Added comments in Classification relating to its limits. Added to res…

…ources. Added SATOracle file which is simply a copy of a file from the aqua repo, with comments added for clarity

Code/ACQUA/Classification/Classification.py

@@ -13,19 +13,19 @@
 from datasets import *
 
 
-def classify(location='',file='testClassify.csv',class_labels=[r'A', r'B']) :
+def classify(location='',file='testClassify.csv',class_labels=[r'A', r'B'], train_size=200, test_size=50) :
 
     # Title is defined in usedDefinedData function - can edit if needed but that file is from the
     # tutorial
     sample_Total, training_input, test_input, class_labels = userDefinedData(location,
                                                                              file,
                                                                              class_labels,
-                                                                             training_size=200,
-                                                                             test_size=50,
-                                                                             n=2,
+                                                                             training_size=train_size,
+                                                                             test_size=test_size,
+                                                                             n=2, # normally n = 2, but can be bigger - timed out with n = 3
                                                                              PLOT_DATA=True)
 
-    # n = 2 is the dimension of each data pointtotal_array, label_to_labelclass = get_points(test_input, class_labels)
+    # n = 2 is the dimension of each data point
     total_array, label_to_labelclass = get_points(test_input, class_labels)
 
     """
@@ -66,5 +66,8 @@ def classify(location='',file='testClassify.csv',class_labels=[r'A', r'B']) :
 
 # Classifies a much larger dataset of banking data - more attributes and more rows so it takes much longer
 # Trying to estimate based on a phone call if they will stay with the company
-classify(file="bank1000.csv", class_labels=[r'Yes', r'No'])
+# NB trained with 500 and tested with 100 and timed out, also with 400 and 100, and 400 and 50, and 300 and 50.
+# 200 and 50 is fine, but timed out with 250 and 50
+# 200 and 200 is fine - so it depends on the size of the training set
+classify(file="bank1000.csv", class_labels=[r'Yes', r'No'], train_size=200, test_size=50)
 

Code/ACQUA/Classification/data/bankText.csv

@@ -0,0 +1,16 @@
+15,16,"age","job","marital","education","default","balance","housing","loan","contact","day","month","duration","campaign","pdays","previous","poutcome","y"
+30,"unemployed","married","primary","no",1787,"no","no","cellular",19,"oct",79,1,-1,0,"unknown","no"
+33,"services","married","secondary","no",4789,"yes","yes","cellular",11,"may",220,1,339,4,"failure","no"
+35,"management","single","tertiary","no",1350,"yes","no","cellular",16,"apr",185,1,330,1,"failure","no"
+30,"management","married","tertiary","no",1476,"yes","yes","unknown",3,"jun",199,4,-1,0,"unknown","no"
+59,"blue-collar","married","secondary","no",0,"yes","no","unknown",5,"may",226,1,-1,0,"unknown","no"
+35,"management","single","tertiary","no",747,"no","no","cellular",23,"feb",141,2,176,3,"failure","no"
+36,"self-employed","married","tertiary","no",307,"yes","no","cellular",14,"may",341,1,330,2,"other","no"
+39,"technician","married","secondary","no",147,"yes","no","cellular",6,"may",151,2,-1,0,"unknown","no"
+41,"entrepreneur","married","tertiary","no",221,"yes","no","unknown",14,"may",57,2,-1,0,"unknown","no"
+43,"services","married","primary","no",-88,"yes","yes","cellular",17,"apr",313,1,147,2,"failure","no"
+39,"services","married","secondary","no",9374,"yes","no","unknown",20,"may",273,1,-1,0,"unknown","no"
+43,"admin.","married","secondary","no",264,"yes","no","cellular",17,"apr",113,2,-1,0,"unknown","no"
+36,"technician","married","tertiary","no",1109,"no","no","cellular",13,"aug",328,2,-1,0,"unknown","no"
+20,"student","single","secondary","no",502,"no","no","cellular",30,"apr",261,1,-1,0,"unknown","yes"
+31,"blue-collar","married","secondary","no",360,"yes","yes","cellular",29,"jan",89,1,241,1,"failure","no"

Code/ACQUA/Classification/datasets.py

@@ -590,4 +590,3 @@ def userDefinedData(location, file, class_labels,training_size, test_size, n=2,
         plt.show()
 
     return sample_train, training_input, test_input, class_labels
-

Code/Basics/CoinFlip.py

@@ -19,6 +19,7 @@
 
 # Show the results
 print("simulation: ", sim_result)
+print(type(sim_result))
 
 currentMax = 0
 currentVal = 0

Code/Grover/SATOracle.py

@@ -0,0 +1,181 @@
+# -*- coding: utf-8 -*-
+
+# Copyright 2018 IBM.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# =============================================================================
+
+
+
+# THIS IS A DIRECT COPY FROM https://github.com/Qiskit/aqua/blob/2fa314ce9a90a2060404cd5d46f2d45f0806918e/qiskit_aqua/algorithms/components/oracles/sat.py
+# SIMPLY WITH COMMENTS ADDED FOR CLARITY
+
+
+import itertools
+import operator
+import logging
+from qiskit import QuantumRegister, QuantumCircuit
+from qiskit_aqua.algorithms.components.oracles import Oracle
+
+logger = logging.getLogger(__name__)
+
+
+class SAT(Oracle):
+    SAT_CONFIGURATION = {
+        'name': 'SAT',
+        'description': 'Satisfiability Oracle',
+        'input_schema': {
+            '$schema': 'http://json-schema.org/schema#',
+            'id': 'sat_oracle_schema',
+            'type': 'object',
+            'properties': {
+                'cnf': {
+                    'type': 'string',
+                },
+            },
+            'additionalProperties': False
+        }
+    }
+
+    def __init__(self, configuration=None):
+        super().__init__(configuration or self.SAT_CONFIGURATION.copy())
+        self._cnf = None
+        self._qr_ancilla = None
+        self._qr_clause = None
+        self._qr_outcome = None
+        self._qr_variable = None
+
+    def init_args(self, cnf):
+
+        # Remove all comments and blank lines
+        # ls is array of what is left
+        ls = [
+            l.strip() for l in cnf.split('\n')
+            if len(l) > 0 and not l.strip()[0] == 'c'
+        ]
+
+        # Extract the info from the p line
+        headers = [l for l in ls if l[0] == 'p']
+        if len(headers) == 1:
+            p, sig, nv, nc = headers[0].split()
+            assert p == 'p' and sig == 'cnf'
+        else:
+            raise ValueError('Invalid cnf format for SAT.')
+
+        # num variables, num clauses
+        h_nv, h_nc = int(nv), int(nc)
+
+        # Split into arrays of strings, where each string represents a clause, store in overall array
+        cs = [
+            c.strip()
+            for c in ' '.join(
+                [l for l in ls if not l[0] == 'p']
+            ).split(' 0') if len(c) > 0
+        ]
+
+        # Store the cnf as arrays of ints, in an overall array
+        self._cnf = [
+            [int(v) for v in c.split() if not int(v) == 0]
+            for c in cs
+            if (
+                len(c.replace('0', '')) > 0
+            ) and (
+                '0' <= c[0] <= '9' or c[0] == '-'
+            )
+        ]
+
+        # Check that the counts given are correct with what was read
+        nv = max(set([abs(v) for v in list(itertools.chain.from_iterable(self._cnf))]))
+        nc = len(self._cnf)
+        if not h_nv == nv:
+            logger.warning('Inaccurate variable count {} in cnf header, actual count is {}.'.format(h_nv, nv))
+        if not h_nc == nc:
+            logger.warning('Inaccurate clause count {} in cnf header, actual count is {}.'.format(h_nc, nc))
+
+
+        # Initialise registers based on input info
+        self._qr_outcome = QuantumRegister(1, name='o')
+        self._qr_variable = QuantumRegister(nv, name='v')
+        self._qr_clause = QuantumRegister(nc, name='c')
+        num_ancillae = max(max(nc, nv) - 2, 0)
+        if num_ancillae > 0:
+            self._qr_ancilla = QuantumRegister(num_ancillae, name='a')
+
+    def variable_register(self):
+        return self._qr_variable
+
+    def ancillary_register(self):
+        return self._qr_ancilla
+
+    def outcome_register(self):
+        return self._qr_outcome
+
+    def _logic_or(self, circuit, conj_expr, conj_index):
+
+        # get the absolute values - ie turn -1 into 1
+        qs = [abs(v) for v in conj_expr]
+
+        # get the control, ancilla and target bits
+        # NB -1 as variables in CNF must start from 1
+        ctl_bits = [self._qr_variable[idx - 1] for idx in qs]
+        anc_bits = [self._qr_ancilla[idx] for idx in range(len(qs) - 2)]
+        tgt_bits = self._qr_clause[conj_index]
+
+        # Add X gates to all +ve variables
+        for idx in [v for v in conj_expr if v > 0]:
+            circuit.x(self._qr_variable[idx - 1])
+
+        # Add CNOT
+        circuit.cnx(ctl_bits, anc_bits, tgt_bits)
+
+        # Add more X gates to all +ve variables
+        for idx in [v for v in conj_expr if v > 0]:
+            circuit.x(self._qr_variable[idx - 1])
+
+    def construct_circuit(self):
+        # Add all the registers to the circuit
+        if self._qr_ancilla:
+            qc = QuantumCircuit(self._qr_variable, self._qr_clause, self._qr_ancilla, self._qr_outcome)
+        else:
+            qc = QuantumCircuit(self._qr_variable, self._qr_clause, self._qr_outcome)
+
+        # init all clause qubit to 1:
+        qc.x(self._qr_clause)
+
+        # build all clause
+        for conj_index, conj_expr in enumerate(self._cnf):
+            # add a logical or between all the values in that clause
+            self._logic_or(qc, conj_expr, conj_index)
+
+        # keep results
+        qc.cnx(
+            [self._qr_clause[i] for i in range(len(self._qr_clause))],
+            [self._qr_ancilla[i] for i in range(len(self._qr_ancilla))] if self._qr_ancilla else [],
+            self._qr_outcome[0]
+        )
+
+        # reverse, de-entanglement
+        for conj_index, conj_expr in reversed(list(enumerate(self._cnf))):
+            self._logic_or(qc, conj_expr, conj_index)
+        return qc
+
+    def evaluate_classically(self, assignment):
+        assignment_set = set(assignment)
+        for clause in self._cnf:
+            if assignment_set.isdisjoint(clause):
+                return False
+        return True
+
+    def interpret_measurement(self, measurement, *args, **kwargs):
+        top_measurement = max(measurement.items(), key=operator.itemgetter(1))[0]
+        return [(var + 1) * (int(tf) * 2 - 1) for tf, var in zip(top_measurement[::-1], range(len(top_measurement)))]

Code/NoughtAndCrosses/GroverPlayer.py

@@ -52,8 +52,6 @@ def takeTurn(self, board):
             currentConfig += "0"
             currentRules += currentConfig
 
-
-
         newBoard = self.runGrover(currentRules)
 
         return self.convertFromSAT(newBoard, board)

Notes/Resources.md

@@ -1,5 +1,8 @@
 # This file contains a list of useful videos to help you understand quantum
-I would recommend starting by reading through the IBM Q beginners guide, using these videos to support your learning.
+I would recommend starting by reading through the IBM Q beginners guide, using these videos/podcasts to support your learning.
+
+## Introduction
+[](https://soundcloud.com/stupidqubit/001-what-the-photonic-muck-is-a-quantum-computer)
 
 ## Qubits
 [](https://www.youtube.com/watch?v=_P7K8jUbLU0)