sjy-ecos/public/lib/bokeh/js/tree/models/tickers/adaptive_ticker.js

72 lines
2.7 KiB
JavaScript

var AdaptiveTicker, ContinuousTicker, _, argmin, clamp, log, p,
extend = function(child, parent) { for (var key in parent) { if (hasProp.call(parent, key)) child[key] = parent[key]; } function ctor() { this.constructor = child; } ctor.prototype = parent.prototype; child.prototype = new ctor(); child.__super__ = parent.prototype; return child; },
hasProp = {}.hasOwnProperty;
_ = require("underscore");
argmin = require("./util").argmin;
ContinuousTicker = require("./continuous_ticker");
p = require("../../core/properties");
clamp = function(x, min_val, max_val) {
return Math.max(min_val, Math.min(max_val, x));
};
log = function(x, base) {
if (base == null) {
base = Math.E;
}
return Math.log(x) / Math.log(base);
};
AdaptiveTicker = (function(superClass) {
extend(AdaptiveTicker, superClass);
function AdaptiveTicker() {
return AdaptiveTicker.__super__.constructor.apply(this, arguments);
}
AdaptiveTicker.prototype.type = 'AdaptiveTicker';
AdaptiveTicker.define({
base: [p.Number, 10.0],
mantissas: [p.Array, [1, 2, 5]],
min_interval: [p.Number, 0.0],
max_interval: [p.Number]
});
AdaptiveTicker.prototype.initialize = function(attrs, options) {
var prefix_mantissa, suffix_mantissa;
AdaptiveTicker.__super__.initialize.call(this, attrs, options);
prefix_mantissa = _.last(this.get('mantissas')) / this.get('base');
suffix_mantissa = _.first(this.get('mantissas')) * this.get('base');
this.extended_mantissas = _.flatten([prefix_mantissa, this.get('mantissas'), suffix_mantissa]);
return this.base_factor = this.get_min_interval() === 0.0 ? 1.0 : this.get_min_interval();
};
AdaptiveTicker.prototype.get_interval = function(data_low, data_high, desired_n_ticks) {
var best_mantissa, candidate_mantissas, data_range, errors, ideal_interval, ideal_magnitude, ideal_mantissa, interval, interval_exponent;
data_range = data_high - data_low;
ideal_interval = this.get_ideal_interval(data_low, data_high, desired_n_ticks);
interval_exponent = Math.floor(log(ideal_interval / this.base_factor, this.get('base')));
ideal_magnitude = Math.pow(this.get('base'), interval_exponent) * this.base_factor;
ideal_mantissa = ideal_interval / ideal_magnitude;
candidate_mantissas = this.extended_mantissas;
errors = candidate_mantissas.map(function(mantissa) {
return Math.abs(desired_n_ticks - (data_range / (mantissa * ideal_magnitude)));
});
best_mantissa = candidate_mantissas[argmin(errors)];
interval = best_mantissa * ideal_magnitude;
return clamp(interval, this.get_min_interval(), this.get_max_interval());
};
return AdaptiveTicker;
})(ContinuousTicker.Model);
module.exports = {
Model: AdaptiveTicker
};