def find_problems(xds_wd):
problems = []
idxref_lp = os.path.join(xds_wd, "IDXREF.LP")
xparm_xds = os.path.join(xds_wd, "XPARM.XDS")
integrate_lp = os.path.join(xds_wd, "INTEGRATE.LP")
correct_lp = os.path.join(xds_wd, "CORRECT.LP")
xdsstat_lp = os.path.join(xds_wd, "XDSSTAT.LP")
if os.path.isfile(idxref_lp):
idexref_has_problem = False
lp = idxreflp.IdxrefLp(idxref_lp)
intness = lp.cluster_integerness()
for h in intness:
if sum(h) > 0 and h[0] / sum(h) < 0.9:
idexref_has_problem = True
if len(lp.subtree_population) > 0:
pp0 = float(lp.subtree_population[0]) / sum(lp.subtree_population)
if pp0 < 0.9: idexref_has_problem = True
else:
idexref_has_problem = True
if not os.path.isfile(xparm_xds): idexref_has_problem = True
if idexref_has_problem:
problems.append("IDXREF")
if os.path.isfile(integrate_lp):
lp = integratelp.IntegrateLp(integrate_lp)
if any(map(lambda x: float(x) > 1.5, lp.sigmars)):
problems.append("INTEGRATE")
if os.path.isfile(correct_lp):
lp = correctlp.CorrectLp(correct_lp)
if not lp.is_ISa_valid() or lp.get_ISa() < 10:
problems.append("CORRECT")
if os.path.isfile(xdsstat_lp):
lp = xdsstat.XdsstatLp(xdsstat_lp)
return problems
def run(params, out=sys.stdout):
cm = CellGraph(tol_length=params.tol_length, tol_angle=params.tol_angle)
if not params.xdsdir and params.topdir:
params.xdsdir = map(
lambda x: x[0],
filter(
lambda x: any(
map(lambda y: y.startswith("XDS_ASCII.HKL"), x[2])) or
"DIALS.HKL" in x[2], os.walk(params.topdir)))
for i, xdsdir in enumerate(params.xdsdir):
cm.add_proc_result(i, xdsdir)
cm.group_xds_results(out)
ret = cm.grouped_dirs
if len(ret) == 0:
return cm
print >> out
print >> out, "About the largest group:"
for idx, wd in enumerate(ret[0]):
xac_hkl = os.path.join(wd, "XDS_ASCII.HKL")
correct_lp = os.path.join(wd, "CORRECT.LP")
print >> out, "%.3d %s" % (idx, os.path.relpath(wd, params.topdir)
if params.topdir is not None else wd),
if not os.path.isfile(xac_hkl):
print >> out, "Unsuccessful"
continue
sg = XDS_ASCII(xac_hkl, read_data=False).symm.space_group_info()
clp = correctlp.CorrectLp(correct_lp)
if "all" in clp.table:
cmpl = clp.table["all"]["cmpl"][-1]
else:
cmpl = float("nan")
ISa = clp.a_b_ISa[-1]
print >> out, "%10s ISa=%5.2f Cmpl=%5.1f " % (sg, ISa, cmpl)
if params.do_pointless:
worker = pointless.Pointless()
files = map(lambda x: os.path.join(x, "INTEGRATE.HKL"), ret[0])
#print files
files = filter(lambda x: os.path.isfile(x), files)
print >> out, "\nRunning pointless for the largest member."
result = worker.run_for_symm(xdsin=files,
logout="pointless.log",
tolerance=10,
d_min=5)
if "symm" in result:
print >> out, " pointless suggested", result[
"symm"].space_group_info()
if 0:
import pylab
pos = nx.spring_layout(G)
#pos = nx.spectral_layout(G)
#pos = nx.circular_layout(G)
#nx.draw_networkx_nodes(G, pos, node_size = 100, nodelist=others, node_color = 'w')
nx.draw_networkx_nodes(G, pos, node_size=100, node_color='w')
nx.draw_networkx_edges(G, pos, width=1)
nx.draw_networkx_labels(G,
pos,
font_size=12,
font_family='sans-serif',
font_color='r')
pylab.xticks([])
pylab.yticks([])
pylab.savefig("network.png")
pylab.show()
return cm
def run(params, out=sys.stdout):
cm = CheckMulti(topdir=params.topdir, xdsdirs=params.xdsdir, out=out)
cm.get_symms_from_xds_results()
cm.construct_graph(params.tol_length, params.tol_angle)
cm.group_xds_results()
print
ret = cm.grouped_dirs
if len(ret) == 0:
return cm
print >> out
print >> out, "About the largest group:"
for idx, wd in enumerate(ret[0]):
gxparm_xds = os.path.join(wd, "GXPARM.XDS")
correct_lp = os.path.join(wd, "CORRECT.LP")
print >> out, "%.3d %s" % (idx, os.path.relpath(wd, params.topdir)
if params.topdir is not None else wd),
if not os.path.isfile(gxparm_xds):
print >> out, "Unsuccessful"
continue
sg = sgtbx.space_group_info(XPARM(gxparm_xds).spacegroup)
clp = correctlp.CorrectLp(correct_lp)
if "all" in clp.table:
cmpl = clp.table["all"]["cmpl"][-1]
else:
cmpl = float("nan")
ISa = clp.a_b_ISa[-1]
print >> out, "%10s ISa=%5.2f Cmpl=%5.1f " % (sg, ISa, cmpl)
if params.do_pointless:
worker = Pointless()
files = map(lambda x: os.path.join(x, "INTEGRATE.HKL"), ret[0])
#print files
files = filter(lambda x: os.path.isfile(x), files)
print >> out, "\nRunning pointless for the largest member."
result = worker.run_for_symm(xdsin=files,
logout="pointless.log",
tolerance=10,
d_min=5)
if "symm" in result:
print >> out, " pointless suggested", result[
"symm"].space_group_info()
if 0:
import pylab
pos = nx.spring_layout(G)
#pos = nx.spectral_layout(G)
#pos = nx.circular_layout(G)
#nx.draw_networkx_nodes(G, pos, node_size = 100, nodelist=others, node_color = 'w')
nx.draw_networkx_nodes(G, pos, node_size=100, node_color='w')
nx.draw_networkx_edges(G, pos, width=1)
nx.draw_networkx_labels(G,
pos,
font_size=12,
font_family='sans-serif',
font_color='r')
pylab.xticks([])
pylab.yticks([])
pylab.savefig("network.png")
pylab.show()
return cm
def make_individual_report(xds_wd, html_wd):
problems = []
xds_inp = os.path.join(xds_wd, "XDS.INP")
idxref_lp = os.path.join(xds_wd, "IDXREF.LP")
xparm_xds = os.path.join(xds_wd, "XPARM.XDS")
spot_xds = os.path.join(xds_wd, "SPOT.XDS")
integrate_lp = os.path.join(xds_wd, "INTEGRATE.LP")
correct_lp = os.path.join(xds_wd, "CORRECT.LP")
xdsstat_lp = os.path.join(xds_wd, "XDSSTAT.LP")
stats_pkl = os.path.join(xds_wd, "merging_stats.pkl")
shika_log = os.path.join(xds_wd, "shika.log")
if not os.path.exists(html_wd):
os.makedirs(html_wd)
html = """\
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<script src="%(amcharts_root)s/amcharts.js" charset="utf-8"></script>
<script src="%(amcharts_root)s/serial.js" charset="utf-8"></script>
<script src="%(amcharts_root)s/xy.js" charset="utf-8"></script>
</head>
<body>
<h1>%(title)s</h1>
created on %(cdate)s
""" % dict(title=os.path.abspath(xds_wd),
cdate=time.strftime("%Y-%m-%d %H:%M:%S"),
amcharts_root=amcharts_root)
if os.path.isfile(shika_log):
lines = open(shika_log).readlines()
if len(lines) > 1:
data = map(lambda x: (x.split()[0], x.split()[2]), lines[1:])
html += "<h1>Low resolution spots</h1>\n"
html += """\
<div id="chartdiv_shika" style="width: 640px; height: 400px;"></div>
<script>
var chart_idxref_ibf = AmCharts.makeChart("chartdiv_shika", {
"type": "serial",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"stackType": "regular",
"gridAlpha": 0.07,
"position": "left",
"title": "Number of located spots by SHIKA"
}],
"graphs": [{
"balloonText": "n_spots: [[value]]",
"fillAlphas": 0.6,
"lineAlpha": 0.4,
"title": "number of spots",
"valueField": "nspt"
}],
"chartCursor": {
"cursorPosition": "mouse"
},
"categoryField": "frame",
"categoryAxis": {
"minorGridEnabled": true,
"title": "frame"
}
});
</script>
""" % (",".join(map(lambda x: '{"frame": %s, "nspt": %s}' % x, data)), )
html += "<h1>IDXREF (Indexing)</h1>\n"
if os.path.isfile(idxref_lp):
SX = idxreflp.SpotXds(spot_xds)
if os.path.isfile(xparm_xds): SX.set_xparm(xparm_xds)
else: SX.set_xdsinp(xds_inp)
i_ui_on_det = SX.indexed_and_unindexed_on_detector(
with_resolution=True)
html += """\
<h3>Indexed/Unindexed spots</h3>
<h4>by frame</h4>
<div id="chartdiv_idxref_indexed_by_frame" style="width: 640px; height: 400px;"></div>
<script>
var chart_idxref_ibf = AmCharts.makeChart("chartdiv_idxref_indexed_by_frame", {
"type": "serial",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"stackType": "regular",
"gridAlpha": 0.07,
"position": "left",
"title": "Number of located spots"
}],
"graphs": [{
"balloonText": "indexed: [[value]]",
"fillAlphas": 0.6,
"lineAlpha": 0.4,
"title": "Indexed spots",
"valueField": "ind"
}, {
"balloonText": "unindexed: [[value]]",
"fillAlphas": 0.6,
"lineAlpha": 0.4,
"title": "Unindexed spots",
"valueField": "und"
}],
"chartCursor": {
"cursorPosition": "mouse"
},
"categoryField": "frame",
"categoryAxis": {
"minorGridEnabled": true,
"title": "frame"
}
});
</script>
<h4>on detector surface</h4>
<div id="chartdiv_idxref_indexed_on_det" style="width: 640px; height: 640px;"></div>
<script>
var chart_idxref_iod = AmCharts.makeChart("chartdiv_idxref_indexed_on_det", {
"type": "xy",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"position":"bottom",
"axisAlpha": 0,
"dashLength": 1,
"title": "Detector X"
}, {
"axisAlpha": 0,
"dashLength": 1,
"position": "left",
"title": "Detector Y"
}],
"graphs": [{
"balloonText": "x:[[x]] y:[[y]]; d=[[description]]",
"bullet": "round",
"bulletSize": 4,
"lineAlpha": 0,
"xField": "ix",
"yField": "iy",
"descriptionField": "d",
"title": "Indexed spots",
"hidden": true,
"lineColor": "#FF6600",
"fillAlphas": 0
}, {
"balloonText": "x:[[x]] y:[[y]]; d=[[description]]",
"bullet": "round",
"bulletSize": 4,
"lineAlpha": 0,
"xField": "ux",
"yField": "uy",
"descriptionField": "d",
"title": "Unindexed spots",
"hidden": true,
"lineColor": "#FCD202",
"fillAlphas": 0
}],
"chartCursor": {
"cursorPosition": "mouse"
},
});
</script>
""" % (
",".join(
map(
lambda x: '{"frame": %d, "ind": %s, "und": %s}' %
(x[0], x[1][0], x[1][1]),
SX.indexed_and_unindexed_by_frame())),
",".join(
map(lambda x: '{"ix":%.1f,"iy":%.1f,"d":%.1f}' % x,
i_ui_on_det["indexed"]) +
map(lambda x: '{"ux":%.1f,"uy":%.1f,"d":%.1f}' % x,
i_ui_on_det["unindexed"])),
)
idexref_has_problem = False
lp = idxreflp.IdxrefLp(idxref_lp)
intness = lp.cluster_integerness()
for h in intness:
if sum(h) > 0 and h[0] / sum(h) < 0.9:
idexref_has_problem = True
html += "<h3>Clusters and subtrees</h3>"
html += """
<h4>Cluster integerness</h4>
<div id="chartdiv_idxref_cluster_int" style="width: 640px; height: 400px;"></div>
<script>
var chart_idxref_cluster_int = AmCharts.makeChart("chartdiv_idxref_cluster_int", {
"type": "serial",
"categoryField": "f",
"categoryAxis": {
"gridPosition": "start",
"position": "left",
"title": "fractional part of indices",
},
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"graphs": [{
"balloonText": "h: [[value]]",
"fillAlphas": 0.8,
"lineAlpha": 0.2,
"title": "h",
"type": "column",
"valueField": "h"
}, {
"balloonText": "k: [[value]]",
"fillAlphas": 0.8,
"lineAlpha": 0.2,
"title": "k",
"type": "column",
"valueField": "k"
}, {
"balloonText": "l: [[value]]",
"fillAlphas": 0.8,
"lineAlpha": 0.2,
"title": "l",
"type": "column",
"valueField": "l"
}
],
"guides": [],
"valueAxes": [
{
"position": "top",
"axisAlpha": 0,
"title": "frequency"
}
],
});
</script>
""" % (",".join(
map(
lambda x: '{"f":.%d,"h":%d,"k":%d,"l":%d}' % x,
map(
lambda x: tuple([
x,
] + map(lambda y: intness[y][x], xrange(3))), xrange(6)))))
html += "<h4>Subtree populations</h4>\n<pre>"
accum_pop = 0
for i, pp in enumerate(
map(lambda x: float(x) / sum(lp.subtree_population),
lp.subtree_population)):
html += "%s subtree: %.2f%%\n" % (util.num_th_str(i + 1),
pp * 100.)
if i == 0 and pp < 0.9: idexref_has_problem = True
accum_pop += pp
if accum_pop > 0.9:
break
html += "</pre>"
if not os.path.isfile(xparm_xds): idexref_has_problem = True
if idexref_has_problem:
problems.append("IDXREF")
html += "<h1>INTEGRATE (Integration)</h1>\n"
if os.path.isfile(integrate_lp):
lp = integratelp.IntegrateLp(integrate_lp)
if any(map(lambda x: float(x) > 1.5, lp.sigmars)):
problems.append("INTEGRATE")
html += """\
<h3>Mosaicity and beam divergence</h3>
<div id="chartdiv_integrate_sigmas" style="width: 640px; height: 400px;"></div>
<h3>rotations off from initial orientation</h3>
<div id="chartdiv_integrate_rotxyz" style="width: 640px; height: 400px;"></div>
<script>
var chart1 = AmCharts.makeChart("chartdiv_integrate_sigmas", {
"type": "serial",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"id":"v1",
"axisColor": "#FF6600",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "left"
}, {
"id":"v2",
"axisColor": "#FCD202",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "right"
}],
"graphs": [{
"balloonText": "σ<sub>R</sub>: [[value]]",
"valueAxis": "v1",
"lineColor": "#FF6600",
"bullet": "round",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "mosaicity",
"valueField": "sigmar",
"fillAlphas": 0
}, {
"balloonText": "σ<sub>B</sub>: [[value]]",
"valueAxis": "v2",
"lineColor": "#FCD202",
"bullet": "square",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "beam divergence",
"valueField": "sigmad",
"fillAlphas": 0
}],
"chartCursor": {
"cursorPosition": "mouse"
},
"categoryField": "frame",
"categoryAxis": {
"minorGridEnabled": true,
"title": "frame"
}
});
var chart2 = AmCharts.makeChart("chartdiv_integrate_rotxyz", {
"type": "serial",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"id":"v1",
"axisColor": "#FF6600",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "left"
}],
"graphs": [{
"valueAxis": "v1",
"lineColor": "#FF6600",
"bullet": "round",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "rot x",
"valueField": "rotx",
"fillAlphas": 0
}, {
"valueAxis": "v2",
"lineColor": "#FCD202",
"bullet": "square",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "rot y",
"valueField": "roty",
"fillAlphas": 0
}, {
"valueAxis": "v3",
"lineColor": "#B0DE09",
"bullet": "triangleUp",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "rot z",
"valueField": "rotz",
"fillAlphas": 0
}],
"chartCursor": {
"cursorPosition": "mouse"
},
"categoryField": "frame",
"categoryAxis": {
"minorGridEnabled": true,
"title": "frame"
}
});
</script>
""" % (
",".join(
map(lambda x: '{"frame": %d, "sigmar": %s, "sigmad": %s}' % x,
zip(lp.frames, lp.sigmars, lp.sigmads))),
",".join(
map(
lambda x: ",".join(
map(
lambda y:
'{"frame": %d, "rotx": %s, "roty": %s, "rotz": %s}'
% ((y, ) + tuple(x[1].get("rotation", ["NaN"] * 3))
), x[0])), lp.blockparams.items())),
)
html += "<h1>CORRECT (Scaling)</h1>\n"
if os.path.isfile(correct_lp):
lp = correctlp.CorrectLp(correct_lp)
if not lp.is_ISa_valid() or lp.get_ISa() < 10:
problems.append("CORRECT")
html += """\
<table border=0 cellpadding=5 style="text-align:right;">
<tr><th>Space group</th><td colspan=6 style="text-align:left;">%(sg)s</td></tr>
""" % dict( #sgstr=lp.space_group.info(), sgnum=lp.space_group.type().number(),
sg=lp.space_group.info().symbol_and_number()
if lp.space_group is not None else "n/a")
if lp.unit_cell is not None:
html += """\
<tr><th>Unit cell</th><td>%(a).3f</td><td>%(b).3f</td><td>%(c).3f</td><td>%(alpha).3f</td><td>%(beta).3f</td><td>%(gamma).3f</td></tr>
<tr><th>e. s. d.</th><td>%(a_e).3f</td><td>%(b_e).3f</td><td>%(c_e).3f</td><td>%(alpha_e).3f</td><td>%(beta_e).3f</td><td>%(gamma_e).3f</td></tr>
</table>
""" % dict(
a=lp.unit_cell[0],
b=lp.unit_cell[1],
c=lp.unit_cell[2],
alpha=lp.unit_cell[3],
beta=lp.unit_cell[4],
gamma=lp.unit_cell[5],
a_e=lp.unit_cell_esd[0],
b_e=lp.unit_cell_esd[1],
c_e=lp.unit_cell_esd[2],
alpha_e=lp.unit_cell_esd[3],
beta_e=lp.unit_cell_esd[4],
gamma_e=lp.unit_cell_esd[5],
)
else: # in case parameter refinement failed
html += """\
<tr><th>Unit cell</th><td colspan=6>n/a</td></tr>
<tr><th>e. s. d.</th><td colspan=6>n/a</td></tr>
</table>
"""
html += "<h3>ISa</h3>\n<pre>%s</pre>\n" % lp.snippets.get("ISa", "")
html += "<h3>Statistics of all data</h3>\n"
if os.path.isfile(stats_pkl):
sio = StringIO.StringIO()
pickle.load(open(stats_pkl))["stats"].show(out=sio, header=False)
html += "<pre>%s</pre>\n" % sio.getvalue().replace(
"<", "<").replace(">", ">")
else:
html += "<pre>%s</pre>\n" % lp.snippets.get("table1", "")
if lp.error_table != {}:
tmp = map(
lambda x: '{"d":%.3f,"ios":%.2f,"nrej":%d}' % x,
zip(lp.error_table["dmin"], lp.error_table["ios"],
lp.error_table["nrej"]))
tmp = tmp[:-1] # last is about all data
html += """\
<h3>By resolution</h3>
<div id="chartdiv_correct_error" style="width: 640px; height: 400px;"></div>
<script>
var chart_correct_er = AmCharts.makeChart("chartdiv_correct_error", {
"type": "serial",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"id":"v1",
"axisColor": "#FF6600",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "left"
}, {
"id":"v2",
"axisColor": "#FCD202",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "right"
}],
"graphs": [{
"balloonText": "Mn(I/sd): [[value]]",
"valueAxis": "v1",
"lineColor": "#FF6600",
"bullet": "round",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "Mean(I/Sigma)",
"valueField": "ios",
"fillAlphas": 0
}, {
"balloonText": "rejected: [[value]]",
"valueAxis": "v2",
"lineColor": "#FCD202",
"bullet": "square",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "Rejected reflections",
"valueField": "nrej",
"fillAlphas": 0
}],
"chartCursor": {
"cursorPosition": "mouse"
},
"categoryField": "d",
"categoryAxis": {
"minorGridEnabled": true,
"title": "resolution"
}
});
</script>
""" % (",".join(tmp))
if os.path.isfile(xdsstat_lp):
lp = xdsstat.XdsstatLp(xdsstat_lp)
if set(("frame", "iobs", "sigma", "ios", "rmeas",
"nmisfits")).issubset(lp.by_frame.keys()):
html += """\
<h3>By frame</h3>
<div id="chartdiv_xdsstat_ios" style="width: 640px; height: 400px;"></div>
<script>
var chart_xdsstat_ios = AmCharts.makeChart("chartdiv_xdsstat_ios", {
"type": "serial",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"id":"v1",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "left"
}, {
"id":"v2",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "right"
}],
"graphs": [{
"balloonText": "Mn(I): [[value]]",
"valueAxis": "v1",
"bullet": "round",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "Mean(I)",
"valueField": "i",
"fillAlphas": 0
}, {
"balloonText": "Mn(sd): [[value]]",
"valueAxis": "v1",
"bullet": "round",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "Mean(Sigma)",
"valueField": "sig",
"fillAlphas": 0
}, {
"balloonText": "Mn(I/sd): [[value]]",
"valueAxis": "v2",
"bullet": "square",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "Mean(I/Sigma)",
"hidden": true,
"valueField": "ios",
"fillAlphas": 0
}],
"chartCursor": {
"cursorPosition": "mouse"
},
"categoryField": "frame",
"categoryAxis": {
"minorGridEnabled": true,
"title": "frame"
}
});
</script>
<div id="chartdiv_xdsstat_r" style="width: 640px; height: 400px;"></div>
<script>
var chart_xdsstat_r = AmCharts.makeChart("chartdiv_xdsstat_r", {
"type": "serial",
"theme": "none",
"legend": {
"useGraphSettings": true
},
"dataProvider": [%s],
"valueAxes": [{
"id":"v1",
"axisColor": "#FF6600",
"axisThickness": 2,
"gridAlpha": 0,
"axisAlpha": 1,
"position": "left"
}, {
"id":"v2",
"axisThickness": 2,
"axisColor": "#FCD202",
"gridAlpha": 0,
"axisAlpha": 1,
"position": "right"
}],
"graphs": [{
"balloonText": "R-meas: [[value]]",
"valueAxis": "v1",
"lineColor": "#FF6600",
"bullet": "round",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "R-meas",
"valueField": "r",
"fillAlphas": 0
}, {
"balloonText": "Misfits: [[value]]",
"valueAxis": "v2",
"lineColor": "#FCD202",
"bullet": "square",
"bulletBorderThickness": 1,
"hideBulletsCount": 30,
"title": "#Misfits",
"valueField": "mis",
"fillAlphas": 0
}],
"chartCursor": {
"cursorPosition": "mouse"
},
"categoryField": "frame",
"categoryAxis": {
"minorGridEnabled": true,
"title": "frame"
}
});
</script>
""" % (",".join(
map(
lambda x: '{"frame":%d,"i":%.2f,"sig":%.2f,"ios":%.2f}' %
x,
zip(lp.by_frame["frame"], lp.by_frame["iobs"],
lp.by_frame["sigma"], lp.by_frame["ios"]))), ",".join(
map(
lambda x: '{"frame":%d,"r":%.4f,"mis":%d}' % x,
zip(lp.by_frame["frame"], lp.by_frame["rmeas"],
lp.by_frame["nmisfits"]))))
html += "</body></html>"
htmlout = os.path.join(html_wd, "report.html")
open(htmlout, "w").write(html)
return htmlout, problems
def run(f):
lp = correctlp.CorrectLp(f)
print lp.snippets["ISa"]
print lp.snippets["table1"]
return lp