import matplotlib.pyplot as plt

%matplotlib inline

import numpy as np


a=np.random.rand(10,3)
x=a[:,0]
y=a[:,1]
z=np.linspace(0,2*np.pi,10)

fig = plt.figure()
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # left, bottom, width, height (range 0 to 1)
axes.plot(a);

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) 
axes.plot(a);

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) 
axes.plot(a);
axes.set_title("Our First Plot");

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # left, bottom, width, height (range 0 to 1)
axes.plot(a);
axes.set_title("Our First Plot");
axes.set_xlabel("alpha ");
axes.set_ylabel("beta ");

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # left, bottom, width, height (range 0 to 1)
axes.plot(a,linewidth=3)
axes.set_title("Our First Plot")
axes.set_xlabel("alpha ")
axes.set_ylabel("beta ")

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) 
axes.plot(a[:,0],a[:,2], "o")
axes.set_title("X Y plot")
axes.set_xlabel("alpha ")
axes.set_ylabel("beta ")

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) 
axes.plot(a[:,0],a[:,2], "o")
axes.set_title("X Y plot")
axes.set_xlabel("alpha ")
axes.set_ylabel("beta ")
axes.grid(True)

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) 
axes.plot(a[:,0],a[:,2], "go")
axes.set_title("X Y plot")
axes.set_xlabel("alpha ")
axes.set_ylabel("beta ")
axes.grid(True)

fig = plt.figure(figsize=(10,4))
axes = fig.add_axes([0.1, 0.1, 0.8, 0.8]) 
axes.plot(a[:,0],a[:,2], "go");
axes.set_title("X Y plot");
axes.set_xlabel("alpha ");
axes.set_ylabel("beta ");
axes.grid(True);

axes2 = fig.add_axes([0.2, 0.5, 0.4, 0.3]) 
axes2.plot(a);
axes2.set_title("mini");
axes2.set_xlabel("a");
axes2.set_ylabel("b");


fig, axes = plt.subplots(figsize=(10,4))

axes.plot(a[:,0],a[:,2], "o")
axes.set_title("X Y plot")
axes.set_xlabel("alpha ")
axes.set_ylabel("beta ")
axes.grid(True)

fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(10,4))

for ax in axes:
    ax.plot(a[:,0],a[:,2], "o")
    ax.set_title("X Y plot")
    ax.set_xlabel("alpha ")
    ax.set_ylabel("beta ")
    ax.grid(True)

fig, axes = plt.subplots(nrows=4, ncols=1,figsize=(8,10))

for ax in axes:
    ax.plot(a[:,0],a[:,2], "o")
    ax.set_title("X Y plot")
    ax.set_xlabel("alpha ")
    ax.set_ylabel("beta ")
    ax.grid(True)


fig, axes = plt.subplots(nrows=4, ncols=1,figsize=(8,10))

for ax in axes:
    ax.plot(a[:,0],a[:,2], "o")
    ax.set_title("X Y plot")
    ax.set_xlabel("alpha ")
    ax.set_ylabel("beta ")
    ax.grid(True)
    
fig.tight_layout()

fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(10,4))

for ax in axes:
    ax.plot(a[:,0],a[:,2], "o")
    ax.set_title("X Y plot")
    ax.set_xlabel("alpha ")
    ax.set_ylabel("beta ")
    ax.grid(True)

fig.tight_layout()

fig.savefig("filename.png")

fig.savefig("filename.png",dpi=300)

fig, ax = plt.subplots(figsize=(10,4))

ax.plot(z, z**2, label="y = z**2")
ax.plot(z, z**3, label="y = z**3")
ax.legend(loc=2); # upper left corner
ax.set_xlabel('z')
ax.set_ylabel('y')
ax.set_title('title');

x=z
fig, axes = plt.subplots(1, 3, figsize=(10, 4))

axes[0].plot(x, x**2, x, x**3)
axes[0].set_title("default axes ranges")

axes[1].plot(x, x**2, x, x**3)
axes[1].axis('tight')
axes[1].set_title("tight axes")

axes[2].plot(x, x**2, x, x**3)
axes[2].set_ylim([0, 60])
axes[2].set_xlim([2, 5])
axes[2].set_title("custom axes range");

fig.tight_layout()

fig, axes = plt.subplots(1, 2, figsize=(10,4))

# default grid appearance
axes[0].plot(x, x**2, x, x**3, lw=2)
axes[0].grid(True)

# custom grid appearance
axes[1].plot(x, x**2, x, x**3, lw=2)
axes[1].grid(color='b', alpha=0.5, linestyle='dashed', linewidth=0.5)
fig.tight_layout()

fig, ax1 = plt.subplots(figsize=(10,4))

ax1.plot(x, x**2, lw=2, color="blue")
ax1.set_ylabel(r"area $(m^2)$", fontsize=18, color="blue")
for label in ax1.get_yticklabels():
    label.set_color("blue")
    
ax2 = ax1.twinx()
ax2.plot(x, x**3, lw=2, color="red")
ax2.set_ylabel(r"volume $(m^3)$", fontsize=18, color="red")
for label in ax2.get_yticklabels():
    label.set_color("red")
fig.tight_layout()

fig, ax = plt.subplots(figsize=(10,4))

ax.plot(x, x**2, x, x**3)

ax.text(5, 10, r"$y=x^2$", fontsize=20, color="blue")
ax.text(4, 160, r"$y=x^3$", fontsize=20, color="green");

def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)

n = 256
x = np.linspace(-3,3,n)
y = np.linspace(-3,3,n)
X,Y = np.meshgrid(x,y)

fig, axes = plt.subplots(1, 1, figsize=(10, 4))
plt.axes([0.025,0.025,0.95,0.95])
plt.contourf(X, Y, f(X,Y), 8, alpha=.75, cmap=plt.cm.hot);
C = plt.contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5);
plt.clabel(C, inline=1, fontsize=10);
plt.xticks([]), plt.yticks([]);

fig, axes = plt.subplots(1, 1, figsize=(10, 4))
plt.axes([0.025,0.025,0.95,0.95])
plt.contourf(X, Y, f(X,Y), 8, alpha=.75, cmap=plt.cm.hot);

fig, axes = plt.subplots(1, 1, figsize=(10, 4))
plt.axes([0.025,0.025,0.95,0.95])
C = plt.contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5)

fig, axes = plt.subplots(1, 1, figsize=(10, 4))
plt.axes([0.025,0.025,0.95,0.95])
C = plt.contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5);
plt.clabel(C, inline=1, fontsize=10);

fig, axes = plt.subplots(1, 1, figsize=(10, 4))
plt.axes([0.025,0.025,0.95,0.95])
C = plt.contour(X, Y, f(X,Y), 8, linewidth=.5);
plt.clabel(C, inline=1, fontsize=10);

x = np.random.rand(20)*10
y = np.random.rand(20)*10

fig, ax = plt.subplots(figsize=(12,6))
ax.bar(range(len(x)), np.sort(y), facecolor='#9999ff',edgecolor='white');
ax.set_title(r"$Bar Chart$");
ax.set_xlabel(r"$\alpha$");
ax.set_ylabel(r"$\beta$");

fig, ax = plt.subplots(figsize=(12,6))
ax.bar(range(len(x)), np.sort(y), facecolor='#9999ff',edgecolor='white');

for xx,yy in zip(range(len(x)),np.sort(y)):
    ax.text(xx+0.4, yy+0.05, '%.2f' % yy, ha='center', va= 'bottom');
ax.set_title(r"$Bar Chart$");
ax.set_xlabel(r"$\alpha$");
ax.set_ylabel(r"$\beta$");

hd=np.random.randn(10000)

fig, ax = plt.subplots(figsize=(10,4))
ax.hist(hd, bins=25,color="lightgreen",edgecolor='white');


fig, ax = plt.subplots(1,2,figsize=(10,4))  
ax[0].hist(hd, bins=10,color="lightgreen",edgecolor='white',orientation="horizontal");
ax[1].plot(hd,"r.");
fig.tight_layout()


n = 12
X,Y = np.mgrid[0:n,0:n]
T = np.arctan2(Y-n/2.0, X-n/2.0)
R = 10+np.sqrt((Y-n/2.0)**2+(X-n/2.0)**2)
U,V = R*np.cos(T), R*np.sin(T)

fig, axes = plt.subplots(1, 1, figsize=(10, 4))
plt.axes([0.025,0.025,0.95,0.95])
plt.quiver(X,Y,U,V,R, alpha=.5);

# Remove Ticks
plt.xlim(-1,n), plt.xticks([]);
plt.ylim(-1,n), plt.yticks([]);


fig, axes = plt.subplots(1, 1, figsize=(10, 4))
plt.axes([0.025,0.025,0.95,0.95])
plt.quiver(X,Y,U,V,R, alpha=.5);
plt.quiver(X,Y,U,V, edgecolor='k', facecolor='None', linewidth=.5);

plt.xlim(-1,n);
plt.xticks([]);
plt.ylim(-1,n);
plt.yticks([]);



Y, X = np.mgrid[-3:3:100j, -3:3:100j]
U = -1 - X**2 + Y
V = 1 + X - Y**2

fig, axes = plt.subplots(1, 1, figsize=(10, 6))
plt.axes([0.025,0.025,0.95,0.95]);
plt.streamplot(X, Y, U, V, density=1, color=U, linewidth=2, cmap=plt.cm.winter);
plt.colorbar();

labels = 'F16', 'Migs', 'Sukhoi', 'F22'
sizes = [23, 34, 44, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'MIGs')


fig, axes = plt.subplots(1, 1, figsize=(10, 6))
i=plt.pie(sizes, labels=labels, )
i=plt.axis('equal')

fig, axes = plt.subplots(1, 1, figsize=(10, 6))
i=plt.pie(sizes, explode=explode, labels=labels, )
i=plt.axis('equal')

fig, axes = plt.subplots(1, 1, figsize=(10, 6))
i=plt.pie(sizes, explode=explode, labels=labels, colors=colors,
        startangle=90)
i=plt.axis('equal')

fig, axes = plt.subplots(1, 1, figsize=(10, 6))
i=plt.pie(sizes, explode=explode, labels=labels, colors=colors,
        autopct='%1.1f%%',  startangle=90)
i=plt.axis('equal')

fig, axes = plt.subplots(1, 1, figsize=(10, 6))
i=plt.pie(sizes, explode=explode, labels=labels, colors=colors,
        autopct='%1.1f%%', shadow=True, startangle=90)
i=plt.axis('equal')

from mpl_toolkits.mplot3d.axes3d import Axes3D

X = np.arange(-5, 5, 0.25)
xlen = len(X)
Y = np.arange(-5, 5, 0.25)
ylen = len(Y)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)

fig, axes = plt.subplots(1, 1, figsize=(10, 6))

axes = fig.add_subplot(1,1,1, projection='3d')
surf = axes.plot_surface(X, Y, Z, rstride=1, cstride=1,
        linewidth=0.5, antialiased=False);
axes.set_zlim3d(-1, 1);


from IPython.display import Image

import mayavi.mlab as mlab

mlab.points3d(a[:,0],a[:,1],a[:,2],a[:,2]);
mlab.show()

Image(r"mlab1.png")

dphi, dtheta = np.pi/250.0, np.pi/250.0
[phi,theta] = np.mgrid[0:np.pi+dphi*1.5:dphi,0:2*np.pi+dtheta*1.5:dtheta]
m0 = 4; m1 = 3; m2 = 2; m3 = 3; m4 = 6; m5 = 2; m6 = 6; m7 = 4;
r = np.sin(m0*phi)**m1 + np.cos(m2*phi)**m3 + np.sin(m4*theta)**m5 + np.cos(m6*theta)**m7
x = r*np.sin(phi)*np.cos(theta)
y = r*np.cos(phi)
z = r*np.sin(phi)*np.sin(theta)

s = mlab.mesh(x, y, z)
mlab.show()

Image(r"mlab2.png")

x, y, z = np.mgrid[-2:3, -2:3, -2:3]
r = np.sqrt(x ** 2 + y ** 2 + z ** 4)
u = y * np.sin(r) / (r + 0.001)
v = -x * np.sin(r) / (r + 0.001)
w = np.zeros_like(z)


src=mlab.quiver3d(x, y, z, u, v, w, line_width=3, scale_factor=1)
mlab.show()

Image(r"mlab3.png")

import numpy as np
x, y, z = np.ogrid[-10:10:20j, -10:10:20j, -10:10:20j]
s = np.sin(x*y*z)/(x*y*z)

mlab.contour3d(s)
mlab.show()

Image(r"mlab4.png")

x, y, z = np.mgrid[0:1:20j, 0:1:20j, 0:1:20j]

u =    np.sin(np.pi*x) * np.cos(np.pi*z)
v = -2*np.sin(np.pi*y) * np.cos(2*np.pi*z)
w = np.cos(np.pi*x)*np.sin(np.pi*z) + np.cos(np.pi*y)*np.sin(2*np.pi*z)

flow = mlab.flow(u, v, w, seed_scale=1,
                          seed_resolution=5,
                          integration_direction='both')
mlab.show()

Image(r"mlab5.png")

x, y = np.mgrid[-7.:7.05:0.1, -5.:5.05:0.05]
f=np.sin(x + y) + np.sin(2 * x - y) + np.cos(3 * x + 4 * y)

s=mlab.surf(x, y, f)
mlab.show()

Image(r"mlab6.png")

from IPython.core.display import HTML
def css_styling():
    styles = open(r'custom.css', 'r').read()
    return HTML(styles)
css_styling()