Boavizta#214 add rounding based on min and max

This function should be used when the API returns a value with an
associated min and max value. The rounding depends on the delta
betwwen min and max

boaviztapi/utils/roundit.py

@@ -30,6 +30,39 @@ def min_significant_figures(*inputs):
     return sigfig if sigfig > config['min_significant_figures'] else config['min_significant_figures']
 
 
+def round_based_on_min_max(val, min_val, max_val, precision):
+    """
+    Returns a rounded values for `val`.
+
+    The rounding depends on the difference betwwen `min_val` and `max-val`. 
+    The bigger the difference, the more agressive the rounding.
+
+    The precision is a % used to round the value.
+
+    """
+    if precision == 0:
+        raise ValueError("Invalid precision value, cannot be 0%")
+    if max_val < min_val:
+        raise ValueError("round_based_on_min_max : min must be less than max")
+
+    # value for approx% of the min max delta
+    approx = (max_val - min_val) / (100/precision)
+    if approx == 0:
+        return val
+    significant = math.floor(math.log10(approx))
+
+    # Mathematically, these two calculation should be equivalent, but
+    # dividing by very small number and multiplying by very large number
+    # cause issues with floats.
+    # We avoid these issues by inverting operation based on the sign of significant
+    if significant > 0:
+        rounded = round(val / 10 ** significant) * 10**significant
+    else:
+        rounded = round(val / 10 ** significant) / 10**-significant
+
+    return rounded
+
+
 def round_to_sigfig(x, significant_figures):
     """
    returns a float rounded to significant figures
@@ -70,6 +103,7 @@ def remove_unsignificant_zeros(x):
     exponent = -math.log10(divider) + 1
     return float(x * (Decimal(10 ** exponent)))
 
+
 def to_precision(x, p):
     """
     Util function

tests/unit/test_roundit.py

@@ -1,4 +1,5 @@
 import boaviztapi.utils.roundit as rd
+import pytest
 
 
 def test_sigfig_():
@@ -33,3 +34,49 @@ def test_round_to_sigfig():
     assert rd.round_to_sigfig(0.0251, 3) == 0.0251
     # this case is not supported as the return float value is 0.2
     # assert rd.round_to_sigfig(0.202, 2) == '0.20'
+
+
+def test_round_based_on_min_max():
+
+    # high difference between min and max:
+    assert rd.round_based_on_min_max(20.29217, 10.91891, 81.81527, 10) == 20
+    # small difference between min and max:
+    assert rd.round_based_on_min_max(20.29217, 18.91891, 22.81527, 10) == 20.3
+
+    # Different precision:
+    # 10%
+    assert rd.round_based_on_min_max(1.2345, 1.2, 1.3, 10) == 1.23
+    # 1%
+    assert rd.round_based_on_min_max(1.2345, 1.2, 1.3, 1) == 1.234
+
+    # WHen no rounding is requied : 
+    assert rd.round_based_on_min_max(60, 10, 90, 10) == 60
+    assert rd.round_based_on_min_max(60, 10, 90, 1) == 60
+
+    # Various other tests:
+    assert rd.round_based_on_min_max(1.52366871, 1, 2, 1) == 1.52
+    assert rd.round_based_on_min_max(1.52366871, 1, 2, 10) == 1.5
+
+    assert rd.round_based_on_min_max(20.29217, 10.91891, 81.81527, 10) == 20
+    assert rd.round_based_on_min_max(
+        1819.821672, 110.14710120000001, 5419.285269084, 10) == 1800
+    assert rd.round_based_on_min_max(
+        0.02040328338, 0.020400523740000003, 0.02042139678, 10) == 0.020403
+    assert rd.round_based_on_min_max(
+        0.00030760589391948, 0.63406418256e-05, 0.00127183984353, 10) == 0.0003
+    assert rd.round_based_on_min_max(
+        306.0165, 179.92950000000002, 1133.6115, 10) == 310
+    assert rd.round_based_on_min_max(
+        61648.853641199996, 62.2570572, 2241972.40986, 10) == 100000
+
+
+def test_round_based_on_min_max_corner_cases():
+
+    #  min == max : must retun the original value without any rounding
+    assert rd.round_based_on_min_max(1, 1, 1, 1) == 1
+    #  precision == 0 : must raise ValueError
+    with pytest.raises(ValueError) as e:
+        rd.round_based_on_min_max(1, 1, 1, 0)
+    # min > max
+    with pytest.raises(ValueError) as e:
+        rd.round_based_on_min_max(5, 10, 5, 10)