D3中的轴和网格的颜色不同
我想要轴的不同颜色（x和y）和图形的网格。我试过改变CSS但是无法改变它。
我已附上图形代码和css。 css代码在
之下.axis path,
.axis line {
fill: none;
/*stroke: #000;*/
stroke: #B2B2B2;
shape-rendering: crispEdges;
opacity: 0.5;
}
.area_characteristics_temperature {
fill: steelblue;
opacity:0.5;
border: 0px;
margin:0px;
overflow: hidden;
}
.area_characteristics_temperature_3yr {
fill: #7da7ca;
opacity:0.5;
border: 0px;
margin:0px;
overflow: hidden;
}
.area_characteristics_temperature_10yr {
fill: #676767;
opacity:0.5;
border: 0px;
margin:0px;
overflow: hidden;
}
.area_characteristics_temperature_prev {
fill: #eec7ea;
opacity:0.5;
border: 0px;
margin:0px;
overflow: hidden;
}
.line {
fill: transparent;
stroke:red;
stroke-width:3px;
}
.line1 {
fill: transparent;
stroke:green;
stroke-width:3px;
}
.line_characteristics_current_temperature_max{
fill: transparent;
/*stroke:red;*/
stroke:#CC3300;
stroke-width:3px;
}
.line_characteristics_current_temperature_min{
fill: transparent;
/*stroke:yellow;*/
stroke:#0099CC;
stroke-width:3px;
}
.line_characteristics_forecast_temperature_max{
fill: transparent;
/*stroke:green;*/
stroke:#CC3300;
stroke-width:3px;
stroke-height:3px;
/*stroke-dasharray:2.5px,6px;*/
stroke-dasharray:2.5px,5.5px,2.5px,5.5px;
stroke-soft:5px;
stroke-linecap:round;
stroke-height:3px;
stroke-width:3.4px;
}
.line_characteristics_forecast_temperature_min{
fill: transparent;
stroke:#0088C3;
stroke-width:3px;
stroke-height:3px;
/*stroke-dasharray:3px,6px,3px,6px;*/
stroke-dasharray:2.5px,5.5px,2.5px,5.5px;
stroke-soft:5px;
stroke-linecap:round;
stroke-height:3px;
stroke-width:3.4px;
strokeDashoffset:10px,5px;
}
#wgtmsr option{
width:150px;
}
/*<DEMO>*/
#nav {
height:200px;
width:100px;
float:left;
padding:5px;
padding-bottom:50px;
}
#section {
width:350px;
float:left;
padding:10px;
}
/* Main style*/
.widget_sidebar{
min-width: 200px;
max-width:25%;
overflow:hidden;
float:left
}
.widget_graphArea{
min-width: 200px;
max-width:75%;
overflow:hidden;
}
图形代码：我使用D3进行图形编码
var self = this;
this.divID = divID;
this.forecastEnabled = true;
this.currentEnabled = true;
this.averagesEnabled = true;
this.currentData = [];
this.areaClass = "area_characteristics_temperature";
this.averagesData = []
this.forecastdata = new Array();
this.merged_data = new Array();
this.svg = null;
this._currentDataTrail = {temperature_max: 0, temperature_min: 0, date: 0}
this.parseDate = d3.time.format("%Y-%m-%d").parse;
w = $("#" + this.divID).width();
h = $("#" + this.divID).height();
this.boxing = {top: 20, right: 30, bottom: 30, left: 50},
this.width = w - this.boxing.left - this.boxing.right,
this.height = h - this.boxing.top - this.boxing.bottom;
this.x = d3.time.scale()
.range([0, this.width]);
this.y = d3.scale.linear()
.range([this.height, 0]);
this.xAxis = d3.svg.axis()
.scale(this.x)
// .ticks(d3.time.day, 1)
// .tickFormat(d3.time.format('%b %d'))
.orient("bottom");
this.yAxis = d3.svg.axis()
.scale(this.y)
.orient("left")
.ticks(5, 0)
.tickPadding(10);
this.svg = null;
this.line_characteristics = d3.svg.line()
.x(function (d) {
return self.x(d.date);
})
.y(function (d) {
return self.y(d.temperature);
});
this.line_characteristics_temperature_min = d3.svg.line()
.x(function (d) {
return self.x(d.date);
})
.y(function (d) {
return self.y(d.temperature_min);
});
this.line_characteristics_temperature_max = d3.svg.line()
.x(function (d) {
return self.x(d.date);
})
.y(function (d) {
return self.y(d.temperature_max);
});
this.area_characteristics_temperature = d3.svg.area()
.x(function (d) {
return self.x(d.date);
})
.y0(function (d) {
return self.y(d.temperature_max);
})
.y1(function (d) {
return self.y(d.temperature_min);
});
self.updateCurrentData = function (newData, append)
{
var _currentMaxDate = new Date(0);
newData.forEach(function (d) {
d.date = self.parseDate(d.date);
d.temperature_max = d.temperatures.max;
d.temperature_min = d.temperatures.min;
if (d.date > _currentMaxDate) {
_currentMaxDate = d.date;
self._currentDataTrail.temperature_max = d.temperature_max;
self._currentDataTrail.temperature_min = d.temperature_min;
self._currentDataTrail.date = d.date;
}
});
if (append) {
self.currentData = self.currentData.concat(newData);
} else {
self.currentData = newData;
}
self.forecastData = new Array();
self.updateMerged();
};
self.setAreaClass = function (css_class) {
self.areaClass = css_class;
}
self.updateForecastData = function (newData)
{
self.forecastData = new Array();
newData.forEach(function (d) {
d.date = self.parseDate(d.date);
d.temperature_max = d.forecast[0].temperatures.max;
d.temperature_min = d.forecast[0].temperatures.min;
});
if (self._currentDataTrail && self._currentDataTrail.date) {
self.forecastData.push(self._currentDataTrail)
}
self.forecastData = self.forecastData.concat(newData)
self.updateMerged();
};
self.updateAveragesData = function (newData, append)
{
var _temp = new Date();
var current = new Date(_temp.getFullYear(), 0, 1);
newData.forEach(function (d) {
if (d.minTemp) {
current.setDate(current.getDate() + 1);
d.temperature_max = d.maxTemp.average.toFixed(4);
d.temperature_min = d.minTemp.average.toFixed(4);
var date = current.getFullYear() + "-" + d.day;
d.date = self.parseDate(date);
} else {
d.date = self.parseDate(d.date);
d.date.setFullYear(d.date.getFullYear() + 1)
d.temperature_max = d.temperatures.max;
d.temperature_min = d.temperatures.min;
}
});
if (append) {
self.averagesData = self.averagesData.concat(newData);
} else {
self.averagesData = newData;
}
self.updateMerged();
};
self.updateMerged = function ()
{
self.merged_data = new Array();
if (self.currentData != undefined && self.currentData instanceof Array && self.currentData.length > 0 && self.forecastData != undefined && self.forecastData instanceof Array && self.forecastData.length > 0) {
self.merged_data = self.merged_data.concat(self.currentData)
self.merged_data = self.merged_data.concat(self.forecastData)
} else if (self.currentData != undefined && self.currentData instanceof Array && self.currentData.length > 0) {
self.merged_data = self.merged_data.concat(self.currentData);
} else if (self.forecastData != undefined && self.forecastData instanceof Array && self.forecastData.length > 0) {
self.merged_data = self.merged_data.concat(self.forecastData);
}
};
self.redraw = function () {
w = $("#" + self.divID).width();
h = $("#" + self.divID).height();
self.width = w - self.boxing.left - self.boxing.right,
self.height = h - self.boxing.top - self.boxing.bottom;
self.x = d3.time.scale()
.range([0, self.width]);
self.y = d3.scale.linear()
.range([self.height, 0]);
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.day, 1)
.tickFormat(d3.time.format('%b %d'))
.orient("bottom");
self.yAxis = d3.svg.axis()
.scale(self.y)
.orient("left")
.tickSize(-self.width)
.ticks(5, 0)
.tickPadding(10);
if (self.svg !== null) {
self.svg.remove();
}
$("#" + self.divID).html("");
self.svg = d3.select("#" + self.divID).append("svg")
.attr("width", self.width + self.boxing.left + self.boxing.right)
.attr("height", self.height + self.boxing.top + self.boxing.bottom)
.append("g")
.attr("transform", "translate(" + self.boxing.left + "," + self.boxing.top + ")");
var minDate = new Date(2999, 01, 01);
self.merged_data.forEach(function (d) {
if (d.date < minDate) {
minDate = d.date;
}
});
var maxDate = new Date(0);
self.merged_data.forEach(function (d) {
if (d.date > maxDate) {
maxDate = d.date;
}
});
var totalDateDiff = maxDate - minDate;
totalDateDiff = totalDateDiff / (1000 * 60 * 60 * 24);
if (w < 500 && !isNaN(totalDateDiff)) {
if (totalDateDiff < 30) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.days, 7)
.tickFormat(d3.time.format('%b %d'))
.orient("bottom");
} else if (totalDateDiff > 30 && totalDateDiff < 150) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.months)
.tickFormat(d3.time.format('%b %y'))
.orient("bottom");
} else if (totalDateDiff > 150 && totalDateDiff < 365) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.years)
.tickFormat(d3.time.format('%b %y'))
.orient("bottom");
} else if (totalDateDiff > 365) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.years)
.tickFormat(d3.time.format('%Y'))
.orient("bottom");
}
} else if (w > 500 && !isNaN(totalDateDiff)) {
if (totalDateDiff < 15) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.days, 1)
.tickFormat(d3.time.format('%b %d'))
.orient("bottom");
} else if (totalDateDiff > 15 && totalDateDiff <= 30) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.days, 4)
.tickFormat(d3.time.format('%b %d'))
.orient("bottom");
} else if (totalDateDiff > 30 && totalDateDiff < 100) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.months, 1)
.tickFormat(d3.time.format('%b %y'))
.orient("bottom");
} else if (totalDateDiff > 100 && totalDateDiff < 365) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.months)
.tickFormat(d3.time.format('%b %y'))
.orient("bottom");
} else if (totalDateDiff > 365) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.years)
.tickFormat(d3.time.format('%b %Y'))
.orient("bottom");
}
} else if (isNaN(w) || isNaN(totalDateDiff)) {
self.xAxis = d3.svg.axis()
.scale(self.x)
.ticks(d3.time.years)
.tickFormat(d3.time.format('%Y'))
.orient("bottom");
}
self.x.domain(d3.extent(self.merged_data, function (d) {
return d.date;
}));
self.y.domain([d3.min(self.merged_data, function (d) {
return d.temperature_min - 10;
}), d3.max(self.merged_data, function (d) {
return d.temperature_max + 10;
})]);
self.svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + self.height + ")")
.call(self.xAxis.orient("bottom"));
self.svg.append("text")
.attr("x", 0)
.attr("y", self.height)
.style("text-anchor", "middle")
.text("");
self.svg.append("g")
.attr("class", "y axis")
.call(self.yAxis)
.append("text")
.attr("transform", "rotate(-90)")
.attr("x", -85)
.attr("y", 6)
.attr("dy", ".71em")
.style("text-align", "middle")
.text("Temperature(°C)");
self.svg.append("path")
.datum(self.averagesData)
.attr("class", self.areaClass)
.attr("d", self.area_characteristics_temperature);
if (self.currentEnabled === true && self.currentData instanceof Array && self.currentData.length > 0) {
self.svg.append("path")
.datum(self.currentData)
.attr("class", "line_characteristics_current_temperature_max")
.attr("d", self.line_characteristics_temperature_max);
self.svg.append("path")
.datum(self.currentData)
.attr("class", "line_characteristics_current_temperature_min")
.attr("d", self.line_characteristics_temperature_min);
}
if (self.forecastEnabled === true && self.forecastData instanceof Array && self.forecastData.length > 0) {
self.svg.append("path")
.datum(self.forecastData)
.attr("class", "line_characteristics_forecast_temperature_max")
.attr("d", self.line_characteristics_temperature_max)
.style("stroke-dasharray", "2.5,7");
self.svg.append("path")
.datum(self.forecastData)
.attr("class", "line_characteristics_forecast_temperature_min")
.attr("d", self.line_characteristics_temperature_min)
.style("stroke-dasharray", "2.5,7");
}
}
self.showCurrent = function (show)
{
self.currentEnabled = show;
};
self.showForecast = function (show)
{
self.forecastEnabled = show;
};
self.showAverages = function (show)
{
self.averagesEnabled = show;
};
}
1 个答案:
答案 0 :(得分：0)
应用CSS，如下所示。
.axis path, .axis line{
stroke: navy;
fill: none;
}
.y.axis path{
stroke: brown;
fill: none;
}
.y.axis line{
stroke: grey;
opacity: 0.5;
}
相关问题
最新问题
- 我写了这段代码，但我无法理解我的错误
- 我无法从一个代码实例的列表中删除 None 值，但我可以在另一个实例中。为什么它适用于一个细分市场而不适用于另一个细分市场？
- 是否有可能使 loadstring 不可能等于打印？卢阿
- java中的random.expovariate()
- Appscript 通过会议在 Google 日历中发送电子邮件和创建活动
- 为什么我的 Onclick 箭头功能在 React 中不起作用？
- 在此代码中是否有使用“this”的替代方法？
- 在 SQL Server 和 PostgreSQL 上查询，我如何从第一个表获得第二个表的可视化
- 每千个数字得到
- 更新了城市边界 KML 文件的来源？