Array type validator

qcodes/tests/test_validators.py

@@ -1,9 +1,10 @@
 from unittest import TestCase
 import math
-import numpy 
+import numpy as np
 
 from qcodes.utils.validators import (Validator, Anything, Bool, Strings,
-                                     Numbers, Ints, Enum, MultiType)
+                                     Numbers, Ints, Enum, MultiType,
+                                     Arrays)
 
 
 class AClass:
@@ -177,7 +178,7 @@ class TestNumbers(TestCase):
                # warning: +/- inf are allowed if max & min are not specified!
                -float("inf"), float("inf"),
                 # numpy scalars
-               numpy.int64(36), numpy.float32(-1.123)
+               np.int64(36), np.float32(-1.123)
                 ]
     not_numbers = ['', None, '1', [], {}, [1, 2], {1: 1},
                    b'good', AClass, AClass(), a_func]
@@ -269,8 +270,8 @@ class TestInts(TestCase):
             # warning: True==1 and False==0 - we *could* prohibit these, using
             # isinstance(v, bool)
             True, False,
-            # numpy scalars
-            numpy.int64(3)]
+            # np scalars
+            np.int64(3)]
     not_ints = [0.1, -0.1, 1.0, 3.5, -2.3e6, 5.5e15, 1.34e-10, -2.5e-5,
                 math.pi, math.e, '', None, float("nan"), float("inf"),
                 -float("inf"), '1', [], {}, [1, 2], {1: 1}, b'good',
@@ -402,3 +403,44 @@ def test_bad(self):
         for args in [[], [1], [Strings(), True]]:
             with self.assertRaises(TypeError):
                 MultiType(*args)
+
+
+class TestArrays(TestCase):
+    def test_type(self):
+        m = Arrays(min_value=0.0, max_value=3.2, shape=(2, 2))
+        for v in ['somestring', 4, 2, [[2, 0], [1, 2]]]:
+            with self.assertRaises(TypeError):
+                m.validate(v)
+
+    def test_min_max(self):
+        m = Arrays(min_value=-5, max_value=50, shape=(2, 2))
+        v = np.random.rand(2, 2)
+        m.validate(v)
+        v = 100*v
+        with self.assertRaises(ValueError):
+            m.validate(v)
+        v = -1*v
+        with self.assertRaises(ValueError):
+            m.validate(v)
+
+        v = np.random.rand(3, 2)
+        with self.assertRaises(ValueError):
+            m.validate(v)
+
+    def test_shape(self):
+        m = Arrays(min_value=-5, max_value=50, shape=(2, 2))
+        v = np.random.rand(2, 2)
+        m.validate(v)
+        v = np.random.rand(3, 2)
+        with self.assertRaises(ValueError):
+            m.validate(v)
+
+        # should pass if no shape specified
+        m = Arrays(min_value=-5, max_value=50)
+        v = np.random.rand(2, 2)
+        m.validate(v)
+        v = np.random.rand(3, 2)
+        m.validate(v)
+
+
+

qcodes/utils/validators.py

@@ -1,5 +1,5 @@
 import math
-import numpy
+import numpy as np
 
 BIGSTRING = 1000000000
 BIGINT = int(1e18)
@@ -140,7 +140,7 @@ class Numbers(Validator):
         - fix raises
     """
 
-    validtypes = (float, int, numpy.integer, numpy.floating)
+    validtypes = (float, int, np.integer, np.floating)
 
     def __init__(self, min_value=-float("inf"), max_value=float("inf")):
 
@@ -180,7 +180,7 @@ class Ints(Validator):
     min_value <= value <= max_value
     """
 
-    validtypes = (int, numpy.integer)
+    validtypes = (int, np.integer)
 
     def __init__(self, min_value=-BIGINT, max_value=BIGINT):
         if isinstance(min_value, self.validtypes):
@@ -294,3 +294,59 @@ def validate(self, value, context=''):
     def __repr__(self):
         parts = (repr(v)[1:-1] for v in self._validators)
         return '<MultiType: {}>'.format(', '.join(parts))
+
+
+class Arrays(Validator):
+    """
+    Validator for numerical numpy arrays
+    Args:
+        min_value (Optional[Union[float, int]):  Min value allowed, default inf
+        max_value:  (Optional[Union[float, int]): Max  value allowed, default inf
+        shape:     (Optional): None
+    """
+
+    validtypes = (int, float, np.integer, np.floating)
+
+    def __init__(self, min_value=-float("inf"), max_value=float("inf"),
+                 shape=None):
+
+        if isinstance(min_value, self.validtypes):
+            self._min_value = min_value
+        else:
+            raise TypeError('min_value must be a number')
+
+        if isinstance(max_value, self.validtypes) and max_value > min_value:
+            self._max_value = max_value
+        else:
+            raise TypeError('max_value must be a number bigger than min_value')
+        self._shape = shape
+
+    def validate(self, value, context=''):
+
+        if not isinstance(value, np.ndarray):
+            raise TypeError(
+                '{} is not a numpy array; {}'.format(repr(value), context))
+
+        if value.dtype not in self.validtypes:
+            raise TypeError(
+                '{} is not an int or float; {}'.format(repr(value), context))
+        if self._shape != None:
+            if (np.shape(value) != self._shape):
+                raise ValueError(
+                    '{} does not have expected shape {}; {}'.format(
+                            repr(value), self._shape, context))
+
+        if not (self._min_value <= np.min(value) and
+                np.max(value) <= self._max_value):
+            raise ValueError(
+                '{} is invalid: all values must be between '
+                '{} and {} inclusive; {}'.format(
+                    repr(value), self._min_value, self._max_value, context))
+
+    is_numeric = True
+
+    def __repr__(self):
+        minv = self._min_value if math.isfinite(self._min_value) else None
+        maxv = self._max_value if math.isfinite(self._max_value) else None
+        return '<Arrays{}, shape: {}>'.format(range_str(minv, maxv, 'v'), self._shape)
+