Let metric define the number of quantiles needed

Some metrics have a specific number of quantiles needed (e.g.  -m
spreadskill). The driver will now check that the right number of
quantiles are specified.

verif/driver.py

@@ -556,6 +556,16 @@ def run(argv):
         if quantiles is None:
             quantiles = data.quantiles
             verif.util.warning("Missing '-q <quantiles>'. Automatically setting quantiles: %s" % (','.join(["%g" % q for q in quantiles])))
+
+        # Check that we have the right number of quantiles
+        if m is not None:
+            if m.min_num_thresholds is not None:
+                if len(quantiles) < m.min_num_thresholds:
+                    verif.util.error(f"Need to specify at least {m.min_num_thresholds} quantiles (-q)")
+            if m.max_num_thresholds is not None:
+                if len(quantiles) > m.max_num_thresholds:
+                    verif.util.error(f"Need to specify at most {m.max_num_thresholds} quantiles (-q)")
+
         # TODO: This is a bit of a hack, using thresholds to hold the
         # quantiles. But otherwise, the classes in output need to deal with
         # testing if the metric needs thresholds or quantiles

verif/metric.py

@@ -143,6 +143,8 @@ class Metric(object):
     aggregator = verif.aggregator.Mean()
     supports_aggregator = False
     type = verif.metric_type.Deterministic()
+    min_num_thresholds = None
+    max_num_thresholds = None
 
     def compute(self, data, input_index, axis, interval):
         """ Compute the score along an axis
@@ -1216,6 +1218,8 @@ class QuantileCoverage(Metric):
     # default_bin_type = "within"
     require_threshold_type = "quantile"
     supports_threshold = True
+    min_num_thresholds = 1
+    max_num_thresholds = 2
 
     def compute_single(self, data, input_index, axis, axis_index, interval):
         var0 = verif.field.Quantile(interval.lower)
@@ -1336,6 +1340,8 @@ class Spread(Metric):
     supports_threshold = True
     perfect_score = 0
     orientation = -1
+    min_num_thresholds = 2
+    max_num_thresholds = 2
 
     def compute_single(self, data, input_index, axis, axis_index, interval):
         var0 = verif.field.Quantile(interval.lower)
@@ -1357,6 +1363,8 @@ class SpreadSkillRatio(Metric):
     supports_threshold = True
     perfect_score = 1
     orientation = 0
+    min_num_thresholds = 2
+    max_num_thresholds = 2
 
     def compute_single(self, data, input_index, axis, axis_index, interval):
         var0 = verif.field.Quantile(interval.lower)