# 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 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