### axes is an np.array object

fig, axes = plt.subplots(ncols=2,nrows=3, sharex=True, sharey=True)
print(type(axes))
print(axes.shape)
print(axes)

### `aexs.flat`
# `aexs.flat` or `aexs.flatten()`: return a 1-D iterator over the aexs array
a = np.array([[2,3],
              [4,5],
              [6,7]])

print(a) 
print('----------')  

print(a.flat)
print('----------')  

for i in a.flat:
    print(i, end = ',')

## here is the example what axes.flat and axes.flatten() looks like:
fig, axes = plt.subplots(3,2)
axes.flatten()

### `enumerate()`
# enumerate()` # The enumerate() method adds a counter to an iterable and returns it (the enumerate object)
clist = ['b','g','r','c','m','y']
list(enumerate(clist))

### itertools.product()
# The product() method of the itertools module returns the cartesian product of the input iterables.
# import itertools

nrow = 3; ncol = 2
for index, [i,j] in enumerate(itertools.product(range(nrow), range(ncol))):
    print(index)
    print('------')
    
    print(i)
    print('------')
    
    print([i,j])

t = np.arange(0, 10, 0.01)
ax1 = plt.subplot(211)                 # two row, 1 column, and indicate the plot1
ax1.plot(t, np.sin(2*np.pi*t), 'r--')

ax2 = plt.subplot(212, sharex=ax1)     # two row, 1 column, and indicate the plot2
ax2.plot(t/2, np.sin(4*np.pi*t),'g-')

plt.show()

def f(t):
    return np.exp(-t) * np.cos(2*np.pi*t)

t1 = np.arange(0.0, 3.0, 0.01)

ax1 = plt.subplot(212)      # 2 sub-locations (2r X 1c, set ax1 as the the 2nd, the one at the bottom)
ax1.margins(0.05)           # Default margin is 0.05, value 0 means fit
ax1.plot(t1, f(t1), 'r--')

ax2 = plt.subplot(221)      # 4 sub-locations (2r X 2c, set ax2 as the the 1st, the one at the upperleft)
ax2.margins(2, 2)           # Values >0.0 zoom out
ax2.plot(t1, f(t1), 'g-')
ax2.set_title('Zoomed out')

ax3 = plt.subplot(222)      # 4 sub-locations (2r X 2c, set ax3 as the the 2nd, the one at the upperright)
ax3.margins(x=0, y=-0.25)   # Values in (-0.5, 0.0) zooms in to center
ax3.plot(t1, f(t1), 'b--')
ax3.set_title('Zoomed in')

plt.show()

# plt.subplot(nrows, ncols, index) # plot one axes each time, mixed layout is available

# subplot1 with blue
plt.subplot(2,3,1)
plt.plot(x1,y1, c = 'b')
plt.ylabel('v' + '_'+'b')

# subplot2 with green
plt.subplot(2,3,2)
plt.plot(x1,y1, c = 'g')
plt.ylabel('v' + '_'+'g')

# subplot3 with red
plt.subplot(2,3,3)
plt.plot(x1,y1, c = 'r')
plt.ylabel('v' + '_'+'r')

# subplot4 with cyan
plt.subplot(2,3,4)
plt.plot(x1,y1, c = 'c')
plt.ylabel('v' + '_'+'c')

# subplot5 with magenta
plt.subplot(2,3,5)
plt.plot(x1,y1, c = 'm')
plt.ylabel('v' + '_'+'m')

# subplot6 with yellow
plt.subplot(2,3,6)
plt.plot(x1,y1, c = 'y')
plt.ylabel('v' + '_'+'y')

plt.tight_layout()  ### Adjust the padding between and around subplots to avoid the overlap.

# for loop to creating multiple subplots

t = np.arange(0, 10, 0.01)
v = np.sin(2*np.pi*t)

clist = ['b','g','r','c','m','y']
for i in range(len(clist)):
    plt.subplot(2,3,i+1)
    plt.plot(x1,y1, c = clist[i])
    plt.ylabel('v')
    plt.title(str(i) + '_' + clist[i])

plt.tight_layout()  ### Adjust the padding between and around subplots to avoid the overlap.

# for loop and enumerate to creating multiple subplots

clist = ['b','g','r','c','m','y']
for i, col in enumerate(clist):
    plt.subplot(2,3,i+1)
    plt.plot(x1,y1, c = col)
    plt.ylabel('v')
    plt.title(str(i) + '_' + col)

plt.tight_layout()  ### Adjust the padding between and around subplots to avoid the overlap.

# mixed layout is available

# subplot1 with blue, which will located in left half part
plt.subplot(1,2,1)
plt.plot(x1,y1, c = 'b')
plt.ylabel('v' + '_'+'b')

# subplot2 with green, which will located in right upper panel
plt.subplot(2,2,2)
plt.plot(x1,y1, c = 'g')
plt.ylabel('v' + '_'+'g')

# subplot3 with red, , which will located in right lower panel
plt.subplot(2,2,4)
plt.plot(x1,y1, c = 'r')
plt.ylabel('v' + '_'+'r')


plt.tight_layout()  ### Adjust the padding between and around subplots to avoid the overlap.

fig = plt.figure(figsize=(6,6))  ###
ax = fig.subplots(3,3, sharex=True, sharey=True)
ax[0,1].plot([1,2],[1,3])
ax[1,0].plot([1,2],[1,3])
ax[1,1].plot([1,2],[1,3], '--r')
ax[2,2].plot([1,2],[1,3])

plt.tight_layout() 

# for loop, enumerate and axes.flat to creat multi-subplots
clist = ['b','g','r','c','m','y']

fig, axes = plt.subplots(3,2)
for i, ax in enumerate(axes.flat):
    ax.plot(x1,y1,c = clist[i])
    ax.set_title(str(i) + '_' + clist[i])

plt.tight_layout() 

# for loop, enumerate and axes.flat to creat multi-subplots
clist = ['b','g','r','c','m','y']

import itertools
nrow = 3; ncol = 2
fig, axes = plt.subplots(nrow, ncol, sharex = True, sharey = True)

for a, [i,j] in enumerate(itertools.product(range(nrow), range(ncol))):
    axes[i,j].plot(x1,y1, c = clist[a])
    axes[i,j].set_title(str(i) + '_' + clist[a])

plt.tight_layout() 

# for loop, enumerate and axes.flat to creat multi-subplots
clist = ['b','g','r','c','m','y']

nrow = 3, ncol = 2
fig, axes = plt.subplots(nrow, ncol, sharex = True, sharey = True)

for i, j in zip(nrow,ncol):
    ax[i,j].plot(x1,y1, c = clist[i])
    ax.set_title(str(i) + '_' + clist[i])

plt.tight_layout() 

# subplot1 and subplot2 share the same x axis
# subplot3 share the same y axis line with subplot1 and subplot2
fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.3, 0.8, 0.5])  # bottom = ax2 bottom + ax2 height
ax2 = fig.add_axes([0.1, 0.1, 0.8, 0.2])  # [left, bottom, width, height]
ax3 = fig.add_axes([0.9, 0.1, 0.8, 0.7])  # left = ax1/ax2 left + ax1/ax2 width
ax1.plot(x1, y1, linestyle = 'dashed', color = 'r')
ax2.plot(x2, y2,linestyle = '--', color = 'g')
ax3.plot(x1, y2,linestyle = '-', color = 'purple')
plt.show()

fig = plt.figure(figsize=(5,6),facecolor="#9B9B9B") # set backgroud as gray
fig.subplots(2,2) #为了更好地看出axes的效果，这里设置了子区
plt.axes( [0.4,0.4,0.3,0.3], frameon=True, facecolor="r" )

fig = plt.figure(figsize=(4,4),facecolor="#9B9B9B") #背景灰色
fig.subplots(1,2) ##为了更好地看效果，这里设置了子区
fig.add_axes([0.3,0.3, 0.3,0.3], facecolor="red" ) 
plt.axes([0,0,0.3,0.3],facecolor="black")
# 无论是用add_axes还是axes()来添加新坐标轴，它们的执行结果都是一样的。只是add_axes()需要用画布实例fig去调用，不能直接用plt调用。
plt.show()

fig = plt.figure(figsize=(4,4),facecolor="#9B9B9B")
plt.subplot(2,1,1)
fig.add_subplot(1,3,3,facecolor="r")  # `fig.add_subplot` is stackable

fig = plt.figure(figsize=(4,4),facecolor="#9B9B9B")
plt.subplot(2,1,1)
plt.subplot(1,3,3,facecolor="r")   # `plt.subplot` is unstackable
plt.show()

fig = plt.figure()
ax1 = plt.subplot2grid((2,2),(0,0),rowspan=2)
ax2 = plt.subplot2grid((2,2),(1,1))
ax1.plot(x1,y2)
ax2.plot(y1,y2)
plt.show()

# import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(4,4)

ax1 = plt.subplot(gs[1:3,1])
ax2 = plt.subplot(gs[0,3])
ax3 = plt.subplot(gs[0,:3])
ax4 = plt.subplot(gs[3,0:])

# prepare multioanel plot
fig = plt.figure(1, figsize = (5,5))
# remember, grifdpec is rows, then columns
gs = gridspec.GridSpec(15,15)
gs.update(wspace = 1, hspace = 1)  # adjust the space amomg subplots
# Generate main figure
sub1 = fig.add_subplot(gs[2:15, 0:14])
sub2 = fig.add_subplot(gs[1:2, 0:14])
sub3 = fig.add_subplot(gs[0:1, 0:14])
sub4 = fig.add_subplot(gs[2:15, 14:15])
fig.add_axes([0.3,0.3, 0.3,0.3], facecolor="red" ) 
plt.axes([0,0,0.3,0.3],facecolor="black")

fig=plt.figure(1)
ax1=plt.subplot(111)
ax2=ax1.twinx()
ax1.plot(np.arange(1,5),'g--')
ax1.set_ylabel('ax1',color='r')
ax2.plot(np.arange(7,10),'b-')
ax2.set_ylabel('ax2',color='b')
plt.show()

import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(4,4)

ax1 = plt.subplot(gs[1:3,1])
ax2 = plt.subplot(gs[0,3])
ax3 = plt.subplot(gs[0,:3])
ax4 = plt.subplot(gs[3,0:])

import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(4,4)

ax1 = plt.subplot(gs[1:3,1])
ax2 = plt.subplot(gs[0,3])
ax3 = plt.subplot(gs[0,:3])
ax4 = plt.subplot(gs[3,0:])
plt.subplots_adjust(wspace=0.001, hspace=0.5) # adjust the space wspace--> horizontal space, hspace--> vertical space