Compute the minimum and maximum.
506783
private void updateMinMax() {
    if(values.length == 0) {
      return; // Keep invalid.
    }
    min = max = values[0];
    for(int i = 1; i < values.length; i++) {
      int v = values[i];
      min = min < v ? min : v;
      max = max > v ? max : v;
    }
  }
109635
private float MIN(float first, float second, float third) {

        float min = Integer.MAX_VALUE;
        if (first < min) {
            min = first;
        }
        if (second < min) {
            min = second;
        }
        if (third < min) {
            min = third;
        }
        return min;
    }
83788
def max_or_none(val1, val2):
    """"""
    return max(val1, val2, key=lambda x: -sys.maxint if x is None else x)
931474
def constrain (n, min, max):

    ''' '''

    if n < min:
        return min
    if n > max:
        return max
    return n
108522
def _min(self, memory, addr, **kwargs):
        
        return memory.state.solver.min(addr, exact=kwargs.pop('exact', self._exact), **kwargs)
862318
def in_range(x: int, minimum: int, maximum: int) -> bool:
    
    return (x >= minimum and x <= maximum)
1043152
def minimum(x1, x2, output_shape=None, name=None):
  
  output_shape = convert_to_shape(output_shape)
  with tf.name_scope(name, default_name="minimum"):
    x1, x2 = binary_arguments_to_tensors(x1, x2)
    return MinMaxOperation(
        tf.minimum, x1, x2, output_shape=_infer_binary_broadcast_shape(
            x1.shape, x2.shape, output_shape)).outputs[0]
377830
def _pre_compute_secondary(self, positive_vals, negative_vals):
        """"""
        self._secondary_min = (
            negative_vals and min(min(negative_vals), self.zero)
        ) or self.zero
        self._secondary_max = (
            positive_vals and max(max(positive_vals), self.zero)
        ) or self.zero
650219
def max_len(iterable, minimum=0):
    
    try:
        result = max(map(len, iterable))
    except ValueError:
        result = minimum
    return minimum if result < minimum else result
196081
def minmax(low, high):
    """"""
    def decorator(function):
        """Decorate a function with args."""
        @functools.wraps(function)
        def wrapper(*args, **kwargs):
            """Wrap the function."""
            series = function(*args, **kwargs)
            lo_pass = low <= series
            hi_pass = series <= high

            return lo_pass & hi_pass

        return wrapper

    return decorator
1018190
def minimum(self):
        
        return min([(x, energy) for _, x, energy, _, _ in self.get_kinks()],
                   key=lambda i: i[1])
36445
def get_minimum_size(self, data):
        """"""
        size = self.element.get_minimum_size(data)
        return datatypes.Point(
            max(size.x, self.min_width),
            max(size.y, self.min_height)
            )
828117
function getMinimum() {
        var args = [];
        for (var _i = 0; _i < arguments.length; _i++) {
            args[_i] = arguments[_i];
        }
        return Math.min.apply(Math, args);
    }
669909
function getMaximum() {
        var args = [];
        for (var _i = 0; _i < arguments.length; _i++) {
            args[_i] = arguments[_i];
        }
        return Math.max.apply(Math, args);
    }
1062413
function (x, min, max) {
    if (x <= min) {
      return 0;
    }
    if (x >= max) {
      return 1;
    }
    x = (x - min) / (max - min);
    return x * x * (3 - 2 * x);
  }
327056
def _compute(self):
        """"""
        if self.xvals:
            xmin = min(self.xvals)
            xmax = max(self.xvals)
            xrng = (xmax - xmin)
        else:
            xrng = None

        if self.yvals:
            ymin = min(min(self.yvals), self.zero)
            ymax = max(max(self.yvals), self.zero)
            yrng = (ymax - ymin)
        else:
            yrng = None

        for serie in self.all_series:
            serie.points = serie.values

        if xrng:
            self._box.xmin, self._box.xmax = xmin, xmax
        if yrng:
            self._box.ymin, self._box.ymax = ymin, ymax

        if self.range and self.range[0] is not None:
            self._box.ymin = self.range[0]

        if self.range and self.range[1] is not None:
            self._box.ymax = self.range[1]
1101354
def min(self, default=None):
        
        return numpy.asscalar(numpy.min(self.values)) if self.values else default