# # File: # bar1.py # # Synopsis: # Illustrates how to draw bar charts. # # Categories: # xy plots # bar charts # polygons # polylines # text # # Author: # Mary Haley # # Date of initial publication: # March 2008 # # Description: # This example shows how to generate bar charts, using polylines and # polygons. # # Effects illustrated: # o Drawing primitives on a plot. # o Drawing text on a plot. # o Using indexed color. # # Output: # This example produces two frames. # # Notes: # from __future__ import print_function import numpy import Ngl # # This script plots, as a series of bars, the number of times US # baseball teams have won or lost the World Series. # # # Function that returns coordinates of a bar, given the x,y values, # the dx (between bars), the width of the bar as a percentage of the # distance between x values (bar_width_perc), and the minimum y to # start the bar from. # def get_bar(x,y,dx,ymin,bar_width_perc=0.6): dxp = (dx * bar_width_perc)/2. xbar = numpy.array([x-dxp,x+dxp,x+dxp,x-dxp,x-dxp]) ybar = numpy.array([ ymin, ymin, y, y, ymin]) return xbar,ybar # # Main program # # # Define long and short name of baseball teams, along with their # colors in RGB percentages. Note that some of these teams became # other teams, but the original and the new names are both included. # teams = { "Anaheim Angels" : {"abbrev" : "AA", "colors" : [ 73, 0, 13]}, \ "Arizona Diamondbacks" : {"abbrev" : "AD", "colors" : [ 39, 21, 63]}, \ "Atlanta Braves" : {"abbrev" : "AB", "colors" : [ 69, 1, 22]}, \ "Baltimore Orioles" : {"abbrev" : "BO", "colors" : [ 82, 35, 4]}, \ "Boston Braves" : {"abbrev" : "BB", "colors" : [ 66, 13, 24]}, \ "Boston Red Sox" : {"abbrev" : "BRS", "colors" : [ 73, 19, 24]}, \ "Brooklyn Dodgers" : {"abbrev" : "BD", "colors" : [ 5, 18, 52]}, \ "Brooklyn Robins" : {"abbrev" : "BR", "colors" : [ 3, 16, 52]}, \ "Chicago Cubs" : {"abbrev" : "CC", "colors" : [ 6, 20, 53]}, \ "Chicago White Sox" : {"abbrev" : "CWS", "colors" : [ 0, 0, 0]}, \ "Cincinnati Reds" : {"abbrev" : "CRe", "colors" : [ 78, 0, 12]}, \ "Cleveland Indians" : {"abbrev" : "CI", "colors" : [ 1, 20, 40]}, \ "Colorado Rockies" : {"abbrev" : "CRo", "colors" : [ 20, 20, 40]}, \ "Detroit Tigers" : {"abbrev" : "DT", "colors" : [ 92, 49, 22]}, \ "Florida Marlins" : {"abbrev" : "FM", "colors" : [ 14, 62, 64]}, \ "Houston Astros" : {"abbrev" : "HA", "colors" : [ 58, 20, 17]}, \ "Kansas City Royals" : {"abbrev" : "KCR", "colors" : [ 0, 2, 45]}, \ "Los Angeles Dodgers" : {"abbrev" : "LAD", "colors" : [ 3, 24, 42]}, \ "Milwaukee Braves" : {"abbrev" : "MBa", "colors" : [ 93, 9, 12]}, \ "Milwaukee Brewers" : {"abbrev" : "MBe", "colors" : [ 4, 13, 32]}, \ "Minnesota Twins" : {"abbrev" : "MT", "colors" : [ 74, 0, 20]}, \ "New York Giants" : {"abbrev" : "NYG", "colors" : [ 2, 6, 26]}, \ "New York Mets" : {"abbrev" : "NYM", "colors" : [ 1, 17, 40]}, \ "New York Yankees" : {"abbrev" : "NYY", "colors" : [ 11, 16, 26]}, \ "Oakland Athletics" : {"abbrev" : "OA", "colors" : [ 0, 22, 19]}, \ "Philadelphia Athletics": {"abbrev" : "PA", "colors" : [ 7, 0, 55]}, \ "Philadelphia Phillies": {"abbrev" : "PPh", "colors" : [ 91, 9, 16]}, \ "Pittsburgh Pirates" : {"abbrev" : "PPi", "colors" : [ 46, 38, 13]}, \ "San Diego Padres" : {"abbrev" : "SDP", "colors" : [ 2, 8, 25]}, \ "San Francisco Giants" : {"abbrev" : "SFG", "colors" : [100, 35, 12]}, \ "Seattle Mariners" : {"abbrev" : "SM", "colors" : [ 5, 17, 34]}, \ "St. Louis Browns" : {"abbrev" : "SLB", "colors" : [ 81, 32, 14]}, \ "St. Louis Cardinals" : {"abbrev" : "SLC", "colors" : [ 77, 12, 23]}, \ "Tampa Bay Devil Rays" : {"abbrev" : "TBDR","colors" : [ 0, 43, 24]}, \ "Texas Rangers" : {"abbrev" : "TR", "colors" : [ 0, 20, 48]}, \ "Toronto Blue Jays" : {"abbrev" : "TBJ", "colors" : [ 0, 20, 60]}, \ "Washington Senators" : {"abbrev" : "WS", "colors" : [ 0, 4, 25]}, \ "Washington Nationals" : {"abbrev" : "WN", "colors" : [ 7, 13, 36]} \ } # # Special notes: # # - No world series in 1904 (boycotted by New York Giants) # or 1994 (strike). # # - Boston Red Sox first won their first WS as the Boston Americans. # I didn't include a separate entry for the Americans because the # bars were getting too thin. # # - Brooklyn Robins became the Brooklyn Dodgers became the LA Dodgers. # # - Boston Braves became the Milwaukee Braves became the Atlanta Braves. # # - St. Louis Browns became the Baltimore Orioles. # # - Washington Senators became the Minnesota Twins. # # - New York Giants became the San Francisco Giants. # # - Philadelphia Athletics became the Oakland Athletics. # # List each world series results as {year, [winning team, losing team]}. # world_series = { 1903 : ["BRS", "PPi"] ,\ 1904 : ["", ""], \ 1905 : ["NYG", "PA"], \ 1906 : ["CWS", "CC"], \ 1907 : ["CC", "DT"], \ 1908 : ["CC", "DT"], \ 1909 : ["PPi", "DT"], \ 1910 : ["PA", "CC"], \ 1911 : ["PA", "NYG"], \ 1912 : ["BRS", "NYG"], \ 1913 : ["PA", "NYG"], \ 1914 : ["BB", "PA"], \ 1915 : ["BRS", "PPh"], \ 1916 : ["BRS", "BR"], \ 1917 : ["CWS", "NYG"], \ 1918 : ["BRS", "CC"], \ 1919 : ["CRe", "CWS"], \ 1920 : ["CI", "BR"], \ 1921 : ["NYG", "NYY"], \ 1922 : ["NYG", "NYY"], \ 1923 : ["NYY", "NYG"], \ 1924 : ["WS", "NYG"], \ 1925 : ["PPi", "WS"], \ 1926 : ["SLC", "NYY"], \ 1927 : ["NYY", "PPi"], \ 1928 : ["NYY", "SLC"], \ 1929 : ["PA", "CC"], \ 1930 : ["PA", "SLC"], \ 1931 : ["SLC", "PA"], \ 1932 : ["NYY", "CC"], \ 1933 : ["NYG", "WS"], \ 1934 : ["SLC", "DT"], \ 1935 : ["DT", "CC"], \ 1936 : ["NYY", "NYG"], \ 1937 : ["NYY", "NYG"], \ 1938 : ["NYY", "CC"], \ 1939 : ["NYY", "CRe"], \ 1940 : ["CRe", "DT"], \ 1941 : ["NYY", "BD"], \ 1942 : ["SLC", "NYY"], \ 1943 : ["NYY", "SLC"], \ 1944 : ["SLC", "SLB"], \ 1945 : ["DT", "CC"], \ 1946 : ["SLC", "BRS"], \ 1947 : ["NYY", "BD"], \ 1948 : ["CI", "BB"], \ 1949 : ["NYY", "BD"], \ 1950 : ["NYY", "PPh"], \ 1951 : ["NYY", "NYG"], \ 1952 : ["NYY", "BD"], \ 1953 : ["NYY", "BD"], \ 1954 : ["NYG", "CI"], \ 1955 : ["BD", "NYY"], \ 1956 : ["NYY", "BD"], \ 1957 : ["MBa", "NYY"], \ 1958 : ["NYY", "MBa"], \ 1959 : ["LAD", "CWS"], \ 1960 : ["PPi", "NYY"], \ 1961 : ["NYY", "CRe"], \ 1962 : ["NYY", "SFG"], \ 1963 : ["LAD", "NYY"], \ 1964 : ["SLC", "NYY"], \ 1965 : ["LAD", "MT"], \ 1966 : ["BO", "LAD"], \ 1967 : ["SLC", "BRS"], \ 1968 : ["DT", "SLC"], \ 1969 : ["NYM", "BO"], \ 1970 : ["BO", "CRe"], \ 1971 : ["PPi", "BO"], \ 1972 : ["OA", "CRe"], \ 1973 : ["OA", "NYM"], \ 1974 : ["OA", "LAD"], \ 1975 : ["CRe", "BRS"], \ 1976 : ["CRe", "NYY"], \ 1977 : ["NYY", "LAD"], \ 1978 : ["NYY", "LAD"], \ 1979 : ["PPi", "BO"], \ 1980 : ["PPh", "KCR"], \ 1981 : ["LAD", "NYY"], \ 1982 : ["SLC", "MBe"], \ 1983 : ["BO", "PPh"], \ 1984 : ["DT", "SDP"], \ 1985 : ["KCR", "SLC"], \ 1986 : ["NYM", "BRS"], \ 1987 : ["MT", "SLC"], \ 1988 : ["LAD", "OA"], \ 1989 : ["OA", "SFG"], \ 1990 : ["CRe", "OA"], \ 1991 : ["MT", "AB"], \ 1992 : ["TBJ", "AB"], \ 1993 : ["TBJ", "PPh"], \ 1994 : ["", ""], \ 1995 : ["AB", "CI"], \ 1996 : ["NYY", "AB"], \ 1997 : ["FM", "CI"], \ 1998 : ["NYY", "SDP"], \ 1999 : ["NYY", "AB"], \ 2000 : ["NYY", "NYM"], \ 2001 : ["AD", "NYY"], \ 2002 : ["AA", "SFG"], \ 2003 : ["FM", "NYY"], \ 2004 : ["BRS", "SLC"], \ 2005 : ["CWS", "HA"], \ 2006 : ["SLC", "DT"], \ 2007 : ["BRS", "CRo"], \ 2008 : ["PPh", "TBR"], \ 2009 : ["NYY", "Pph"], \ 2010 : ["SFG", "TR"], \ 2011 : ["SLC", "TR"], \ 2012 : ["SFG", "DT"], \ 2013 : ["BRS", "SLC"], \ 2014 : ["SFG", "KCR"], \ 2015 : ["KCR", "NYM"], \ 2016 : ["CC", "CI"], \ 2017 : ["HA", "LAD"] \ } # # Count the number of times each team has won or lost and store # in an array. # nteams = len(teams) # Number of teams max_year = max(world_series.keys()) values = numpy.array(list(world_series.values())) won = values[:,0].tolist() # Index 0 = winning teams lost = values[:,1].tolist() # Index 1 = losing teams ngames = len(won) # Number of games # # Set up arrays to Define colors for each winning/losing team. # winning_colors = numpy.zeros((ngames+1,3),'f') losing_colors = numpy.zeros((ngames+1,3),'f') winning_colors[0,:] = [1.,1.,1.] winning_colors[1,:] = [0.,0.,0.] winning_colors[ngames,:] = [0.9,0.9,0.9] # Gray losing_colors[0,:] = [1.,1.,1.] losing_colors[1,:] = [0.,0.,0.] losing_colors[ngames,:] = [0.9,0.9,0.9] # Gray # # Loop through each team and count the number of teams it won and/or # lost the world series. If this number is > 0, then store in an # array. # winning_teams_ct = [] winning_teams_nm = [] losing_teams_ct = [] losing_teams_nm = [] nw = 2 # color index counter for winning team nl = 2 # color index counter for losing team sorted_teams = list(teams.keys()) sorted_teams.sort() # Sort the team names for team in sorted_teams: steam = teams[team]["abbrev"] if won.count(steam) > 0: winning_teams_ct.append(won.count(steam)) # Here's the count winning_teams_nm.append(team) # Name of winning team winning_colors[nw,:] = numpy.array(teams[team]["colors"])/100. nw += 1 if lost.count(steam) > 0: losing_teams_ct.append(lost.count(steam)) # Here's the count losing_teams_nm.append(team) # Name of losing team losing_colors[nl,:] = numpy.array(teams[team]["colors"])/100. nl += 1 # Store the winning and losing counts in numpy arrays. y_win = numpy.array(winning_teams_ct) x_win = numpy.array(list(range(1,y_win.shape[0]+1))) y_lose = numpy.array(losing_teams_ct) x_lose = numpy.array(list(range(1,y_lose.shape[0]+1))) # # Start the graphics portion of the script. # wks_type = "png" wks = Ngl.open_wks(wks_type,"bar1") Ngl.define_colormap(wks,winning_colors) res = Ngl.Resources() res.nglMaximize = False # Need to set to False if using # vp resources. res.vpXF = 0.12 # Move plot to left a little. res.vpYF = 0.98 # Move plot up a little. res.vpHeightF = 0.90 # Make plot higher than res.vpWidthF = 0.80 # it is wide. res.tmXBOn = False # Turn off bottom tickmarks & labes res.tmXTOn = False # Turn off top tickmarks & labes res.tmYROn = False # Turn off right tickmarks & labes res.tmYLMinorOn = False # Turn off left minor tickmarks res.tmEqualizeXYSizes = False # Don't try to equalize the lengths # of the tickmarks. res.tmYLMajorLengthF = 0.01 # Total length res.tmYLMajorOutwardLengthF = 0.01 # Outward length res.trYMinF = 0 # Minimum value on Y axis res.trXMinF = 0 # Minimum value on X axis. res.trYMaxF = max(y_win)+1 # Maximum value on Y axis. res.trXMaxF = max(x_win)+1 # Maximum value on X axis. res.tiXAxisString = "# of World Series Wins through {}".format(max_year) res.tiXAxisFontHeightF = 0.03 res.nglFrame = False # Don't advance frame. ymin = 0. # For bar plot. dx = min(x_win[1:-1]-x_win[0:-2]) # Distance between X values. bar_width_perc = 0.6 bar_width = bar_width_perc * dx # Bar width. txres = Ngl.Resources() # Resource list for text strings. txres.txFontHeightF = 0.015 gsres = Ngl.Resources() # Resource list for bars. # # Plot results for winning teams. # # Loop through each value, and create and draw a bar for it. # imax = numpy.where(y_win == max(y_win))[0] for i in range(len(y_win)): xbar,ybar = get_bar(x_win[i],y_win[i],dx,ymin) plot = Ngl.xy(wks,xbar,ybar,res) gsres.gsFillColor = [i+2] # Set color for bar. Ngl.polygon(wks,plot,xbar,ybar,gsres) # Fill the bar. Ngl.polyline(wks,plot,xbar,ybar) # Outline the bar. xbar,ybar = get_bar(x_win[i],y_win[i],dx,ymin) # # Put names of teams vertically above the bar. Have to treat the team # with the most wins (NY Yankees as of 2008) special because # the text runs off the screen otherwise. # if i == imax: txres.txJust = "BottomCenter" txres.txAngleF = 0. Ngl.text(wks,plot,winning_teams_nm[i],x_win[i],y_win[i],txres) else: txres.txJust = "CenterLeft" txres.txAngleF = 90. Ngl.text(wks,plot," {}".format(winning_teams_nm[i]),x_win[i],y_win[i],txres) Ngl.frame(wks) # # Now plot losing team results. # Ngl.define_colormap(wks,losing_colors) dx = min(x_lose[1:-1]-x_lose[0:-2]) # Distance between X values. bar_width = bar_width_perc * dx # Bar width. res.trYMaxF = max(y_lose)+1 # Maximum value on Y axis. res.trXMaxF = max(x_lose)+1 # Maximum value on X axis. res.tiXAxisString = "# of World Series Losses through {}".format(max_year) # # Loop through each value, and create and draw a bar for it. # imax = numpy.where(y_lose == max(y_lose))[0] for i in range(len(y_lose)): xbar,ybar = get_bar(x_lose[i],y_lose[i],dx,ymin) plot = Ngl.xy(wks,xbar,ybar,res) gsres.gsFillColor = [i+2] # Set color for bar. Ngl.polygon(wks,plot,xbar,ybar,gsres) # Fill the bar. Ngl.polyline(wks,plot,xbar,ybar) # Outline the bar. # # Put names of teams vertically above the bar. Have to treat the team # with the most losses (NY Yankees as of 2008) special because # the text runs off the screen otherwise. # if i == imax: txres.txJust = "BottomCenter" txres.txAngleF = 0. Ngl.text(wks,plot,losing_teams_nm[i],x_lose[i],y_lose[i],txres) else: txres.txJust = "CenterLeft" txres.txAngleF = 90. Ngl.text(wks,plot," {}".format(losing_teams_nm[i]),x_lose[i],y_lose[i],txres) Ngl.frame(wks) Ngl.end()