Generates Axis with values from start to stop inclusive.
355518
public static Axis generateAxisFromRange(float start, float stop, float step) {

        List<AxisValue> values = new ArrayList<AxisValue>();
        for (float value = start; value <= stop; value += step) {
            AxisValue axisValue = new AxisValue(value);
            values.add(axisValue);
        }

        Axis axis = new Axis(values);
        return axis;
    }
582252
def __map_axis(self, axis):
        """"""
        start_code, start_value = axis
        value = start_value
        code = self.manager.codes['xpad'][start_code]
        return code, value
1234163
def mad(self,x, axis=None):
        """"""
        return np.median(np.abs(x - np.median(x, axis)), axis)
574321
def values(self, axis=None):
        
        if axis is None:
            return self._plot
        else:
            return [value.get(axis) for value in self._plot]
799170
function () {

    if (!this.used) return;

    var axis  = this,
      o       = axis.options,
      min     = o.min !== null ? o.min : axis.datamin,
      max     = o.max !== null ? o.max : axis.datamax,
      margin  = o.autoscaleMargin;
        
    if (o.scaling == 'logarithmic') {
      if (min <= 0) min = axis.datamin;

      // Let it widen later on
      if (max <= 0) max = min;
    }

    if (max == min) {
      var widen = max ? 0.01 : 1.00;
      if (o.min === null) min -= widen;
      if (o.max === null) max += widen;
    }

    if (o.scaling === 'logarithmic') {
      if (min < 0) min = max / o.base;  // Could be the result of widening

      var maxexp = Math.log(max);
      if (o.base != Math.E) maxexp /= Math.log(o.base);
      maxexp = Math.ceil(maxexp);

      var minexp = Math.log(min);
      if (o.base != Math.E) minexp /= Math.log(o.base);
      minexp = Math.ceil(minexp);
      
      axis.tickSize = Flotr.getTickSize(o.noTicks, minexp, maxexp, o.tickDecimals === null ? 0 : o.tickDecimals);
                        
      // Try to determine a suitable amount of miniticks based on the length of a decade
      if (o.minorTickFreq === null) {
        if (maxexp - minexp > 10)
          o.minorTickFreq = 0;
        else if (maxexp - minexp > 5)
          o.minorTickFreq = 2;
        else
          o.minorTickFreq = 5;
      }
    } else {
      axis.tickSize = Flotr.getTickSize(o.noTicks, min, max, o.tickDecimals);
    }

    axis.min = min;
    axis.max = max; //extendRange may use axis.min or axis.max, so it should be set before it is caled

    // Autoscaling. @todo This probably fails with log scale. Find a testcase and fix it
    if(o.min === null && o.autoscale){
      axis.min -= axis.tickSize * margin;
      // Make sure we don't go below zero if all values are positive.
      if(axis.min < 0 && axis.datamin >= 0) axis.min = 0;
      axis.min = axis.tickSize * Math.floor(axis.min / axis.tickSize);
    }
    
    if(o.max === null && o.autoscale){
      axis.max += axis.tickSize * margin;
      if(axis.max > 0 && axis.datamax <= 0 && axis.datamax != axis.datamin) axis.max = 0;        
      axis.max = axis.tickSize * Math.ceil(axis.max / axis.tickSize);
    }

    if (axis.min == axis.max) axis.max = axis.min + 1;
  }
1070760
function(axis) {
				if(!s.backAnimStarted[axis]) {
					s.speedDecelerationRatio[axis] = s.speedDecelerationRatio[axis] * (s.slowDownRatio[axis] + 
												s.slowDownRatioReverse[axis] - 
												s.slowDownRatioReverse[axis] * s.timeDiff / 10);

					s.speedDecelerationRatioAbs[axis] = Math.abs(s.lastFlickSpeed[axis] * s.speedDecelerationRatio[axis]);
					s.distanceOffset[axis] = s.lastFlickSpeed[axis] * s.speedDecelerationRatio[axis] * s.timeDiff;
					_panOffset[axis] += s.distanceOffset[axis];

				}
			}
857843
def range(self, axis=None):
        
        return (self.min(axis=axis), self.max(axis=axis))
624815
def plot_metrics(self, skip_start:int=0, skip_end:int=0, return_fig:bool=None)->Optional[plt.Figure]:
        ""
        assert len(self.metrics) != 0, "There are no metrics to plot."
        fig, axes = plt.subplots(len(self.metrics[0]),1,figsize=(6, 4*len(self.metrics[0])))
        val_iter = self._split_list_val(np.cumsum(self.nb_batches), skip_start, skip_end)
        axes = axes.flatten() if len(self.metrics[0]) != 1 else [axes]
        for i, ax in enumerate(axes):
            values = [met[i] for met in self.metrics]
            values = self._split_list_val(values, skip_start, skip_end)
            ax.plot(val_iter, values)
            ax.set_ylabel(str(self.metrics_names[i]))
            ax.set_xlabel('Batches processed')             
        if ifnone(return_fig, defaults.return_fig): return fig
        if not IN_NOTEBOOK: plot_sixel(fig)
1329509
function ( axis, startX, startY, endX, endY ) {
        var result = 'none';

        if ( axis == 'horizontal' ) {
            if ( startX > endX ) {
                result = 'left';
            } else if ( startX < endX ) {
                result = 'right';
            }
        } else {
            if ( startY > endY ) {
                result = 'top';
            } else if ( startY < endY ) {
                result = 'bottom';
            }
        }

        return result;
    }
368284
def axis(self):
        """"""
        return getattr(
            self.colorbar.ax, self.axis_locations[self.position] + 'axis')
282889
function () {
		var axis = this,
			chart = axis.chart,
			pointer = chart.pointer;

		// hide tooltip and hover states
		if (pointer.reset) {
			pointer.reset(true);
		}

		// render the axis
		axis.render();

		// move plot lines and bands
		each(axis.plotLinesAndBands, function (plotLine) {
			plotLine.render();
		});

		// mark associated series as dirty and ready for redraw
		each(axis.series, function (series) {
			series.isDirty = true;
		});

	}
705382
def formatted_values(self):
        
        return self._df.apply(lambda x: self.formatters[x["type"]](x["value"]),axis=1)
25405
def _xxrange(self, start, end, step_count):
        """"""
        _step = (end - start) / float(step_count)
        return (start + (i * _step) for i in xrange(int(step_count)))
561028
def process_values(self):
        """"""

        if self.padding>0:
            channels = np.zeros((self.vals.shape[0], self.vals.shape[1]+self.padding))
            channels[:, 0:self.vals.shape[0]] = self.vals
        else:
            channels = self.vals
        vals_mat = self.skel.to_xyz(channels.flatten())
        self.vals = np.zeros_like(vals_mat)
        # Flip the Y and Z axes
        self.vals[:, 0] = vals_mat[:, 0].copy()
        self.vals[:, 1] = vals_mat[:, 2].copy()
        self.vals[:, 2] = vals_mat[:, 1].copy()
1244548
def slicesum(self, start, stop=None, axis=0):
        """"""
        return self.slice(start, stop, axis).sum(axis)
149142
def _set_axis_limits(self, axis, view, subplots, ranges):
        
        # Extents
        extents = self.get_extents(view, ranges)
        if not extents or self.overlaid:
            axis.autoscale_view(scalex=True, scaley=True)
            return

        valid_lim = lambda c: util.isnumeric(c) and not np.isnan(c)
        coords = [coord if np.isreal(coord) or isinstance(coord, np.datetime64) else np.NaN for coord in extents]
        coords = [date2num(util.dt64_to_dt(c)) if isinstance(c, np.datetime64) else c
                  for c in coords]
        if self.projection == '3d' or len(extents) == 6:
            l, b, zmin, r, t, zmax = coords
            if self.invert_zaxis or any(p.invert_zaxis for p in subplots):
                zmin, zmax = zmax, zmin
            if zmin != zmax:
                if valid_lim(zmin):
                    axis.set_zlim(bottom=zmin)
                if valid_lim(zmax):
                    axis.set_zlim(top=zmax)
        else:
            l, b, r, t = coords

        if self.invert_axes:
            l, b, r, t = b, l, t, r

        invertx = self.invert_xaxis or any(p.invert_xaxis for p in subplots)
        xlim, scalex = self._compute_limits(l, r, self.logx, invertx, 'left', 'right')
        inverty = self.invert_yaxis or any(p.invert_yaxis for p in subplots)
        ylim, scaley =  self._compute_limits(b, t, self.logy, inverty, 'bottom', 'top')
        if xlim:
            axis.set_xlim(**xlim)
        if ylim:
            axis.set_ylim(**ylim)
        axis.autoscale_view(scalex=scalex, scaley=scaley)
1162485
def axes(value):
        
        for i, entry in enumerate(value):
            _assert_is_type('axes[{0}]'.format(i), entry, Axis)