Module vis: visualization methods for tensors

Package teneva, module vis: visualization methods for tensors.

This module contains the functions for visualization of TT-tensors.

---

teneva.vis.show(Y)

Check and display mode sizes and TT-ranks of the given TT-tensor.

Parameters:

Y (list) – TT-tensor.

Examples:

# 5-dim random TT-tensor with TT-rank 12:
Y = teneva.rand([4]*5, 12)

# Print the resulting TT-tensor:
teneva.show(Y)

# >>> ----------------------------------------
# >>> Output:

# TT-tensor     5D : |4|  |4|  |4|  |4|  |4|
# <rank>  =   12.0 :   \12/ \12/ \12/ \12/
#

# 5-dim random TT-tensor with TT-rank 2:
Y = teneva.rand([2000, 2, 20000, 20, 200], 2)

# Print the resulting TT-tensor:
teneva.show(Y)

# >>> ----------------------------------------
# >>> Output:

# TT-tensor     5D : |2000| |2| |20000| |20| |200|
# <rank>  =    2.0 :      \2/ \2/     \2/  \2/
#

# 5-dim random TT-tensor with TT-rank 122:
Y = teneva.rand([2000, 2, 20000, 20, 200], 122)

# Print the resulting TT-tensor:
teneva.show(Y)

# >>> ----------------------------------------
# >>> Output:

# TT-tensor     5D : |2000|   |2|   |20000|   |20|   |200|
# <rank>  =  122.0 :      \122/ \122/     \122/  \122/
#

# 5-dim random TT-tensor with TT-rank 12:
Y = teneva.rand([2**14]*5, 12)

# Print the resulting TT-tensor:
teneva.show(Y)

# >>> ----------------------------------------
# >>> Output:

# TT-tensor     5D : |16384|  |16384|  |16384|  |16384|  |16384|
# <rank>  =   12.0 :       \12/     \12/     \12/     \12/
#

If an incorrect TT-tensor is passed to the function (the correctness of the shape of all cores is explicitly checked), then an error will be generated:

Y = []

try:
    teneva.show(Y)
except ValueError as e:
    print('Error :', e)

# >>> ----------------------------------------
# >>> Output:

# Error : Invalid TT-tensor
#

Y = [42.]

try:
    teneva.show(Y)
except ValueError as e:
    print('Error :', e)

# >>> ----------------------------------------
# >>> Output:

# Error : Invalid core for TT-tensor
#

Y = [np.zeros((1, 5, 7)), np.zeros((42, 7, 1))]

try:
    teneva.show(Y)
except ValueError as e:
    print('Error :', e)

# >>> ----------------------------------------
# >>> Output:

# Error : Invalid shape of core for TT-tensor
#