Remove f-strings for compatability with python 3 <3.6

.github/workflows/ci.yml

@@ -15,7 +15,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.6, 3.7, 3.8, 3.9]
+        python-version: [3.5, 3.6, 3.7, 3.8, 3.9]
 
     steps:
     - uses: actions/checkout@v2

.github/workflows/wheels.yml

@@ -36,7 +36,7 @@ jobs:
         run: |
           python -m cibuildwheel --output-dir wheelhouse
         env:
-          CIBW_BUILD: "cp36-* cp37-* cp38-* cp39-*"
+          CIBW_BUILD: "cp*-*"
           CIBW_SKIP: "*-win32"
       - uses: actions/upload-artifact@v2
         with:

docs/toric-code-example.ipynb

@@ -187,8 +187,8 @@
       "Simulating L=4...\n",
       "Simulating L=8...\n",
       "Simulating L=12...\n",
-      "CPU times: user 1min 58s, sys: 592 ms, total: 1min 59s\n",
-      "Wall time: 2min 1s\n"
+      "CPU times: user 1min 56s, sys: 589 ms, total: 1min 57s\n",
+      "Wall time: 2min 3s\n"
      ]
     }
    ],
@@ -201,7 +201,7 @@
     "np.random.seed(2)\n",
     "log_errors_all_L = []\n",
     "for L in Ls:\n",
-    "    print(f\"Simulating L={L}...\")\n",
+    "    print(\"Simulating L={}...\".format(L))\n",
     "    Hx = toric_code_x_stabilisers(L)\n",
     "    logX = toric_code_x_logicals(L)\n",
     "    log_errors = []\n",
@@ -242,7 +242,7 @@
     "plt.figure()\n",
     "for L, logical_errors in zip(Ls, log_errors_all_L):\n",
     "    std_err = (logical_errors*(1-logical_errors)/num_trials)**0.5\n",
-    "    plt.errorbar(ps, logical_errors, yerr=std_err, label=f\"L={L}\")\n",
+    "    plt.errorbar(ps, logical_errors, yerr=std_err, label=\"L={}\".format(L))\n",
     "plt.xlabel(\"Physical error rate\")\n",
     "plt.ylabel(\"Logical error rate\")\n",
     "plt.legend(loc=0);"
@@ -311,8 +311,8 @@
       "Simulating L=8...\n",
       "Simulating L=10...\n",
       "Simulating L=12...\n",
-      "CPU times: user 13min 22s, sys: 3.07 s, total: 13min 25s\n",
-      "Wall time: 13min 31s\n"
+      "CPU times: user 13min 40s, sys: 4.17 s, total: 13min 44s\n",
+      "Wall time: 14min 15s\n"
      ]
     }
    ],
@@ -324,7 +324,7 @@
     "ps = np.linspace(0.02, 0.04, 7)\n",
     "log_errors_all_L = []\n",
     "for L in Ls:\n",
-    "    print(f\"Simulating L={L}...\")\n",
+    "    print(\"Simulating L={}...\".format(L))\n",
     "    Hx = toric_code_x_stabilisers(L)\n",
     "    logX = toric_code_x_logicals(L)\n",
     "    log_errors = []\n",
@@ -338,7 +338,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Plotting the results, we find a threshold of around 3%, consistent with the threshold of 2.93% found in [this paper](https://arxiv.org/abs/quant-ph/0207088):"
+    "Plotting the results, we find a threshold of around 3%, consistent with the threshold of 2.9% found in [this paper](https://arxiv.org/abs/quant-ph/0207088):"
    ]
   },
   {
@@ -365,7 +365,7 @@
     "plt.figure()\n",
     "for L, logical_errors in zip(Ls, log_errors_all_L):\n",
     "    std_err = (logical_errors*(1-logical_errors)/num_trials)**0.5\n",
-    "    plt.errorbar(ps, logical_errors, yerr=std_err, label=f\"L={L}\")\n",
+    "    plt.errorbar(ps, logical_errors, yerr=std_err, label=\"L={}\".format(L))\n",
     "plt.yscale(\"log\")\n",
     "plt.xlabel(\"Physical error rate\")\n",
     "plt.ylabel(\"Logical error rate\")\n",

docs/usage.ipynb

@@ -169,7 +169,7 @@
    ],
    "source": [
     "c = m.decode(z)\n",
-    "print(f\"c: {c}, of type {type(c)}\")"
+    "print(\"c: {}, of type {}\".format(c, type(c)))"
    ]
   },
   {

src/pymatching/matching.py

@@ -278,20 +278,20 @@ def decode(self, z, num_neighbours=20, return_weight=False):
             z = np.array(z, dtype=np.uint8)
         except:
             raise ValueError("Syndrome must be of type numpy.ndarray or "\
-                             f"convertible to numpy.ndarray, not {z}")
+                             "convertible to numpy.ndarray, not {}".format(z))
         if len(z.shape) == 1 and (self.num_stabilisers <= z.shape[0]
                 <= self.num_stabilisers+len(self.boundary)):
             defects = z.nonzero()[0]
         elif len(z.shape) == 2 and z.shape[0] == self.num_stabilisers:
             num_stabs = self.stabiliser_graph.get_num_nodes()
             max_num_defects = z.shape[0]*z.shape[1]
             if max_num_defects > num_stabs:
-                raise ValueError(f"Syndrome size {z.shape[0]}x{z.shape[1]} exceeds" \
-                        f" the number of stabilisers ({num_stabs})")
+                raise ValueError("Syndrome size {}x{} exceeds" \
+                        " the number of stabilisers ({})".format(z.shape[0],z.shape[1],num_stabs))
             times, checks = z.T.nonzero()
             defects = times*self.num_stabilisers + checks
         else:
-            raise ValueError(f"The shape ({z.shape}) of the syndrome vector z is not valid.")
+            raise ValueError("The shape ({}) of the syndrome vector z is not valid.".format(z.shape))
         if len(defects) % 2 != 0:
             if len(self.boundary) == 0:
                 raise ValueError("Syndrome must contain an even number of defects "
@@ -409,8 +409,9 @@ def __repr__(self):
         M = self.num_stabilisers
         B = len(self.boundary)
         E = self.stabiliser_graph.get_num_edges()
-        return (f"<pymatching.Matching object with "
-                f"{N} qubit{'s' if N != 1 else ''},"
-                f" {M} stabiliser{'s' if M != 1 else ''}, "
-                f"{B} boundary node{'s' if B != 1 else ''}, and "
-                f"{E} edge{'s' if E != 1 else ''}>")
+        return "<pymatching.Matching object with "\
+                "{} qubit{}, {} stabiliser{}, "\
+                "{} boundary node{}, "\
+                "and {} edge{}>".format(N, 's' if N != 1 else '',
+                    M, 's' if M != 1 else '', B, 's' if B != 1 else '',
+                    E, 's' if E != 1 else '')