#!/usr/bin/env python
# coding: utf-8

# In[1]:


# import
import matplotlib.pyplot as plt
import numpy as np

get_ipython().run_line_magic('matplotlib', 'inline')


# #### Figures
# A “ﬁgure” in matplotlib means the whole window in the user interface. Within this ﬁgure there can be “sub-plots”.
# A ﬁgure is the windows in the GUI that has “Figure #” as title. Figures are numbered starting from1 as opposed
# to the normal Python way starting from 0.
# 
# Argument | Default| Description
# ----|---------|----------------------------
# num| 1| number of ﬁgure
# figsize| figure.figsize |ﬁgure size in in inches (width, height)
# dpi| figure.dpi| resolution in dots per inch
# facecolor| figure.facecolor| color of the drawing background
# edgecolor| figure.edgecolor| color of edge around the drawing background
# frameon| True| draw ﬁgure frame or not
# 
# 
# #### Subplots
# With subplot you can arrange plots in a regular grid. You need to specify the number of rows and columns and
# the number of the plot.
# 
# 
# #### Axes
# Axes are very similar to subplots but allow placement of plots at any location in the figure.
# So if we want to put a smaller plot inside a bigger one we do so with axes.
# 
# 
# #### Ticks
# Well formatted ticks are an important part of publishing-ready figures. Matplotlib provides a totally configurable
# system for ticks. There are tick locators to specify where ticks should appear and tick formatters to
# give ticks the appearance you want.

# In[2]:


# generating some data points
X = np.linspace(-np.pi, np.pi, 256, endpoint=True)
C, S = np.cos(X), np.sin(X)


# In[3]:


# creating a figure
fig = plt.figure(figsize=(4,3), dpi=120)

#plotting
plt.plot(X, C, linestyle='--')
plt.plot(X, S)

# plotting
plt.show()


# In[4]:


# creating a figure
fig = plt.figure(figsize=(4,3), dpi=120)

#plotting
plt.plot(X, C, linestyle='--')
plt.plot(X, S, linewidth=2)

# adding labels
plt.xlabel("X data")
plt.ylabel("Y data")
plt.title("Plotting")

# adding margins, grid and autoscale
plt.margins(0.15)
plt.autoscale(True)
plt.grid(True)

# plotting
plt.show()


# ** Adding one more sub plot **

# In[5]:


# creating a figure
fig = plt.figure(figsize=(12,6), dpi=120)

# adding subplot
plt.subplot(1,2,1)   # 1 row, 2 columns, 1st plot
plt.plot(X, C, linestyle='--')
plt.xlabel("X data")
plt.ylabel("Y data")
plt.title("Cos Plotting")
plt.grid(True)
plt.margins(0.15)
plt.legend(["Cos"], loc="upper left")


plt.subplot(1,2,2)  # 1 row, 2 columns, 2nd plot
plt.plot(X, S, linewidth=2)
plt.xlabel("X data")
plt.ylabel("Y data")
plt.title("Sin Plotting")
plt.legend(["Sin"], loc="upper left")
plt.margins(0.15)
plt.autoscale(True)
plt.grid(True)

# plotting
plt.show()


# ** another way to add subplots **

# In[6]:


# creating a figure
fig = plt.figure(figsize=(12,6), dpi=120)

# adding subplot
ax1 = fig.add_subplot(1,2,1)   # 1 row, 2 columns, 1st plot
ax1.plot(X, C, linestyle='--')
ax1.grid(True)
ax1.margins(0.15)

ax2 = fig.add_subplot(1,2,2)  # 1 row, 2 columns, 2nd plot
ax2.plot(X, S, linewidth=2)
ax2.margins(0.2)
ax2.autoscale(True)
ax2.grid(True)

# plotting
plt.xlabel("X data")
plt.ylabel("Y data")
plt.title("Sin Plotting")
plt.legend(["Sin"], loc="upper left")
plt.show()


# ** One more way to add subplots **

# In[7]:


# creating a figure
plt.figure(figsize=(12,6), dpi=120)
f, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, sharex=True, sharey=True)

ax1.plot(X,S, color='green', linestyle='--', linewidth='2')
ax1.grid(True)
ax1.margins(0.2)

ax2.plot(X,C, color='blue', linestyle='-', linewidth='2')
ax2.grid(True)
ax2.margins(0.2)


# In[8]:


# creating a figure
plt.figure(figsize=(12,6), dpi=120)
f, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, sharex=True, sharey=True)

ax1.plot(X,S, color='green', linestyle='--', linewidth='2', label="Sin wave")
ax1.grid(True)
ax1.margins(0.2)

ax2.plot(X,C, color='blue', linestyle='-', linewidth='2', label="Cos wave")
ax2.grid(True)
ax2.margins(0.2)

ax1.legend()
ax2.legend()


# In[9]:


# creating a figure
plt.figure(figsize=(12,6), dpi=120)
f, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, sharex=True, sharey=True)

ax1.plot(X,S, color='green', linestyle='--', linewidth='2', label="Sin wave")
ax1.grid(True)
ax1.margins(0.2)

ax2.plot(X,C, color='blue', linestyle='-', linewidth='2', label="Cos wave")
ax2.grid(True)
ax2.margins(0.2)

ax1.legend()
ax1.set_xlabel("X data")
ax1.set_ylabel("Sin data")
ax1.set_title("Sin Chart")

ax2.legend()
ax2.set_xlabel("X data")
ax2.set_ylabel("Sin data")
ax2.set_title("Cos Chart")


# ** Adding some samples plots **

# In[10]:


fig = plt.figure(figsize=(16,12))
plt.subplots(nrows=3, ncols=4)
plt.show()


# In[11]:


fig = plt.figure(figsize=(8,6))
ax1 = plt.subplot(1,2,1)
plt.subplot(3,2,2)
plt.subplot(3,2,4)
plt.subplot(3,2,6)
ax1.plot([1,2,3], [0.5,4,1.5])
plt.show()


# In[12]:


X = [ (2,1,1), (2,3,4), (2,3,5), (2,3,6) ]
for nrows, ncols, plot_number in X:
    plt.subplot(nrows, ncols, plot_number)


# In[13]:


# removing all ticks

X = [ (2,1,1), (2,3,4), (2,3,5), (2,3,6) ]
for nrows, ncols, plot_number in X:
    plt.subplot(nrows, ncols, plot_number)
    plt.xticks([])
    plt.yticks([])


# In[14]:


# removing all ticks

X = [ (1,2,1), (3,2,2), (3,2,4), (3,2,6) ]
for nrows, ncols, plot_number in X:
    plt.subplot(nrows, ncols, plot_number)
    plt.xticks([])
    plt.yticks([])


# In[15]:


# removing all ticks

X = [ (4,2,1), (4,2,3), (4,2,5), (4,1,4), (4,2,2), (4,2,(4,6)) ]
for nrows, ncols, plot_number in X:
    plt.subplot(nrows, ncols, plot_number)
    plt.xticks([])
    plt.yticks([])


# ** Setting the Plot Range ** 

# In[16]:


fig, axes = plt.subplots(1, 3, figsize=(10, 4))
x = np.arange(0, 5, 0.25)
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");


# In[20]:


fig, ax1 = plt.subplots()
x = np.arange(1,7,0.1)
ax1.plot(x, 2 * np.pi * x, lw=2, color="blue")
ax1.set_ylabel(r"Circumference $(cm)$", fontsize=16, color="blue")
for label in ax1.get_yticklabels():
    label.set_color("blue")
    
ax2 = ax1.twinx()
ax2.plot(x, np.pi * x ** 2, lw=2, color="darkgreen")
ax2.set_ylabel(r"area $(cm^2)$", fontsize=16, color="darkgreen")
for label in ax2.get_yticklabels():
    label.set_color("darkgreen")
    
#plt.grid(color='b', alpha=1.5, linestyle='dashed', linewidth=0.5)


# In[18]:


fig.savefig("filename.png", dpi=200)


# In[24]:


def f(t):
    return np.exp(-t) * np.cos(2*np.pi*t)
def fp(t):
    return -2*np.pi * np.exp(-t) * np.sin(2*np.pi*t) - np.e**(-t)*np.cos(2*np.pi*t)
def g(t):
    return np.sin(t) * np.cos(1/(t+0.1))
def g(t):
    return np.sin(t) * np.cos(1/(t))
python_course_green = "#476042"
fig = plt.figure(figsize=(6, 4))
t = np.arange(-5.0, 1.0, 0.1)
sub1 = fig.add_subplot(221) # instead of plt.subplot(2, 2, 1)
sub1.set_title('The function f') # non OOP: plt.title('The function f')
sub1.plot(t, f(t))
sub2 = fig.add_subplot(222, axisbg="lightgrey")
sub2.set_title('fp, the derivation of f')
sub2.plot(t, fp(t))
t = np.arange(-3.0, 2.0, 0.02)
sub3 = fig.add_subplot(223)
sub3.set_title('The function g')
sub3.plot(t, g(t))
t = np.arange(-0.2, 0.2, 0.001)
sub4 = fig.add_subplot(224, axisbg="lightgrey")
sub4.set_title('A closer look at g')
sub4.set_xticks([-0.2, -0.1, 0, 0.1, 0.2])
sub4.set_yticks([-0.15, -0.1, 0, 0.1, 0.15])
sub4.plot(t, g(t))
plt.plot(t, g(t))
plt.tight_layout()
plt.show()


# In[ ]: