Removed the basicStatistics directory/contents because nothing there was being used except corestats, which I moved to utility

Removed box plot code from Plot.py since we no longer use it either

5 files changed, 3 insertions, 347 deletions

diff --git a/wqflask/basicStatistics/BasicStatisticsFunctions.py b/wqflask/basicStatistics/BasicStatisticsFunctions.py
deleted file mode 100644
index 1e5646a1..00000000
--- a/wqflask/basicStatistics/BasicStatisticsFunctions.py
+++ /dev/null
@@ -1,207 +0,0 @@
-from __future__ import print_function
-
-#import string
-from math import *
-#import piddle as pid
-#import os
-import traceback
-
-from pprint import pformat as pf
-
-from corestats import Stats
-
-import reaper
-from htmlgen import HTMLgen2 as HT
-
-#from utility import Plot
-from utility import webqtlUtil
-from base import webqtlConfig
-from db import webqtlDatabaseFunction
-
-def basicStatsTable(vals, trait_type=None, cellid=None, heritability=None):
-    print("basicStatsTable called - len of vals", len(vals))
-    st = {}  # This is the dictionary where we'll put everything for the template
-    valsOnly = []
-    dataXZ = vals[:]
-    for i in range(len(dataXZ)):
-        valsOnly.append(dataXZ[i][1])
-
-    (st['traitmean'],
-     st['traitmedian'],
-     st['traitvar'],
-     st['traitstdev'],
-     st['traitsem'],
-     st['N']) = reaper.anova(valsOnly) #ZS: Should convert this from reaper to R in the future
-
-    #tbl = HT.TableLite(cellpadding=20, cellspacing=0)
-    #dataXZ = vals[:]
-    dataXZ = sorted(vals, webqtlUtil.cmpOrder)
-
-    print("data for stats is:", pf(dataXZ))
-    for num, item in enumerate(dataXZ):
-        print(" %i - %s" % (num, item))
-    print("  length:", len(dataXZ))
-
-    st['min'] = dataXZ[0][1]
-    st['max'] = dataXZ[-1][1]
-
-    numbers = [x[1] for x in dataXZ]
-    stats = Stats(numbers)
-
-    at75 = stats.percentile(75)
-    at25 = stats.percentile(25)
-    print("should get a stack")
-    traceback.print_stack()
-    print("Interquartile:", at75 - at25)
-
-    #tbl.append(HT.TR(HT.TD("Statistic",align="left", Class="fs14 fwb ffl b1 cw cbrb", width = 180),
-    #                HT.TD("Value", align="right", Class="fs14 fwb ffl b1 cw cbrb", width = 60)))
-    #tbl.append(HT.TR(HT.TD("N of Samples",align="left", Class="fs13 b1 cbw c222"),
-    #                HT.TD(N,nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-    #tbl.append(HT.TR(HT.TD("Mean",align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-    #                HT.TD("%2.3f" % traitmean,nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-    #tbl.append(HT.TR(HT.TD("Median",align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-    #                HT.TD("%2.3f" % traitmedian,nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-    ##tbl.append(HT.TR(HT.TD("Variance",align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-    ##               HT.TD("%2.3f" % traitvar,nowrap="yes",align="left", Class="fs13 b1 cbw c222")))
-    #tbl.append(HT.TR(HT.TD("Standard Error (SE)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-    #                HT.TD("%2.3f" % traitsem,nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-    #tbl.append(HT.TR(HT.TD("Standard Deviation (SD)", align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-    #                HT.TD("%2.3f" % traitstdev,nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-    #tbl.append(HT.TR(HT.TD("Minimum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-    #                HT.TD("%s" % dataXZ[0][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-    #tbl.append(HT.TR(HT.TD("Maximum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-    #                HT.TD("%s" % dataXZ[-1][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-
-
-
-    if (trait_type != None and trait_type == 'ProbeSet'):
-        #tbl.append(HT.TR(HT.TD("Range (log2)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-        #        HT.TD("%2.3f" % (dataXZ[-1][1]-dataXZ[0][1]),nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-        #tbl.append(HT.TR(HT.TD(HT.Span("Range (fold)"),align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-        #        HT.TD("%2.2f" % pow(2.0,(dataXZ[-1][1]-dataXZ[0][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-        #tbl.append(HT.TR(HT.TD(HT.Span(HT.Href(url="/glossary.html#Interquartile", target="_blank", text="Interquartile Range", Class="non_bold")), align="left", Class="fs13 b1 cbw c222",nowrap="yes"),
-        #        HT.TD("%2.2f" % pow(2.0,(dataXZ[int((N-1)*3.0/4.0)][1]-dataXZ[int((N-1)/4.0)][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right"))
-        st['range_log2'] = dataXZ[-1][1]-dataXZ[0][1]
-        st['range_fold'] = pow(2.0, (dataXZ[-1][1]-dataXZ[0][1]))
-        st['interquartile'] = pow(2.0, (dataXZ[int((st['N']-1)*3.0/4.0)][1]-dataXZ[int((st['N']-1)/4.0)][1]))
-
-        #XZ, 04/01/2009: don't try to get H2 value for probe.
-        if not cellid:
-            if heritability:
-                # This field needs to still be put into the Jinja2 template
-                st['heritability'] = heritability
-                #tbl.append(HT.TR(HT.TD(HT.Span("Heritability"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),HT.TD("%s" % heritability, nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
-
-        # Lei Yan
-        # 2008/12/19
-
-    return st
-
-def plotNormalProbability(vals=None, RISet='', title=None, showstrains=0, specialStrains=[None], size=(750,500)):
-
-    dataXZ = vals[:]
-    dataXZ.sort(webqtlUtil.cmpOrder)
-    dataLabel = []
-    dataX = map(lambda X: X[1], dataXZ)
-
-    showLabel = showstrains
-    if len(dataXZ) > 50:
-        showLabel = 0
-    for item in dataXZ:
-        strainName = webqtlUtil.genShortStrainName(RISet=RISet, input_strainName=item[0])
-        dataLabel.append(strainName)
-
-    dataY=Plot.U(len(dataX))
-    dataZ=map(Plot.inverseCumul,dataY)
-    c = pid.PILCanvas(size=(750,500))
-    Plot.plotXY(c, dataZ, dataX, dataLabel = dataLabel, XLabel='Expected Z score', connectdot=0, YLabel='Trait value', title=title, specialCases=specialStrains, showLabel = showLabel)
-
-    filename= webqtlUtil.genRandStr("nP_")
-    c.save(webqtlConfig.GENERATED_IMAGE_DIR+filename, format='gif')
-
-    img=HT.Image('/image/'+filename+'.gif',border=0)
-
-    return img
-
-def plotBoxPlot(vals):
-
-    valsOnly = []
-    dataXZ = vals[:]
-    for i in range(len(dataXZ)):
-        valsOnly.append(dataXZ[i][1])
-
-    plotHeight = 320
-    plotWidth = 220
-    xLeftOffset = 60
-    xRightOffset = 40
-    yTopOffset = 40
-    yBottomOffset = 60
-
-    canvasHeight = plotHeight + yTopOffset + yBottomOffset
-    canvasWidth = plotWidth + xLeftOffset + xRightOffset
-    canvas = pid.PILCanvas(size=(canvasWidth,canvasHeight))
-    XXX = [('', valsOnly[:])]
-
-    Plot.plotBoxPlot(canvas, XXX, offset=(xLeftOffset, xRightOffset, yTopOffset, yBottomOffset), XLabel= "Trait")
-    filename= webqtlUtil.genRandStr("Box_")
-    canvas.save(webqtlConfig.GENERATED_IMAGE_DIR+filename, format='gif')
-    img=HT.Image('/image/'+filename+'.gif',border=0)
-
-    plotLink = HT.Span("More about ", HT.Href(text="Box Plots", url="http://davidmlane.com/hyperstat/A37797.html", target="_blank", Class="fs13"))
-
-    return img, plotLink
-
-def plotBarGraph(identification='', RISet='', vals=None, type="name"):
-
-    this_identification = "unnamed trait"
-    if identification:
-        this_identification = identification
-
-    if type=="rank":
-        dataXZ = vals[:]
-        dataXZ.sort(webqtlUtil.cmpOrder)
-        title='%s' % this_identification
-    else:
-        dataXZ = vals[:]
-        title='%s' % this_identification
-
-    tvals = []
-    tnames = []
-    tvars = []
-    for i in range(len(dataXZ)):
-        tvals.append(dataXZ[i][1])
-        tnames.append(webqtlUtil.genShortStrainName(RISet=RISet, input_strainName=dataXZ[i][0]))
-        tvars.append(dataXZ[i][2])
-    nnStrain = len(tnames)
-
-    sLabel = 1
-
-    ###determine bar width and space width
-    if nnStrain < 20:
-        sw = 4
-    elif nnStrain < 40:
-        sw = 3
-    else:
-        sw = 2
-
-    ### 700 is the default plot width minus Xoffsets for 40 strains
-    defaultWidth = 650
-    if nnStrain > 40:
-        defaultWidth += (nnStrain-40)*10
-    defaultOffset = 100
-    bw = int(0.5+(defaultWidth - (nnStrain-1.0)*sw)/nnStrain)
-    if bw < 10:
-        bw = 10
-
-    plotWidth = (nnStrain-1)*sw + nnStrain*bw + defaultOffset
-    plotHeight = 500
-    #print [plotWidth, plotHeight, bw, sw, nnStrain]
-    c = pid.PILCanvas(size=(plotWidth,plotHeight))
-    Plot.plotBarText(c, tvals, tnames, variance=tvars, YLabel='Value', title=title, sLabel = sLabel, barSpace = sw)
-
-    filename= webqtlUtil.genRandStr("Bar_")
-    c.save(webqtlConfig.GENERATED_IMAGE_DIR+filename, format='gif')
-    img=HT.Image('/image/'+filename+'.gif',border=0)
-
-    return img
diff --git a/wqflask/basicStatistics/__init__.py b/wqflask/basicStatistics/__init__.py
deleted file mode 100644
index e69de29b..00000000
--- a/wqflask/basicStatistics/__init__.py
+++ /dev/null
diff --git a/wqflask/utility/Plot.py b/wqflask/utility/Plot.py
index d60e2bb2..3a8b8dd5 100644
--- a/wqflask/utility/Plot.py
+++ b/wqflask/utility/Plot.py
@@ -36,11 +36,10 @@ from numarray import linear_algebra as la
 from numarray import ones, array, dot, swapaxes
 
 import reaper
-# sys.path.append("..") Never in a running webserver
-from basicStatistics import corestats
 
 import svg
 import webqtlUtil
+import corestats
 from base import webqtlConfig
 
 import utility.logger
@@ -315,137 +314,6 @@ def find_outliers(vals):
     logger.debug(pf(locals()))
     return upper_bound, lower_bound
 
-
-def plotBoxPlot(canvas, data, offset= (40, 40, 40, 40), XLabel="Category", YLabel="Value"):
-    xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
-    plotWidth = canvas.size[0] - xLeftOffset - xRightOffset
-    plotHeight = canvas.size[1] - yTopOffset - yBottomOffset
-    iValues = []
-    for item in data:
-        for item2 in item[1]:
-            try:
-                iValues.append(item2[1])
-            except:
-                iValues.append(item2)
-
-    #draw frame
-    max_Y = max(iValues)
-    min_Y = min(iValues)
-    scaleY = detScale(min_Y, max_Y)
-    Yll = scaleY[0]
-    Yur = scaleY[1]
-    nStep = scaleY[2]
-    stepY = (Yur - Yll)/nStep
-    stepYPixel = plotHeight/(nStep)
-    canvas.drawRect(plotWidth+xLeftOffset, plotHeight + yTopOffset, xLeftOffset, yTopOffset)
-
-    ##draw Y Scale
-    YYY = Yll
-    YCoord = plotHeight + yTopOffset
-    scaleFont=pid.Font(ttf="cour",size=11,bold=1)
-    for i in range(nStep+1):
-        strY = cformat(d=YYY, rank=0)
-        YCoord = max(YCoord, yTopOffset)
-        canvas.drawLine(xLeftOffset,YCoord,xLeftOffset-5,YCoord)
-        canvas.drawString(strY, xLeftOffset -30,YCoord +5,font=scaleFont)
-        YYY += stepY
-        YCoord -= stepYPixel
-
-    ##draw X Scale
-    stepX = plotWidth/len(data)
-    XCoord = xLeftOffset + 0.5*stepX
-    YCoord = plotHeight + yTopOffset
-    scaleFont = pid.Font(ttf="tahoma",size=12,bold=0)
-    labelFont = pid.Font(ttf="tahoma",size=13,bold=0)
-    for item in data:
-        itemname, itemvalue = item
-        canvas.drawLine(XCoord, YCoord,XCoord, YCoord+5, color=pid.black)
-        canvas.drawString(itemname, XCoord - canvas.stringWidth(itemname,font=labelFont)/2.0,\
-        YCoord +20,font=labelFont)
-
-        nValue = len(itemvalue)
-        catValue = []
-        for item2 in itemvalue:
-            try:
-                tstrain, tvalue = item2
-            except:
-                tvalue = item2
-            if nValue <= 4:
-                canvas.drawCross(XCoord, plotHeight + yTopOffset - (tvalue-Yll)*plotHeight/(Yur - Yll), color=pid.red,size=5)
-            else:
-                catValue.append(tvalue)
-        if catValue != []:
-            catMean = gmean(catValue)
-            catMedian = gmedian(catValue)
-            lowHinge = gpercentile(catValue, 25)
-            upHinge = gpercentile(catValue, 75)
-            Hstep = 1.5*(upHinge - lowHinge)
-
-            outlier = []
-            extrem = []
-
-            upperAdj = None
-            for item in catValue:
-                if item >= upHinge + 2*Hstep:
-                    extrem.append(item)
-                elif item >= upHinge + Hstep:
-                    outlier.append(item)
-                elif item > upHinge and  item < upHinge + Hstep:
-                    if upperAdj == None or item > upperAdj:
-                        upperAdj = item
-                else:
-                    pass
-            lowerAdj = None
-            for item in catValue:
-                if item <= lowHinge - 2*Hstep:
-                    extrem.append(item)
-                elif item <= lowHinge - Hstep:
-                    outlier.append(item)
-                if item < lowHinge and  item > lowHinge - Hstep:
-                    if lowerAdj == None or item < lowerAdj:
-                        lowerAdj = item
-                    else:
-                        pass
-            canvas.drawRect(XCoord-20, plotHeight + yTopOffset - (lowHinge-Yll)*plotHeight/(Yur - Yll), \
-                    XCoord+20, plotHeight + yTopOffset - (upHinge-Yll)*plotHeight/(Yur - Yll))
-            canvas.drawLine(XCoord-20, plotHeight + yTopOffset - (catMedian-Yll)*plotHeight/(Yur - Yll), \
-                    XCoord+20, plotHeight + yTopOffset - (catMedian-Yll)*plotHeight/(Yur - Yll))
-            if upperAdj != None:
-                canvas.drawLine(XCoord, plotHeight + yTopOffset - (upHinge-Yll)*plotHeight/(Yur - Yll), \
-                XCoord, plotHeight + yTopOffset - (upperAdj-Yll)*plotHeight/(Yur - Yll))
-                canvas.drawLine(XCoord-20, plotHeight + yTopOffset - (upperAdj-Yll)*plotHeight/(Yur - Yll), \
-                XCoord+20, plotHeight + yTopOffset - (upperAdj-Yll)*plotHeight/(Yur - Yll))
-            if lowerAdj != None:
-                canvas.drawLine(XCoord, plotHeight + yTopOffset - (lowHinge-Yll)*plotHeight/(Yur - Yll), \
-                XCoord, plotHeight + yTopOffset - (lowerAdj-Yll)*plotHeight/(Yur - Yll))
-                canvas.drawLine(XCoord-20, plotHeight + yTopOffset - (lowerAdj-Yll)*plotHeight/(Yur - Yll), \
-                XCoord+20, plotHeight + yTopOffset - (lowerAdj-Yll)*plotHeight/(Yur - Yll))
-
-            outlierFont = pid.Font(ttf="cour",size=12,bold=0)
-            if outlier != []:
-                for item in outlier:
-                    yc = plotHeight + yTopOffset - (item-Yll)*plotHeight/(Yur - Yll)
-                    #canvas.drawEllipse(XCoord-3, yc-3, XCoord+3, yc+3)
-                    canvas.drawString('o', XCoord-3, yc+5, font=outlierFont, color=pid.orange)
-            if extrem != []:
-                for item in extrem:
-                    yc = plotHeight + yTopOffset - (item-Yll)*plotHeight/(Yur - Yll)
-                    #canvas.drawEllipse(XCoord-3, yc-3, XCoord+3, yc+3)
-                    canvas.drawString('*', XCoord-3, yc+6, font=outlierFont, color=pid.red)
-
-            canvas.drawCross(XCoord, plotHeight + yTopOffset - (catMean-Yll)*plotHeight/(Yur - Yll), \
-                    color=pid.blue,size=3)
-            #print(catMean, catMedian, cat25per, cat75per)
-            pass
-
-        XCoord += stepX
-
-    labelFont=pid.Font(ttf="verdana",size=18,bold=0)
-    canvas.drawString(XLabel, xLeftOffset + (plotWidth -canvas.stringWidth(XLabel,font=labelFont))/2.0, \
-    YCoord +40, font=labelFont)
-    canvas.drawString(YLabel,xLeftOffset-40, YCoord-(plotHeight -canvas.stringWidth(YLabel,font=labelFont))/2.0,\
-     font=labelFont, angle =90)
-
 def plotSecurity(canvas, text="12345"):
     if not text:
         return
diff --git a/wqflask/basicStatistics/corestats.py b/wqflask/utility/corestats.py
index eba84c52..c48183ed 100644
--- a/wqflask/basicStatistics/corestats.py
+++ b/wqflask/utility/corestats.py
@@ -13,11 +13,9 @@
 #  License as published by the Free Software Foundation; either
 #  version 2.1 of the License, or (at your option) any later version.
 
-
-
 import sys
 
-
+#ZS: Should switch to using some third party library for this; maybe scipy has an equivalent
 class Stats:
 
     def __init__(self, sequence):
@@ -89,8 +87,6 @@ class Stats:
         return value
 
 
-
-
 # Sample script using this class:
 # -------------------------------------------
 #    #!/usr/bin/env python
@@ -100,4 +96,4 @@ class Stats:
 #    stats = corestats.Stats(sequence)
 #    print stats.avg()
 #    print stats.percentile(90)
-# -------------------------------------------
+# -------------------------------------------
\ No newline at end of file
diff --git a/wqflask/wqflask/show_trait/show_trait.py b/wqflask/wqflask/show_trait/show_trait.py
index 6de5cd5f..1f000564 100644
--- a/wqflask/wqflask/show_trait/show_trait.py
+++ b/wqflask/wqflask/show_trait/show_trait.py
@@ -24,7 +24,6 @@ from utility import webqtlUtil, Plot, Bunch, helper_functions
 from base.trait import GeneralTrait
 from base import data_set
 from db import webqtlDatabaseFunction
-from basicStatistics import BasicStatisticsFunctions
 
 from pprint import pformat as pf