal Component 2', size = 25)
- cb4.set_label('Helix (H)',size = 15)
- cb2.set_label('Sheet (E)',size = 15)
- cb8.set_label('Other (C)',size = 15)
- cb7.set_label('H-Bonded Turn (T)',size = 15)
- cb6.set_label('Bend (S)',size = 15)
- ax.set_title('8-State PCA Analysis: 108 Dimensions', size = 30)
- plt.show()
- import numpy as np
- from matplotlib import pyplot as plt
- #Create the grid
- x = np.arange(-20,21,1)
- y=x
- X,Y = np.meshgrid(x,y)
- #Create the functions to plot
- Z1 = 1000-np.abs(X**2+(Y+4)**3)
- Z2 = 1000-np.abs((X+4)**3+Y**3)
- Z3 = 1000-np.abs((Y+2)**3+(X-3)**3)
- Z4 = 1000-np.abs(X**2+Y**3-1)
- fig = plt.figure(figsize=(8,8))
- ax = plt.subplot(111)
- #Plot using contourf making sure you set your contour levels and don't show the lowest levels
- b=ax.contourf(X,Y,Z1/np.nanmax(Z1),[.25,.5,.75],alpha=.5,cmap='Greens',linewidths=3,extend='max')
- d=ax.contourf(X,Y,Z2/np.nanmax(Z2),[.25,.5,.75],alpha=.5,cmap='Reds',linewidths=3,extend='max')
- f=ax.contourf(X,Y,Z3/np.nanmax(Z3),[.25,.5,.75],alpha=.5,cmap='Blues',linewidths=3,extend='max')
- g=ax.contourf(X,Y,Z4/np.nanmax(Z4),[.25,.5,.75],alpha=.5,cmap='Purples',linewidths=3,extend='max')
- plt.show()
- import numpy as np
- from matplotlib import pyplot as plt
- #Create the grid
- x = np.arange(-20,21,1)
- y=x
- X,Y = np.meshgrid(x,y)
- #Create the functions to plot
- Z1 = 1000-np.abs(X**2+(Y+4)**3)
- Z2 = 1000-np.abs((X+4)**3+Y**3)
- Z3 = 1000-np.abs((Y+2)**3+(X-3)**3)
- Z4 = 1000-np.abs(X**2+Y**3-1)
- fig = plt.figure(figsize=(8,8))
- ax = plt.subplot(111)
- #Plot using contour instead of contourf and change the colors
- b=ax.contour(X,Y,Z1/np.nanmax(Z1),[.25,.5,.75],alpha=.8,colors='Green',linewidths=3)
- d=ax.contour(X,Y,Z2/np.nanmax(Z2),[.25,.5,.75],alpha=.8,colors='Red',linewidths=3)
- f=ax.contour(X,Y,Z3/np.nanmax(Z3),[.25,.5,.75],alpha=.8,colors='Blue',linewidths=3)
- g=ax.contour(X,Y,Z4/np.nanmax(Z4),[.25,.5,.75],alpha=.8,colors='Purple',linewidths=3,linestyles='dashed')
- plt.show()
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