show failing and nop symbols

3 files changed, 80 insertions, 15 deletions

diff --git a/bin/analyze-kconfig.py b/bin/analyze-kconfig.py
index ff220b0..444ea2c 100755
--- a/bin/analyze-kconfig.py
+++ b/bin/analyze-kconfig.py
@@ -24,6 +24,16 @@ def main():
         formatter_class=argparse.RawDescriptionHelpFormatter, description=__doc__
     )
     parser.add_argument(
+        "--failing-symbols",
+        action="store_true",
+        help="Show Kconfig symbols related to build failures. Must be used with an experiment result directory.",
+    )
+    parser.add_argument(
+        "--nop-symbols",
+        action="store_true",
+        help="Show Kconfig symbols which are only present in a single configuration. Must be used with an experiment result directory.",
+    )
+    parser.add_argument(
         "--export-tree",
         type=str,
         help="Export decision tree model to file",
@@ -76,6 +86,11 @@ def main():
     if os.path.isdir(args.model):
         data = KConfigAttributes(args.kconfig_path, args.model)
 
+        if args.failing_symbols:
+            show_failing_symbols(data)
+        if args.nop_symbols:
+            show_nop_symbols(data)
+
         if args.sample_size:
             shuffled_data_indices = np.random.permutation(np.arange(len(data.data)))
             sample_indices = shuffled_data_indices[: args.sample_size]
@@ -161,5 +176,40 @@ def main():
                 )
 
 
+def show_failing_symbols(data):
+    for symbol in data.symbol_names:
+        failed_true = len(
+            list(filter(lambda config: config[symbol] == True, data.failures))
+        )
+        failed_false = len(
+            list(filter(lambda config: config[symbol] == False, data.failures))
+        )
+        success_true = len(
+            list(filter(lambda config: config[0][symbol] == True, data.data))
+        )
+        success_false = len(
+            list(filter(lambda config: config[0][symbol] == False, data.data))
+        )
+        if success_false == 0 and failed_false > 0:
+            print(f"Setting {symbol} to n reliably causes the build to fail")
+        if success_true == 0 and failed_true > 0:
+            print(f"Setting {symbol} to y reliably causes the build to fail")
+
+
+def show_nop_symbols(data):
+    for symbol in data.symbol_names:
+        true_count = len(
+            list(filter(lambda config: config[symbol] == True, data.failures))
+        ) + len(list(filter(lambda config: config[0][symbol] == True, data.data)))
+        false_count = len(
+            list(filter(lambda config: config[symbol] == False, data.failures))
+        ) + len(list(filter(lambda config: config[0][symbol] == False, data.data)))
+        if false_count == 0:
+            print(f"Symbol {symbol} is never n")
+        if true_count == 0:
+            print(f"Symbol {symbol} is never y")
+    pass
+
+
 if __name__ == "__main__":
     main()
diff --git a/bin/explore-kconfig.py b/bin/explore-kconfig.py
index 7602076..5b4bdc6 100755
--- a/bin/explore-kconfig.py
+++ b/bin/explore-kconfig.py
@@ -96,12 +96,13 @@ def main():
         for i in range(args.random):
             logging.info(f"Running randconfig {i+1} of {args.random}")
             status = kconf.run_randconfig()
-            if status["success"]:
+            if args.with_neighbourhood and status["success"]:
                 config_filename = status["config_path"]
                 logging.info(f"Exploring neighbourhood of {config_filename}")
                 kconf.run_exploration_from_file(config_filename)
 
     if args.neighbourhood:
+        # TODO also explore range of numeric options
         if os.path.isfile(args.neighbourhood):
             kconf.run_exploration_from_file(args.neighbourhood)
         elif os.path.isdir(args.neighbourhood):
diff --git a/lib/loader.py b/lib/loader.py
index 5e9b20a..a1f9ca6 100644
--- a/lib/loader.py
+++ b/lib/loader.py
@@ -1639,7 +1639,7 @@ class MIMOSA:
 
         :returns: numpy array of mean currents (µA per 10µs)
         """
-        ua_max = 1.836 / self.shunt * 1000000
+        ua_max = 1.836 / self.shunt * 1_000_000
         ua_step = ua_max / 65535
         return charge * ua_step
 
@@ -1694,7 +1694,7 @@ class MIMOSA:
         :param charges: numpy array of charges (pJ per 10µs)
 
         :returns: numpy array of currents (mean µA per 10µs)"""
-        ua_max = 1.836 / self.shunt * 1000000
+        ua_max = 1.836 / self.shunt * 1_000_000
         ua_step = ua_max / 65535
         return charges.astype(np.double) * ua_step
 
@@ -1711,11 +1711,11 @@ class MIMOSA:
         """
         trigidx = []
 
-        if len(triggers) < 1000000:
+        if len(triggers) < 1_000_000:
             self.errors.append("MIMOSA log is too short")
             return trigidx
 
-        prevtrig = triggers[999999]
+        prevtrig = triggers[999_999]
 
         # if the first trigger is high (i.e., trigger/buzzer pin is active before the benchmark starts),
         # something went wrong and are unable to determine when the first
@@ -1735,7 +1735,7 @@ class MIMOSA:
 
         # the device is reset for MIMOSA calibration in the first 10s and may
         # send bogus interrupts -> bogus triggers
-        for i in range(1000000, triggers.shape[0]):
+        for i in range(1_000_000, triggers.shape[0]):
             trig = triggers[i]
             if trig != prevtrig:
                 # Due to MIMOSA's integrate-read-reset cycle, the charge/current
@@ -1758,27 +1758,27 @@ class MIMOSA:
         """
         r1idx = 0
         r2idx = 0
-        ua_r1 = self.voltage / self.r1 * 1000000
+        ua_r1 = self.voltage / self.r1 * 1_000_000
         # first second may be bogus
-        for i in range(100000, len(currents)):
+        for i in range(100_000, len(currents)):
             if r1idx == 0 and currents[i] > ua_r1 * 0.6:
                 r1idx = i
             elif (
                 r1idx != 0
                 and r2idx == 0
-                and i > (r1idx + 180000)
+                and i > (r1idx + 180_000)
                 and currents[i] < ua_r1 * 0.4
             ):
                 r2idx = i
         # 2s disconnected, 2s r1, 2s r2  with r1 < r2  ->  ua_r1 > ua_r2
         # allow 5ms buffer in both directions to account for bouncing relais contacts
         return (
-            r1idx - 180500,
+            r1idx - 180_500,
             r1idx - 500,
             r1idx + 500,
             r2idx - 500,
             r2idx + 500,
-            r2idx + 180500,
+            r2idx + 180_500,
         )
 
     def calibration_function(self, charges, cal_edges):
@@ -1817,8 +1817,8 @@ class MIMOSA:
         cal_r1_mean = np.mean(chg_r1)
         cal_r2_mean = np.mean(chg_r2)
 
-        ua_r1 = self.voltage / self.r1 * 1000000
-        ua_r2 = self.voltage / self.r2 * 1000000
+        ua_r1 = self.voltage / self.r1 * 1_000_000
+        ua_r2 = self.voltage / self.r2 * 1_000_000
 
         if cal_r2_mean > cal_0_mean:
             b_lower = (ua_r2 - 0) / (cal_r2_mean - cal_0_mean)
@@ -1947,11 +1947,14 @@ class MIMOSA:
 class KConfigAttributes:
     def __init__(self, kconfig_path, datadir):
         experiments = list()
+        failed_experiments = list()
         for direntry in os.listdir(datadir):
             config_path = f"{datadir}/{direntry}/.config"
             attr_path = f"{datadir}/{direntry}/attributes.json"
             if os.path.exists(attr_path):
                 experiments.append((config_path, attr_path))
+            elif os.path.exists(config_path):
+                failed_experiments.append(config_path)
 
         kconf = kconfiglib.Kconfig(kconfig_path)
         self.kconf = kconf
@@ -1966,15 +1969,18 @@ class KConfigAttributes:
             )
         )
 
-        self.choice_names = sorted(map(lambda choice: choice.name, kconf.choices))
+        self.choice_names = sorted(
+            map(lambda choice: choice.name or choice.name_and_loc, kconf.choices)
+        )
 
         self.symbol = kconf.syms
         self.choice = dict()
         for choice in kconf.choices:
-            self.choice[choice.name] = choice
+            self.choice[choice.name or choice.name_and_loc] = choice
 
         self.data = list()
         self.configs = list()
+        self.failures = list()
 
         for config_path, attr_path in experiments:
             self.configs.append(config_path)
@@ -1987,3 +1993,11 @@ class KConfigAttributes:
                 if kconf.syms[sym].tri_value == 2:
                     config[sym] = True
             self.data.append((frozendict(config), attr))
+
+        for config_path in failed_experiments:
+            kconf.load_config(config_path)
+            config = dict.fromkeys(self.symbol_names, False)
+            for sym in self.symbol_names:
+                if kconf.syms[sym].tri_value == 2:
+                    config[sym] = True
+            self.failures.append(frozendict(config))