# qml.drawer.tape_text¶

tape_text(tape, wire_order=None, show_all_wires=False, decimals=None, max_length=100, show_matrices=False, cache=None)[source]

Text based diagram for a Quantum Tape.

Parameters

tape (QuantumTape) – the operations and measurements to draw

Keyword Arguments
• wire_order (Sequence[Any]) – the order (from top to bottom) to print the wires of the circuit

• show_all_wires (bool) – If True, all wires, including empty wires, are printed.

• decimals (int) – How many decimal points to include when formatting operation parameters. Default None will omit parameters from operation labels.

• max_length (Int) – Maximum length of a individual line. After this length, the diagram will begin anew beneath the previous lines.

• show_matrices=False (bool) – show matrix valued parameters below all circuit diagrams

• cache (dict) – Used to store information between recursive calls. Necessary keys are 'tape_offset' and 'matrices'.

Returns

String based graphic of the circuit.

Return type

str

Example:

with qml.tape.QuantumTape() as tape:
qml.QFT(wires=(0, 1, 2))
qml.RX(1.234, wires=0)
qml.RY(1.234, wires=1)
qml.RZ(1.234, wires=2)
qml.Toffoli(wires=(0, 1, "aux"))

qml.expval(qml.PauliZ("aux"))
qml.var(qml.PauliZ(0) @ qml.PauliZ(1))
qml.probs(wires=(0, 1, 2, "aux"))

>>> print(qml.drawer.tape_text(tape))
0: ─╭QFT──RX─╭●─┤ ╭Var[Z@Z] ╭Probs
1: ─├QFT──RY─├●─┤ ╰Var[Z@Z] ├Probs
2: ─╰QFT──RZ─│──┤           ├Probs
aux: ──────────╰X─┤  <Z>      ╰Probs


By default, parameters are omitted. By specifying the decimals keyword, parameters are displayed to the specified precision. Matrix-valued parameters are never displayed.

>>> print(qml.drawer.tape_text(tape, decimals=2))
0: ─╭QFT──RX(1.23)─╭●─┤ ╭Var[Z@Z] ╭Probs
1: ─├QFT──RY(1.23)─├●─┤ ╰Var[Z@Z] ├Probs
2: ─╰QFT──RZ(1.23)─│──┤           ├Probs
aux: ────────────────╰X─┤  <Z>      ╰Probs


The max_length keyword wraps long circuits:

rng = np.random.default_rng(seed=42)
shape = qml.StronglyEntanglingLayers.shape(n_wires=5, n_layers=5)
params = rng.random(shape)
tape2 = qml.StronglyEntanglingLayers(params, wires=range(5)).expand()
print(qml.drawer.tape_text(tape2, max_length=60))

0: ──Rot─╭●──────────╭X──Rot─╭●───────╭X──Rot──────╭●────╭X
1: ──Rot─╰X─╭●───────│───Rot─│──╭●────│──╭X────Rot─│──╭●─│─
2: ──Rot────╰X─╭●────│───Rot─╰X─│──╭●─│──│─────Rot─│──│──╰●
3: ──Rot───────╰X─╭●─│───Rot────╰X─│──╰●─│─────Rot─╰X─│────
4: ──Rot──────────╰X─╰●──Rot───────╰X────╰●────Rot────╰X───

───Rot───────────╭●─╭X──Rot──────╭●──────────────╭X─┤
──╭X────Rot──────│──╰●─╭X────Rot─╰X───╭●─────────│──┤
──│────╭X────Rot─│─────╰●───╭X────Rot─╰X───╭●────│──┤
──╰●───│─────Rot─│──────────╰●───╭X────Rot─╰X─╭●─│──┤
───────╰●────Rot─╰X──────────────╰●────Rot────╰X─╰●─┤


The wire_order keyword specifies the order of the wires from top to bottom:

>>> print(qml.drawer.tape_text(tape, wire_order=["aux", 2, 1, 0]))
aux: ──────────╭X─┤  <Z>      ╭Probs
2: ─╭QFT──RZ─│──┤           ├Probs
1: ─├QFT──RY─├●─┤ ╭Var[Z@Z] ├Probs
0: ─╰QFT──RX─╰●─┤ ╰Var[Z@Z] ╰Probs


If the wire order contains empty wires, they are only shown if the show_all_wires=True.

>>> print(qml.drawer.tape_text(tape, wire_order=["a", "b", "aux", 0, 1, 2], show_all_wires=True))
a: ─────────────┤
b: ─────────────┤
aux: ──────────╭X─┤  <Z>      ╭Probs
0: ─╭QFT──RX─├●─┤ ╭Var[Z@Z] ├Probs
1: ─├QFT──RY─╰●─┤ ╰Var[Z@Z] ├Probs
2: ─╰QFT──RZ────┤           ╰Probs


Matrix valued parameters are always denoted by M followed by an integer corresponding to unique matrices. The list of unique matrices can be printed at the end of the diagram by selecting show_matrices=True:

with qml.tape.QuantumTape() as tape:
qml.QubitUnitary(np.eye(2), wires=0)
qml.QubitUnitary(np.eye(2), wires=1)
qml.expval(qml.Hermitian(np.eye(4), wires=(0,1)))

>>> print(qml.drawer.tape_text(tape, show_matrices=True))
0: ──U(M0)─┤ ╭<𝓗(M1)>
1: ──U(M0)─┤ ╰<𝓗(M1)>
M0 =
[[1. 0.]
[0. 1.]]
M1 =
[[1. 0. 0. 0.]
[0. 1. 0. 0.]
[0. 0. 1. 0.]
[0. 0. 0. 1.]]


An existing matrix cache can be passed via the cache keyword. Note that the dictionary passed to cache will be modified during execution to contain any new matrices and the tape offset.

>>> cache = {'matrices': [-np.eye(3)]}
>>> print(qml.drawer.tape_text(tape, show_matrices=True, cache=cache))
0: ──U(M1)─┤ ╭<𝓗(M2)>
1: ──U(M1)─┤ ╰<𝓗(M2)>
M0 =
[[-1. -0. -0.]
[-0. -1. -0.]
[-0. -0. -1.]]
M1 =
[[1. 0.]
[0. 1.]]
M2 =
[[1. 0. 0. 0.]
[0. 1. 0. 0.]
[0. 0. 1. 0.]
[0. 0. 0. 1.]]
>>> cache
{'matrices': [tensor([[-1., -0., -0.],
[-0., -1., -0.],
[-0., -0., -1.]], requires_grad=True), tensor([[1., 0.],
[0., 1.]], requires_grad=True), tensor([[1., 0., 0., 0.],
[0., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]], requires_grad=True)], 'tape_offset': 0}


When the provided tape has nested tapes inside, this function is called recursively. To maintain numbering of tapes to arbitrary levels of nesting, the cache keyword uses the "tape_offset" value to determine numbering. Note that the value is updated during the call.

with qml.tape.QuantumTape() as tape:
with qml.tape.QuantumTape() as tape_inner:
qml.PauliX(0)

cache = {'tape_offset': 3}
print(qml.drawer.tape_text(tape, cache=cache))
print("New tape offset: ", cache['tape_offset'])

0: ──Tape:3─┤

Tape:3
0: ──X─┤
New tape offset:  4


Using PennyLane

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