#!/usr/bin/python
from pychartdir import *
import cgi
# Get HTTP query parameters
query = cgi.FieldStorage()
#
# In this demo, the generated web page needs to load the "cdjcv.js" Javascript file and several GIF
# files. For ease of installation, we put these files in the same directory as this script. However,
# if this script is installed in a CGI only directory (such as cgi-bin), the web server would not
# allow the browser to access these non-CGI files.
#
# To get around this potential issue, a special load resource script is used to load these files.
# Instead of using:
#
# <SCRIPT SRC="cdjcv.js">
#
# we now use:
#
# <SCRIPT SRC="loadresource.py?file=cdjcv.js">
#
# Similar methods are used to load the GIF files.
#
# If this script is not in a CGI only directory, you may replace the following loadResource string
# with an empty string "" to improve performance.
#
loadResource = "loadresource.py?file="
#
# Initialize the WebChartViewer when the page is first loaded
#
def initViewer(viewer) :
# The full x-axis range is from Jan 1, 2007 to Jan 1, 2012
startDate = chartTime(2007, 1, 1)
endDate = chartTime(2012, 1, 1)
viewer.setFullRange("x", startDate, endDate)
# Initialize the view port to show the last 366 days (out of 1826 days)
viewer.setViewPortWidth(366.0 / 1826)
viewer.setViewPortLeft(1 - viewer.getViewPortWidth())
# Set the maximum zoom to 10 days (out of 1826 days)
viewer.setZoomInWidthLimit(10.0 / 1826)
#
# Draw the chart
#
def drawChart(viewer) :
# Determine the visible x-axis range
viewPortStartDate = viewer.getValueAtViewPort("x", viewer.getViewPortLeft())
viewPortEndDate = viewer.getValueAtViewPort("x", viewer.getViewPortLeft(
) + viewer.getViewPortWidth())
# We need to get the data within the visible x-axis range. In real code, this can be by using a
# database query or some other means as specific to the application. In this demo, we just
# generate a random data table, and then select the data within the table.
# Generate the random data table
r = RanTable(127, 4, 1828)
r.setDateCol(0, chartTime(2007, 1, 1), 86400)
r.setCol(1, 150, -10, 10)
r.setCol(2, 200, -10, 10)
r.setCol(3, 250, -8, 8)
# Select the data for the visible date range viewPortStartDate to viewPortEndDate. It is
# possible there is no data point at exactly viewPortStartDate or viewPortEndDate. In this case,
# we also need the data points that are just outside the visible date range to "overdraw" the
# line a little bit (the "overdrawn" part will be clipped to the plot area) In this demo, we do
# this by adding a one day margin to the date range when selecting the data.
r.selectDate(0, viewPortStartDate - 86400, viewPortEndDate + 86400)
# The selected data from the random data table
timeStamps = r.getCol(0)
dataSeriesA = r.getCol(1)
dataSeriesB = r.getCol(2)
dataSeriesC = r.getCol(3)
#
# Now we have obtained the data, we can plot the chart.
#
#================================================================================
# Configure overall chart appearance.
#================================================================================
# Create an XYChart object 600 x 300 pixels in size, with pale blue (f0f0ff) background, black
# (000000) rounded border, 1 pixel raised effect.
c = XYChart(600, 300, 0xf0f0ff, 0x000000)
c.setRoundedFrame()
# Set the plotarea at (52, 60) and of size 520 x 205 pixels. Use white (ffffff) background.
# Enable both horizontal and vertical grids by setting their colors to grey (cccccc). Set
# clipping mode to clip the data lines to the plot area.
c.setPlotArea(55, 60, 520, 205, 0xffffff, -1, -1, 0xcccccc, 0xcccccc)
# As the data can lie outside the plotarea in a zoomed chart, we need to enable clipping.
c.setClipping()
# Add a top title to the chart using 15 pts Times New Roman Bold Italic font, with a light blue
# (ccccff) background, black (000000) border, and a glass like raised effect.
c.addTitle("Product Line International Market Price", "timesbi.ttf", 15).setBackground(0xccccff,
0x000000, glassEffect())
# Add a legend box at the top of the plot area with 9pts Arial Bold font with flow layout.
c.addLegend(50, 33, 0, "arialbd.ttf", 9).setBackground(Transparent, Transparent)
# Set axes width to 2 pixels
c.xAxis().setWidth(2)
c.yAxis().setWidth(2)
# Add a title to the y-axis
c.yAxis().setTitle("Price (USD)", "arialbd.ttf", 10)
#================================================================================
# Add data to chart
#================================================================================
#
# In this example, we represent the data by lines. You may modify the code below to use other
# representations (areas, scatter plot, etc).
#
# Add a line layer for the lines, using a line width of 2 pixels
layer = c.addLineLayer2()
layer.setLineWidth(2)
# In this demo, we do not have too many data points. In real code, the chart may contain a lot
# of data points when fully zoomed out - much more than the number of horizontal pixels in this
# plot area. So it is a good idea to use fast line mode.
layer.setFastLineMode()
# Now we add the 3 data series to a line layer, using the color red (ff0000), green (00cc00) and
# blue (0000ff)
layer.setXData(timeStamps)
layer.addDataSet(dataSeriesA, 0xff0000, "Product Alpha")
layer.addDataSet(dataSeriesB, 0x00cc00, "Product Beta")
layer.addDataSet(dataSeriesC, 0x0000ff, "Product Gamma")
#================================================================================
# Configure axis scale and labelling
#================================================================================
# Set the x-axis as a date/time axis with the scale according to the view port x range.
viewer.syncDateAxisWithViewPort("x", c.xAxis())
# In this demo, we rely on ChartDirector to auto-label the axis. We ask ChartDirector to ensure
# the x-axis labels are at least 75 pixels apart to avoid too many labels.
c.xAxis().setTickDensity(75)
#================================================================================
# Output the chart
#================================================================================
# Output the chart
chartQuery = c.makeTmpFile("/tmp/tmpcharts")
# Include tool tip for the chart
imageMap = c.getHTMLImageMap("", "", "title='[{dataSetName}] {x|mmm dd, yyyy}: USD {value|2}'")
# Set the chart URL, image map and chart metrics to the viewer
viewer.setImageUrl("getchart.py?img=/tmp/tmpcharts/" + chartQuery)
viewer.setImageMap(imageMap)
viewer.setChartMetrics(c.getChartMetrics())
#
# This script handles both the full page request, as well as the subsequent partial updates (AJAX
# chart updates). We need to determine the type of request first before we processing it.
#
# Create the WebChartViewer object
viewer = WebChartViewer(query, "chart1")
if viewer.isPartialUpdateRequest() :
# Is a partial update request. Draw the chart and perform a partial response.
drawChart(viewer)
binaryPrint(viewer.partialUpdateChart())
sys.exit()
#
# If the code reaches here, it is a full page request.
#
# In this exapmle, we just need to initialize the WebChartViewer and draw the chart.
initViewer(viewer)
drawChart(viewer)
print("Content-type: text/html\n")
print("""
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html>
<head>
<title>Simple Zooming and Scrolling</title>
<script type="text/javascript" src="%(loadResource)scdjcv.js"></script>
</head>
<body style="margin:0px;">
<script type="text/javascript">
//
// Execute the following initialization code after the web page is loaded
//
JsChartViewer.addEventListener(window, 'load', function() {
// Update the chart when the view port has changed (eg. when the user zooms in using the mouse)
var viewer = JsChartViewer.get('%(id)s');
viewer.attachHandler("ViewPortChanged", viewer.partialUpdate);
// Set the initial mouse usage to "scroll"
viewer.setMouseUsage(JsChartViewer.Scroll);
document.getElementById("scrollChart").checked = true;
});
</script>
<form method="post">
<table cellspacing="0" cellpadding="0" border="0">
<tr>
<td align="right" colspan="2" style="background:#000088">
<div style="padding:0px 3px 2px 0px; font:italic bold 10pt Arial;">
<a style="color:#FFFF00; text-decoration:none" href="http://www.advsofteng.com/">Advanced Software Engineering</a>
</div>
</td>
</tr>
<tr valign="top">
<td style="width:127px; background:#c0c0ff; border-right:black 1px solid; border-bottom:black 1px solid;">
<div style="font:9pt Verdana; padding:10px 0px 0px 3px; line-height:1.5; width:127px">
<!-- The onclick handler of the following radio buttons sets the mouse usage mode. -->
<input name="mouseUsage" id="scrollChart" type="radio"
onclick="JsChartViewer.get('%(id)s').setMouseUsage(JsChartViewer.Scroll)" />
Drag To Scroll<br />
<input name="mouseUsage" id="zoomInChart" type="radio"
onclick="JsChartViewer.get('%(id)s').setMouseUsage(JsChartViewer.ZoomIn)" />
Zoom In<br />
<input name="mouseUsage" id="zoomOutChart" type="radio"
onclick="JsChartViewer.get('%(id)s').setMouseUsage(JsChartViewer.ZoomOut)" />
Zoom Out<br />
</div>
</td>
<td>
<div style="font-weight:bold; font-size:20pt; margin:5px 0px 0px 5px; font-family:Arial">
Simple Zooming and Scrolling
</div>
<hr style="border:solid 1px #000080" />
<div style="padding:0px 5px 5px 10px">
<!-- ****** Here is the chart image ****** -->
%(chartImg)s
</div>
</td>
</tr>
</table>
</form>
</body>
</html>
""" % {
"loadResource" : loadResource,
"id" : viewer.getId(),
"chartImg" : viewer.renderHTML()
}) |