Improving simulations.py input options

.github/CHANGELOG.md

@@ -2,6 +2,16 @@
 
 ### New features since the last release
 
+* The I/O of frontend `simulations.py` has been improved. The input has been simplified to an intuitive set of `code`, `code_args`, `noise`, and `noise_args`. As long as those combinations are valid, FlamingPy will run simulations and automatically set up the output file based on inputs. [#111](https://github.com/XanaduAI/flamingpy/pull/111) (backward incompatible)
+  * An example run will be 
+    ```
+    python flamingpy/simulations.py -code "SurfaceCode" -code_args "{'distance':3, 'ec':'primal', 'boundaries':'open'}" -noise "CVLayer" -noise_args "{'delta':0.09, 'p_swap':0.25}" -decoder "MWPM" -decoder_args "{'weight_opts':{'method':'blueprint', 'integer':False, 'multiplier':1, 'delta':0.09}}" -trials 100
+    ```
+    which generates
+    ```
+    code,distance,ec,boundaries,noise,delta,p_swap,decoder,weight_opts,errors,trials,current_time,simulation_time,mpi_size
+    SurfaceCode,3,primal,open,CVLayer,0.09,0.25,MWPM,{'method': 'blueprint', 'integer': False, 'multiplier': 1, 'delta': 0.09},10,100,00:15:50,0.370795,1
+    ```
 
 ### Bug fixes
 
@@ -16,6 +26,8 @@
 
 This release contains contributions from (in alphabetical order):
 
+Nariman Saadatmand
+
 See full commit details ...
 
 

flamingpy/_version.py

@@ -14,4 +14,4 @@
 """Version number (major.minor.patch[label])"""
 
 
-__version__ = "0.9.1b0"
+__version__ = "0.9.1b0.dev0"

flamingpy/decoders/decoder.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 """Decoding and recovery functions."""
 
-# pylint: disable=import-outside-toplevel
+# pylint: disable=import-outside-toplevel,too-many-statements
 
 import sys
 import numpy as np
@@ -55,42 +55,44 @@ def assign_weights(code, decoder, **kwargs):
 
     # Blueprint weight assignment or weighted-union-find weight assignment
     # dependent on the type of neighbours.
-    if weight_options.get("method") == "blueprint" and decoder == "MWPM":
-        for node in qubit_coords:
-            neighbors = G[node]
-            # Obtain the list and the number of p-squeezed states in the neighborhood of the node.
-            p_list = [G.nodes[v]["state"] for v in neighbors if G.nodes[v]["state"] == "p"]
-            p_count = len(p_list)
-            if p_count in (0, 1):
-                if weight_options.get("prob_precomputed"):
-                    err_prob = G.nodes[node]["p_phase_cond"]
-                else:
-                    delta_effective = (len(neighbors) + 1) * weight_options.get("delta")
-                    hom_val = G.nodes[node]["hom_val_p"]
-                    err_prob = Z_err_cond(delta_effective, hom_val)
-                # Allow for taking log of 0.
-                err_prob = min(err_prob, 0.5)
-                # TODO: Can I just choose an arbitrary small number?
-                if err_prob == 0:
-                    err_prob = smallest_number
-                if weight_options.get("integer"):
-                    multiplier = weight_options.get("multiplier")
-                    weight = round(-multiplier * np.log(err_prob))
-                else:
-                    weight = -np.log(err_prob)
-                G.nodes[node]["weight"] = weight
-            else:
-                # Dictionary of the form number of swapouts: error probability.
-                weight_dict = {2: 1 / 4, 3: 1 / 3, 4: 2 / 5}
-                err_prob = weight_dict[p_count]
-                if weight_options.get("integer"):
-                    multiplier = weight_options.get("multiplier")
-                    weight = round(-multiplier * np.log(err_prob))
+    if weight_options.get("method") == "blueprint":
+        if decoder == "MWPM":
+            for node in qubit_coords:
+                neighbors = G[node]
+                # Obtain the list and the number of p-squeezed states in
+                # the neighborhood of the node.
+                p_list = [G.nodes[v]["state"] for v in neighbors if G.nodes[v]["state"] == "p"]
+                p_count = len(p_list)
+                if p_count in (0, 1):
+                    if weight_options.get("prob_precomputed"):
+                        err_prob = G.nodes[node]["p_phase_cond"]
+                    else:
+                        delta_effective = (len(neighbors) + 1) * weight_options.get("delta")
+                        hom_val = G.nodes[node]["hom_val_p"]
+                        err_prob = Z_err_cond(delta_effective, hom_val)
+                    # Allow for taking log of 0.
+                    err_prob = min(err_prob, 0.5)
+                    # TODO: Can I just choose an arbitrary small number?
+                    if err_prob == 0:
+                        err_prob = smallest_number
+                    if weight_options.get("integer"):
+                        multiplier = weight_options.get("multiplier")
+                        weight = round(-multiplier * np.log(err_prob))
+                    else:
+                        weight = -np.log(err_prob)
+                    G.nodes[node]["weight"] = weight
                 else:
-                    weight = -np.log(err_prob)
-                G.nodes[node]["weight"] = weight
-        if decoder == "UF":
-            raise Exception("Incompatible decoder/weight options.")
+                    # Dictionary of the form number of swapouts: error probability.
+                    weight_dict = {2: 1 / 4, 3: 1 / 3, 4: 2 / 5}
+                    err_prob = weight_dict[p_count]
+                    if weight_options.get("integer"):
+                        multiplier = weight_options.get("multiplier")
+                        weight = round(-multiplier * np.log(err_prob))
+                    else:
+                        weight = -np.log(err_prob)
+                    G.nodes[node]["weight"] = weight
+        elif decoder == "UF":
+            raise Exception("Incompatible decoder & weight options combination.")
     # Naive weight assignment, unity weights.
     elif weight_options.get("method") == "uniform":
         if decoder == "UF":