# Start writing code here...
1 + 1
import numpy as np
x = np.array([2, 1.4 , 5, 6, 9.2])
y = np.array([-1.1, 2, 33, 11, 4.5])
a = .5
xnew = (x-2)
ynew = (y-2)
print("xnew and ynew" , xnew, " ", ynew)
xnew = xnew % a
ynew = ynew % a
print("xnew and ynew modulo 0.5 are " , xnew, " ", ynew)
xnew and ynew [ 0. -0.6 3. 4. 7.2] [-3.1 0. 31. 9. 2.5]
xnew and ynew modulo 0.5 are [0. 0.4 0. 0. 0.2] [0.4 0. 0. 0. 0. ]
-3.1 / .5
x = [0, 0.05883, 0.10385, .16138, .22843, .30785, .35412, .4025, 0.4476] #alpha values
ysqu = [.8428, .8362, .8304, .8262, .8123, .8046, .8042,.80751, .79295] # phi_critical values
ytri = [.8428,0.834536,0.827745,0.82761,0.819201,0.79921,0.789193,0.788091,0.784619 ]
w = [0, .070, .125, .195, .281, .383, .439, .500, .564] #n_f values
import matplotlib.pyplot as plt
plt.plot(w,ysqu, 'rs' , markerfacecolor = 'w')
plt.plot(w,ytri, 'g^', markerfacecolor = 'w')
plt.title("Jan 23,24 Pressure sweep data: phi_c vs. n_f")
plt.xlabel('n_f')
plt.ylabel('phi_c')
plt.show()
plt.plot(x,ysqu, 'rs' )
plt.plot(x,ytri, 'g^' )
plt.title("Jan 23, 24 Pressure sweep data: phi_c vs. alpha")
plt.xlabel('alpha')
plt.ylabel('phi_c')
plt.show()
import numpy as np
X_COORDINATE = np.linspace(0.0, 10.0, num=100); Z_COORDINATE = X_COORDINATE; C_I = np.sin(X_COORDINATE * Z_COORDINATE)
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LogNorm
from scipy.interpolate import interp2d
x_list = np.array(X_COORDINATE)
z_list = np.array(Z_COORDINATE)
C_I_list = np.array(C_I)
# f will be a function with two arguments (x and z coordinates),
# but those can be array_like structures too, in which case the
# result will be a matrix representing the values in the grid
# specified by those arguments
f = interp2d(x_list,z_list,C_I_list,kind="linear")
x_coords = np.arange(min(x_list),max(x_list)+1)
z_coords = np.arange(min(z_list),max(z_list)+1)
c_i = f(x_coords,z_coords)
fig = plt.imshow(c_i,
extent=[min(x_list),max(x_list),min(z_list),max(z_list)],
origin="lower", interpolation='bicubic')
# Show the positions of the sample points, just to have some reference
fig.axes.set_autoscale_on(False)
plt.scatter(x_list,z_list,400,facecolors='none')
plt.colorbar()
plt.show()
/opt/venv/lib/python3.7/site-packages/scipy/interpolate/_fitpack_impl.py:977: RuntimeWarning: No more knots can be added because the number of B-spline
coefficients already exceeds the number of data points m.
Probable causes: either s or m too small. (fp>s)
kx,ky=1,1 nx,ny=14,11 m=100 fp=23.438771 s=0.000000
warnings.warn(RuntimeWarning(_iermess2[ierm][0] + _mess))
from pylab import plot,show
y = [1.0, 2.4, 1.7, 0.3, 0.6]
x = [0.0, 1.0, 2.5, 3.9, 4.7]
#plot(y)
plot(x,y, "ro")
plot(x,y,'k')
show()
from numpy import linspace, sin
x = linspace(0,10,1000)
y = sin(x)
plot(x,y)
show()
from numpy import loadtxt
data = loadtxt("values.txt", float)
plot(data[:,0],data[:,1], "co")
plot(data[:,0],data[:,1], 'b')
show()
xpoints = []
ypoints = []
for x in linspace(0,10,1000):
xpoints.append(x)
ypoints.append(sin(x))
plot(xpoints,ypoints)
show()
ypoints = np.power(ypoints,2)
zpoints = np.power(1 - ypoints, .5)
/shared-libs/python3.7/py-core/lib/python3.7/site-packages/ipykernel_launcher.py:3: RuntimeWarning: invalid value encountered in power
This is separate from the ipykernel package so we can avoid doing imports until
import pylab as py
import numpy as np
py.plot(xpoints,ypoints, 'c')
py.plot(xpoints,ypoints, 'b')
py.plot(xpoints,zpoints,'c')
py.ylim(-1.5,1.5)
py.xlabel("x axis"); py.ylabel("y axis")
show()
in_array1 = [0, math.pi / 2, np.pi / 3, np.pi]
out_array1 = np.sin(in_array1)
py.scatter(in_array1, out_array1)
in_array = np.linspace(-np.pi, np.pi, 12)
out_array = np.sin(in_array)
py.plot(in_array, out_array, "r" )
py.scatter(in_array, out_array)
from pylab import imshow,show, gray, jet
from numpy import loadtxt
data = loadtxt("circular.txt",float)
imshow(data)
jet()
show()
from math import sqrt,sin,pi
from numpy import empty
from pylab import imshow,gray,show
wavelength = 5.0
k = 2*pi/wavelength
xi0 = 1.0
separation = 20.0 # Separation of centers in cm
side = 100.0 # Side of the square in cm
points = 500 # Number of grid points along each side
spacing = side/points # Spacing of points in cm
# Calculate the positions of the centers of the circles
x1 = side/2 + separation/2
y1 = side/2
x2 = side/2 - separation/2
y2 = side/2
# Make an array to store the heights
xi = empty([points,points],float)
# Calculate the values in the array
for i in range(points):
y = spacing*i
for j in range(points):
x = spacing*j
r1 = ((x-x1)**2+(y-y1)**2) ** 0.5
r2 = ((x-x2)**2+(y-y2)**2) **0.5
xi[i,j] = xi0*sin(k*r1) + xi0*sin(k*r2)
# Make the plot
imshow(xi,origin="lower",extent=[0,side,0,side])
gray()
show()
from math import sqrt,sin,pi
from numpy import empty
from pylab import imshow,gray,show
wavelength = 5.0
k = 2*pi/wavelength
xi0 = 1.0
separation = 20.0 # Separation of centers in cm
side = 100.0 # Side of the square in cm
points = 500 # Number of grid points along each side
spacing = side/points # Spacing of points in cm
# Calculate the positions of the centers of the circles
x1 = side/2 + separation/2
y1 = side/2
x2 = side/2 - separation/2
y2 = side/2
# Make an array to store the heights
xi = empty([points,points],float)
# Calculate the values in the array
for i in range(points):
y = spacing*i
for j in range(points):
x = spacing*j
r1 = ((x-x1)**2+(y-y1)**2) ** 0.5
r2 = ((x-x2)**2+(y-y2)**2) **0.5
xi[i,j] = xi0*sin(k*r1) + xi0*sin(k*r2)
# Make the plot
imshow(xi,origin="lower",extent=[0,side,0,side])
#gray()
show()
from math import sqrt,sin,pi
from numpy import empty
from pylab import imshow,gray,show
wavelength = 5.0
k = 2*pi/wavelength
xi0 = 1.0
separation = 20.0 # Separation of centers in cm
side = 100.0 # Side of the square in cm
points = 500 # Number of grid points along each side
spacing = side/points # Spacing of points in cm
# Calculate the positions of the centers of the circles
x1 = side/2 + separation/2
y1 = side/2
x2 = side/2 - separation/2
y2 = side/2
# Make an array to store the heights
xi = empty([points,points],float)
# Calculate the values in the array
for i in range(points):
y = spacing*i
for j in range(points):
x = spacing*j
r1 = ((x-x1)**2+(y-y1)**2) ** 0.5
r2 = ((x-x2)**2+(y-y2)**2) **0.5
xi[i,j] = xi0*sin(k*r1) + xi0*sin(k*r2)
# Make the plot
imshow(xi,origin="lower",extent=[0,side,0,side])
gray()
show()