visualise functions in R2 and R3 in python

plotter.py

# In[1]:

import os,sys,glob
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# run for jupyter notebook
# get_ipython().magic('matplotlib notebook')
# from IPython.core.interactiveshell import InteractiveShell
# InteractiveShell.ast_node_interactivity = "all"

# ## Plotter functions

# In[2]:

def plot_2d(function, x):
    y = eval(function)
    plt.clf()
    plt.plot(x, y)
    plt.show()
#%%


# In[3]:

def plot_3d(Z, X, Y):
    from mpl_toolkits.mplot3d import Axes3D
    from matplotlib import cm
    from matplotlib.ticker import LinearLocator, FormatStrFormatter
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1,
                           cmap=cm.RdBu, linewidth=0, antialiased=False)

    ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
    fig.colorbar(surf, shrink=0.5, aspect=5)
    plt.show()


# In[4]:

x = np.arange(-20, 20, 0.5)
plot_2d('-x**2 + 2 * x - 2', x)


# In[5]:

x = np.arange(-20, 20, 0.5)
plot_2d('-x**3+ 2 * x**2 - 2', x)


# In[6]:

x = np.arange(-3.0, 3.0, 0.1)
y = np.arange(-3.0, 3.0, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

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

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[7]:

y = np.arange(-10, 10, 0.1)
x = np.arange(-10, 10, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return x**2 + y**2 - 2*x - 2*y

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[78]:

y = np.linspace(-20, 20, 50)
x = np.linspace(-20, 20, 50)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return x**2 + y**2 - 2*x - 2*y

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[81]:

y = np.arange(-10, 10, 0.1)
x = np.arange(-10, 10, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return -x**2 +x*y - y**2 +x - y

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[ ]:

y = np.arange(-30, 30, 0.1)
x = np.arange(-30, 30, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return (x-y)**2

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[82]:

y = np.arange(-10, 10, 0.1)
x = np.arange(-10, 10, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return -x**2 + y**4

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[10]:

y = np.arange(0, 3, 0.1)
x = np.arange(0, 3, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return 2-3*x*y+ x**2*y**2

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[4]:

y = np.arange(0, 10, 0.1)
x = np.arange(0, 10, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return 1/(x*y+1)

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[ ]:




# In[4]:

y = np.arange(0, 10, 0.1)
x = np.arange(0, 10, 0.1)
X, Y = np.meshgrid(x, y)  # grid of points

def z_func(x, y):
    return (x-2)**2 + (y-2)**2

Z = z_func(X, Y)
plot_3d(Z, X, Y)


# In[ ]: