# HG changeset patch
# User devteam
# Date 1406562994 14400
# Node ID 6ff47de059a0237636cd8dd9eac68f57b96c4c3f
Imported from capsule None
diff -r 000000000000 -r 6ff47de059a0 histogram.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/histogram.py Mon Jul 28 11:56:34 2014 -0400
@@ -0,0 +1,101 @@
+#!/usr/bin/env python
+#Greg Von Kuster
+
+import sys
+from rpy import *
+
+assert sys.version_info[:2] >= ( 2, 4 )
+
+def stop_err(msg):
+ sys.stderr.write(msg)
+ sys.exit()
+
+def main():
+
+ # Handle input params
+ in_fname = sys.argv[1]
+ out_fname = sys.argv[2]
+ try:
+ column = int( sys.argv[3] ) - 1
+ except:
+ stop_err( "Column not specified, your query does not contain a column of numerical data." )
+ title = sys.argv[4]
+ xlab = sys.argv[5]
+ breaks = int( sys.argv[6] )
+ if breaks == 0:
+ breaks = "Sturges"
+ if sys.argv[7] == "true":
+ density = True
+ else: density = False
+ if len( sys.argv ) >= 9 and sys.argv[8] == "true":
+ frequency = True
+ else: frequency = False
+
+ matrix = []
+ skipped_lines = 0
+ first_invalid_line = 0
+ invalid_value = ''
+ i = 0
+ for i, line in enumerate( file( in_fname ) ):
+ valid = True
+ line = line.rstrip('\r\n')
+ # Skip comments
+ if line and not line.startswith( '#' ):
+ # Extract values and convert to floats
+ row = []
+ try:
+ fields = line.split( "\t" )
+ val = fields[column]
+ if val.lower() == "na":
+ row.append( float( "nan" ) )
+ except:
+ valid = False
+ skipped_lines += 1
+ if not first_invalid_line:
+ first_invalid_line = i+1
+ else:
+ try:
+ row.append( float( val ) )
+ except ValueError:
+ valid = False
+ skipped_lines += 1
+ if not first_invalid_line:
+ first_invalid_line = i+1
+ invalid_value = fields[column]
+ else:
+ valid = False
+ skipped_lines += 1
+ if not first_invalid_line:
+ first_invalid_line = i+1
+
+ if valid:
+ matrix += row
+
+ if skipped_lines < i:
+ try:
+ a = r.array( matrix )
+ r.pdf( out_fname, 8, 8 )
+ histogram = r.hist( a, probability=not frequency, main=title, xlab=xlab, breaks=breaks )
+ if density:
+ density = r.density( a )
+ if frequency:
+ scale_factor = len( matrix ) * ( histogram['mids'][1] - histogram['mids'][0] ) #uniform bandwidth taken from first 2 midpoints
+ density[ 'y' ] = map( lambda x: x * scale_factor, density[ 'y' ] )
+ r.lines( density )
+ r.dev_off()
+ except Exception, exc:
+ stop_err( "%s" %str( exc ) )
+ else:
+ if i == 0:
+ stop_err("Input dataset is empty.")
+ else:
+ stop_err( "All values in column %s are non-numeric." %sys.argv[3] )
+
+ print "Histogram of column %s. " %sys.argv[3]
+ if skipped_lines > 0:
+ print "Skipped %d invalid lines starting with line #%d, '%s'." % ( skipped_lines, first_invalid_line, invalid_value )
+
+ r.quit( save="no" )
+
+if __name__ == "__main__":
+ main()
diff -r 000000000000 -r 6ff47de059a0 histogram2.png
Binary file histogram2.png has changed
diff -r 000000000000 -r 6ff47de059a0 histogram2.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/histogram2.xml Mon Jul 28 11:56:34 2014 -0400
@@ -0,0 +1,77 @@
+
+ of a numeric column
+
+ rpy
+ R
+
+ histogram.py $input $out_file1 $numerical_column "$title" "$xlab" $breaks $density $frequency
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+.. class:: infomark
+
+**TIP:** To remove comment lines that do not begin with a *#* character, use *Text Manipulation->Remove beginning*
+
+ .. class:: infomark
+
+**TIP:** If your data is not TAB delimited, use *Text Manipulation->Convert*
+
+-----
+
+**Syntax**
+
+This tool computes a histogram of the numerical values in a column of a dataset.
+
+- All invalid, blank and comment lines in the dataset are skipped. The number of skipped lines is displayed in the resulting history item.
+- **Column for x axis** - only numerical columns are possible.
+- **Number of breaks(bars)** - breakpoints between histogram cells. Value of '0' will determine breaks automatically.
+- **Plot title** - the histogram title.
+- **Label for x axis** - the label of the x axis for the histogram.
+- **Include smoothed density** - if checked, the resulting graph will join the given corresponding points with line segments.
+
+-----
+
+**Example**
+
+- Input file::
+
+ 1 68 4.1
+ 2 71 4.6
+ 3 62 3.8
+ 4 75 4.4
+ 5 58 3.2
+ 6 60 3.1
+ 7 67 3.8
+ 8 68 4.1
+ 9 71 4.3
+ 10 69 3.7
+
+- Create a histogram on column 2 of the above dataset.
+
+.. image:: histogram2.png
+
+
+
diff -r 000000000000 -r 6ff47de059a0 plot_filter.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/plot_filter.py Mon Jul 28 11:56:34 2014 -0400
@@ -0,0 +1,19 @@
+
+def validate(incoming):
+ """Validator for the plotting program"""
+
+ bins = incoming.get("bins","")
+ col = incoming.get("col","")
+
+ if not bins or not col:
+ raise Exception, "You need to specify a number for bins and columns"
+
+ try:
+ bins = int(bins)
+ col = int(col)
+ except:
+ raise Exception, "Parameters are not valid numbers, columns:%s, bins:%s" % (col, bins)
+
+ if not 1= ( 2, 4 )
+
+def stop_err(msg):
+ sys.stderr.write(msg)
+ sys.exit()
+
+if __name__ == '__main__':
+ # parse the arguments
+
+ if len(sys.argv) != 6:
+ stop_err('Usage: python histogram.py input_file column bins output_file style')
+ sys.exit()
+
+ mode = sys.argv[5]
+ HIST = mode == 'hist'
+ try:
+ col = int(float(sys.argv[2]))
+ if HIST:
+ bin = int(float(sys.argv[3]))
+ else:
+ # hack, this parameter is the plotting style for scatter plots
+ if sys.argv[3] == 'P':
+ style = 'o'
+ elif sys.argv[3] == 'LP':
+ style = 'o-'
+ else:
+ style = '-'
+
+ except:
+ msg = 'Parameter were not numbers %s, %s' % (sys.argv[3], sys.argv[4])
+ stop_err(msg)
+
+ # validate arguments
+ inp_file = sys.argv[1]
+ out_file = sys.argv[4]
+
+ if HIST:
+ print "Histogram on column %s (%s bins)" % (col, bin)
+ else:
+ print "Scatterplot on column %s" % (col)
+
+ xcol= col -1
+ # read the file
+ values = []
+ try:
+ count = 0
+ for line in file(inp_file):
+ count += 1
+ line = line.strip()
+ if line and line[0] != '#':
+ values.append(float(line.split()[xcol]))
+ except Exception, e:
+ stop_err('%s' % e)
+ stop_err("Non numerical data at line %d, column %d" % (count, col) )
+
+ # plot the data
+
+ if HIST:
+ n, bins, patches = hist(values, bins=bin, normed=0)
+ else:
+ plot(values, style)
+
+ xlabel('values')
+ ylabel('counts')
+
+ if HIST:
+ title('Histogram of values over column %s (%s bins)' % (col, len(bins)) )
+ else:
+ title('Scatterplot over column %s' % col )
+ grid(True)
+
+ # the plotter detects types by file extension
+ png_out = out_file + '.png' # force it to png
+ savefig(png_out)
+
+ # shuffle it back and clean up
+ data = file(png_out, 'rb').read()
+ fp = open(out_file, 'wb')
+ fp.write(data)
+ fp.close()
+ os.remove(png_out)
diff -r 000000000000 -r 6ff47de059a0 test-data/histogram_in1.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/histogram_in1.tabular Mon Jul 28 11:56:34 2014 -0400
@@ -0,0 +1,10 @@
+1 68 4.1
+2 71 4.6
+3 62 3.8
+4 75 4.4
+5 58 3.2
+6 60 3.1
+7 67 3.8
+8 68 4.1
+9 71 4.3
+10 69 3.7
diff -r 000000000000 -r 6ff47de059a0 test-data/histogram_out1.pdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/histogram_out1.pdf Mon Jul 28 11:56:34 2014 -0400
@@ -0,0 +1,545 @@
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diff -r 000000000000 -r 6ff47de059a0 tool_dependencies.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_dependencies.xml Mon Jul 28 11:56:34 2014 -0400
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