aboutsummaryrefslogtreecommitdiff
path: root/wqflask/basicStatistics/updatedBasicStatisticsPage.py
blob: ab7ed07d8fd3d5ae138c4b5fa5f588975994df8e (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
from htmlgen import HTMLgen2 as HT

from base.templatePage import templatePage
from dbFunction import webqtlDatabaseFunction
import BasicStatisticsFunctions

#Window generated from the Trait Data and Analysis page (DataEditingPage.py) with updated stats figures; takes the page's values that can bed edited by the user
class updatedBasicStatisticsPage(templatePage):
	
	plotMinInformative = 4
	
	def __init__(self, fd):	

		templatePage.__init__(self, fd)

		if not fd.genotype:
			fd.readGenotype()
			this_strainlist = fd.strainlist

		if fd.allstrainlist:
			this_strainlist = fd.allstrainlist
			
		fd.readData(this_strainlist)
		
		specialStrains = [] #This appears to be the "other/non-RISet strainlist" without parents/f1 strains; not sure what to name it
		setStrains = []
		for item in this_strainlist:
			if item not in fd.strainlist and item.find('F1') < 0:
				specialStrains.append(item)
			else:
				continue
			
		specialStrains.sort()
		if specialStrains:
			specialStrains = fd.f1list+fd.parlist+specialStrains			

		self.dict['title'] = 'Basic Statistics'
		TD_LR = HT.TD(valign="top",width="100%",bgcolor="#fafafa")

		stats_row = HT.TR()
		stats_cell = HT.TD()
		stats_script = HT.Script(language="Javascript")	

		#Get strain names, values, and variances
		strain_names = fd.formdata.getvalue('strainNames').split(',')
		strain_vals = fd.formdata.getvalue('strainVals').split(',')
		strain_vars = fd.formdata.getvalue('strainVars').split(',')

		vals = []
		if (len(strain_names) > 0):
			if (len(strain_names) > 3):
				#Need to create "vals" object
				for i in range(len(strain_names)):
					try:
						 this_strain_val = float(strain_vals[i])
					except:
						 continue
					try:
						 this_strain_var = float(strain_vars[i])						 
					except:
						 this_strain_var = None
						
					thisValFull = [strain_names[i], this_strain_val, this_strain_var]	
					vals.append(thisValFull)
	
				stats_tab_list = [HT.Href(text="Basic Table", url="#statstabs-1", Class="stats_tab"),HT.Href(text="Probability Plot", url="#statstabs-2", Class="stats_tab"), 
								HT.Href(text="Bar Graph (by name)", url="#statstabs-3", Class="stats_tab"), HT.Href(text="Bar Graph (by rank)", url="#statstabs-4", Class="stats_tab"), 
								HT.Href(text="Box Plot", url="#statstabs-5", Class="stats_tab")]
				stats_tabs = HT.List(stats_tab_list)
				
				stats_container = HT.Div(id="stats_tabs", Class="ui-tabs")
				stats_container.append(stats_tabs)
				
				stats_script_text = """$(function() { $("#stats_tabs").tabs();});""" #Javascript enabling tabs
				
				table_div = HT.Div(id="statstabs-1", style="height:320px;width:740px;overflow:scroll;")
				table_container = HT.Paragraph()	
			
				statsTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
				this_trait_type = fd.formdata.getvalue('trait_type', None)
				this_cellid = fd.formdata.getvalue('cellid', None)
				statsTableCell = BasicStatisticsFunctions.basicStatsTable(vals=vals, trait_type=this_trait_type, cellid=this_cellid)
				statsTable.append(HT.TR(HT.TD(statsTableCell)))
	
				table_container.append(statsTable)
				table_div.append(table_container)
				stats_container.append(table_div)
	
				normalplot_div = HT.Div(id="statstabs-2", style="height:540px;width:740px;overflow:scroll;")
				normalplot_container = HT.Paragraph()
				normalplot = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
				plotTitle = fd.formdata.getvalue("normalPlotTitle","")
				normalplot_img = BasicStatisticsFunctions.plotNormalProbability(vals=vals, RISet=fd.RISet, title=plotTitle, specialStrains=specialStrains)
				normalplot.append(HT.TR(HT.TD(normalplot_img)))
				normalplot.append(HT.TR(HT.TD(HT.BR(),HT.BR(),"This plot evaluates whether data are \
				normally distributed. Different symbols represent different groups.",HT.BR(),HT.BR(),
				"More about ", HT.Href(url="http://en.wikipedia.org/wiki/Normal_probability_plot", 
						target="_blank", text="Normal Probability Plots"), " and more about interpreting these plots from the ", HT.Href(url="/glossary.html#normal_probability", target="_blank", text="glossary"))))				
				normalplot_container.append(normalplot)
				normalplot_div.append(normalplot_container)
				stats_container.append(normalplot_div)
	
				barName_div = HT.Div(id="statstabs-3", style="height:540px;width:740px;overflow:scroll;")
				barName_container = HT.Paragraph()
				barName = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
				barName_img = BasicStatisticsFunctions.plotBarGraph(identification=fd.identification, RISet=fd.RISet, vals=vals, type="name")
				barName.append(HT.TR(HT.TD(barName_img)))		
				barName_container.append(barName)
				barName_div.append(barName_container)
				stats_container.append(barName_div)
	
				barRank_div = HT.Div(id="statstabs-4", style="height:540px;width:740px;overflow:scroll;")
				barRank_container = HT.Paragraph()
				barRank = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
				barRank_img = BasicStatisticsFunctions.plotBarGraph(identification=fd.identification, RISet=fd.RISet, vals=vals, type="rank")
				barRank.append(HT.TR(HT.TD(barRank_img)))	
				barRank_container.append(barRank)
				barRank_div.append(barRank_container)
				stats_container.append(barRank_div)		

				boxplot_div = HT.Div(id="statstabs-5", style="height:540px;width:740px;overflow:scroll;")
				boxplot_container = HT.Paragraph()
				boxplot = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
				boxplot_img, boxplot_link = BasicStatisticsFunctions.plotBoxPlot(vals)
				boxplot.append(HT.TR(HT.TD(boxplot_img, HT.P(), boxplot_link, align="left")))		
				boxplot_container.append(boxplot)
				boxplot_div.append(boxplot_container)
				stats_container.append(boxplot_div)					
	
				stats_cell.append(stats_container)	
				stats_script.append(stats_script_text)
		
				submitTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
				stats_row.append(stats_cell)
				
				submitTable.append(stats_row)
				submitTable.append(stats_script)
		
				TD_LR.append(submitTable)
				self.dict['body'] = str(TD_LR)						
			else:
					heading = "Basic Statistics"
					detail = ['Fewer than %d case data were entered for %s data set. No statitical analysis has been attempted.' % (self.plotMinInformative, fd.RISet)]
					self.error(heading=heading,detail=detail)
					return
		else:
			heading = "Basic Statistics"
			detail = ['Empty data set, please check your data.']
			self.error(heading=heading,detail=detail)
			return