generated pngs and updated README

README.md

 # Satellite TLE Utils
 
-## dailySatPositions
+## TLEConverter
 
-Creates a file of the daily position of a satellite from a file of TLEs
+Creates a .sbpt file of the daily position of a satellite from a file of TLEs
 
 ### Synopsis
 
-**dailySatPositions.py** [OPTIONS] SAT-NAME TLE-FILE
+**TLEConverter.py** [OPTIONS] SAT-NAME TLE-FILE
 
 ### Description
 
-This script will generate a list of days and subpoints in the format
+This script will generate a .sbpt file with the following format
 
-{day-format} {subpoint}  
+{satellite} {year} {day of year} {subpoint}  
 ...
 
+for every day in the time range of the TLE file.
+
 The script takes in a file that contains a list of TLE (two line or three line elements).
 Any improperly formatted TLEs will be skipped.
 
 ### Options
 
 **-o, --output=OUTPUT**  
-    Change the output of the daily positions, default is stdout  
+    Change the output of the daily subpoints, default is stdout  
  
-**-f, --format=FORMAT**  
-    Change the {day-format} of the output, must follow C standard strftime date formats  
-
 **-m, --mode=MODE**  
     Change the mode to open the specified output, options are w,x,wb,xb  
 
 **-v, --verbose**  
     Changes the verbosity of script  
 
-## positionVisualizer
+## multiTLEConverter
+
+Creates multiple .sbpt files based on all the .tle files in a directory
+
+### Synopsis
+
+**multiTLEConverter**
+
+### Description
+
+This script will prompt the user for a directory full of .tle files, then the output directory for the to-be-generated .sbpt files.
+Then the script will go through every .tle file in the directory and prompt the user for the same of the satellite associated with that tle.
+Finally, the script will generate all the .sbpt files specified by the user.
+
+## subptVisualizer
+
+Visualizes one or more .sbpt files using matplotlib and numpy
+
+### Synopsis
+
+**subptVisualizer.py** [OPTIONS]
+
+### Description
+
+This script will create a .png image of a .sbpt file, graphing the satellites latitude through time.
+
+### Options
+
+**-l, --list=LIST** 
+    Required list of the path to one or more .sbpt files
+
+**-v, --verbose** 
+    Changes the verbosity of script
+
+**-o, --outdir=OUT** 
+    Change the directory that the .png file is generated in, default is current directory
+
+### Dependencies
 
-To be implemented
+This script requires matplotlib and numpy to run.

bin/pos_visualizer.py

-import sys, os, random
-import matplotlib
-matplotlib.use('agg')
-import matplotlib.pyplot as plt
-import matplotlib.patches as mpatches
-import numpy as np
-
-LEGEND_LIST = []
-COLORS = ['blue', 'red', 'green', 'purple', 'orange', 'black', 'lime', 'olive', 'sienna']
-
-# initializes the plot
-def initPlot(f):
-    plt.ylabel('Year')
-    plt.xlabel('Longitude')
-    plt.title('Geostationary Equator Coverage')
-    plt.figure().set_figheight(15)
-   
-    plt.ylim() 
-    plt.xlim(-180, 180)
-    #plt.axis([-180, 180, 1996, 1966])
-
-# generates the boxes on the plot for a specific location file
-def genPlot(f):
-    global COLORS, LEGEND_LIST
-    
-    print("Using file " + f)
-    i = random.randint(0,len(COLORS) - 1)
-    color = COLORS[i]
-    del COLORS[i]
-    
-    new_patch = mpatches.Patch(color=color, label=f[f.rindex('/') + 1 : f.index("_SUBPOINTS.txt")])
-    LEGEND_LIST.append(new_patch)
-     
-    data = np.loadtxt(f, dtype='str', skiprows=2)
-    x_vals = np.char.partition(data[:,2], ':')[:,0].astype('float')
-    heights = np.full_like(data[:,0], 1 / 365, dtype = 'float')
-    widths = np.full_like(data[:,0], 60, dtype = 'float')
-    bottoms = data[:,0].astype('float') 
-    plt.bar(x_vals, heights, width = widths, bottom = bottoms, color = color)
-    
-    print('finished file ' + f)
-
-def main(argv):
-    if(len(argv) != 2):
-        print("Usage:  daily_pos_file out_dir")
-        exit()
-    
-    os.makedirs(argv[1], exist_ok='True')    
-    outName = ""
-    try:
-        f = open(argv[0], 'r')
-    except IOError as error:
-        print("Error reading file in pos_visualizer.py")
-        print(error)
-    initPlot(f)
-
-    if(os.path.isfile(argv[0])):
-        genPlot(argv[0])
-        try:
-            outName = argv[0][argv[0].rindex('/') + 1 : argv[0].find('_')]
-        except:
-            outName = 'sat-vis'
-    elif(os.path.isdir(argv[0])):
-        outName = 'all'
-        fileCount = 1
-        for filename in os.listdir(argv[0]):
-            if(fileCount > MAX_FILES):
-                break;
-            f = os.path.join(argv[0],filename)
-            if os.path.isfile(f):
-                fileCount+=1
-                genPlot(f)
-    
-    plt.legend(handles=LEGEND_LIST, loc ='upper right')
-    plt.savefig(os.path.join(argv[1], outName + '.png'))
-
-if __name__ == '__main__':
-    main(sys.argv[1:])

bin/dailyPositionVisualizer.py → bin/subptVisualizer.py

@@ -4,6 +4,7 @@ try:
     import matplotlib
     matplotlib.use('agg')
     import matplotlib.pyplot as plt
+    import matplotlib.patches as mpatches
 except ImportError as e:
     print("Matplotlib is needed to generate graphs")
     sys.exit(1)
@@ -34,27 +35,40 @@ def main(argv):
 
     args = parser.parse_args(argv)
 
+    if(not os.path.isdir(args.outdir)):
+        print("Output directory does not exist: " + args.outdir)
+        sys.exit(1)
+
     plt.ylabel('Year')
     plt.xlabel('Longitude')
     plt.title('Geostationary Equator Coverage')
     plt.figure().set_figheight(15)
-    plt.xlim(-180, 180)
+    plt.xlim(-180,180)
 
     min_date =  9999999
     max_date = -9999999
     plot_list = []
+    patch_list = []
     for subpt in args.list:
         data = np.loadtxt(subpt, dtype='str')
         min_date = min(min_date, int(data[0][1]))
         max_date = max(max_date, int(data[-1][1]))
-        plot_list.append(genData(data))
+        if(args.verbose):
+            print("Graphing " + data[0][0])
+        gen = genData(data)
+        p = plt.bar(gen[0], gen[1], width = gen[2], bottom = gen[3])
+        patch_list.append(mpatches.Patch(label=data[0][0], color = p[-1].get_facecolor()))
+       
+    year_axis = np.arange(max_date, min_date - 1, -1, dtype='int')
+    plt.yticks(year_axis)
+    plt.gca().invert_yaxis()
+    plt.legend(handles=patch_list)
     
-    plt.ylim(min_date, max_date)
-
-    for dat in plot_list:
-        plt.bar(dat[0], dat[1], width = dat[2], bottom = dat[3])
-
-    plt.savefig(os.path.join(args.outdir, args.list[0] + '.png')) 
+    if(len(args.list) == 1):
+        out_name = data[0][0]
+    else:
+        out_name = "sats"
+    plt.savefig(os.path.join(args.outdir, out_name + '.png')) 
 
 if __name__ == '__main__':
     main(sys.argv[1:])