added STYLES_MAP and consistent ordering to plot

gwinc/plot.py

@@ -3,26 +3,71 @@ import matplotlib.pyplot as plt
 
 import logging
 
-COLOR_MAP = {
-    'Quantum Vacuum': (0.41568627450980394, 0.23921568627450981, 0.60392156862745094),
-    'Seismic': (0.69411764705882351, 0.34901960784313724, 0.15686274509803921),
-    'Newtonian Gravity': (0.20000000000000001, 0.62745098039215685, 0.17254901960784313),
-    'Suspension Thermal': (0.12156862745098039, 0.47058823529411764, 0.70588235294117652),
-    'Coating Brownian': (0.8901960784313725, 0.10196078431372549, 0.10980392156862745),
-    'Coating Thermo-Optic': (0.98431372549019602, 0.60392156862745094, 0.59999999999999998),
-    'ITM Thermo-Refractive': (1.0, 0.49803921568627452, 0.0),
-    'ITM Carrier Density': (0.99215686274509807, 0.74901960784313726, 0.43529411764705883),
-    'Substrate Brownian': (0.69803921568627447, 0.87450980392156863, 0.54117647058823526),
-    'Substrate Thermo-Elastic': (0.65098039215686276, 0.80784313725490198, 0.8901960784313725),
-    'Excess Gas': (0.792156862745098, 0.69803921568627447, 0.83921568627450982),
-    }
-
-
-def plot_noise(noises):
+PRIORITY_MAP = {
+    'Quantum Vacuum': 0,
+    'Seismic': 1,
+    'Newtonian Gravity': 2,
+    'Suspension Thermal': 3,
+    'Coating Brownian': 4,
+    'Coating Thermo-Optic': 5,
+    'ITM Thermo-Refractive': 6,
+    'ITM Carrier Density': 7,
+    'Substrate Brownian': 8,
+    'Substrate Thermo-Elastic': 9,
+    'Excess Gas': 10,
+}
+
+STYLE_MAP = {
+    'Quantum Vacuum': dict(
+        color = (0.41568627450980394, 0.23921568627450981, 0.60392156862745094),
+    ),
+    'Seismic': dict(
+        color = (0.69411764705882351, 0.34901960784313724, 0.15686274509803921),
+    ),
+    'Newtonian Gravity': dict(
+        color = (0.20000000000000001, 0.62745098039215685, 0.17254901960784313),
+    ),
+    'Suspension Thermal': dict(
+        color = (0.12156862745098039, 0.47058823529411764, 0.70588235294117652),
+    ),
+    'Coating Brownian': dict(
+        color = (0.8901960784313725, 0.10196078431372549, 0.10980392156862745),
+    ),
+    'Coating Thermo-Optic': dict(
+        color = (0.98431372549019602, 0.60392156862745094, 0.59999999999999998),
+        ls = '--',
+    ),
+    'ITM Thermo-Refractive': dict(
+        color = (1.0, 0.49803921568627452, 0.0),
+        ls = '--',
+    ),
+    'ITM Carrier Density': dict(
+        color = (0.99215686274509807, 0.74901960784313726, 0.43529411764705883),
+        ls = '--',
+    ),
+    'Substrate Brownian': dict(
+        color = (0.69803921568627447, 0.87450980392156863, 0.54117647058823526),
+        ls = '--',
+    ),
+    'Substrate Thermo-Elastic': dict(
+        color = (0.65098039215686276, 0.80784313725490198, 0.8901960784313725),
+        ls = '--',
+    ),
+    'Excess Gas': dict(
+        color = (0.792156862745098, 0.69803921568627447, 0.83921568627450982),
+        ls = '--',
+    ),
+}
+
+
+def plot_noise(noises,):
     f = noises['Freq']
 
     def plot_dict(noises):
-        for name, noise in noises.items():
+        #use sorted to force a consistent ordering
+        #The key lambda in sorted gets the (name, noise) pair and so nn[0] returns the name
+        #the return tuple causes sorting by priority, with a fallback to lexical sort on the name
+        for name, noise in sorted(noises.items(), key = lambda nn : (PRIORITY_MAP.get(nn[0], 100), nn[0])):
             if name in ['Freq', 'Total']:
                 continue
             if isinstance(noise, dict):
@@ -30,17 +75,34 @@ def plot_noise(noises):
             else:
                 logging.info("plotting '{}'...".format(name))
                 noise = noises[name]
+                stylekw = dict(
+                    color = (0, 0, 0),
+                    label = name,
+                    lw = 3,
+                )
                 try:
-                    color = COLOR_MAP[name]
+                    style = STYLE_MAP[name]
+                    stylekw.update(style)
                 except KeyError:
-                    color = (0, 0, 0)
-                plt.loglog(f, sqrt(noise), color=color, label=name, lw=3)
+                    pass
+                plt.loglog(f, sqrt(noise), **stylekw)
     plot_dict(noises)
 
     plt.loglog(f, sqrt(noises['Total']), color='black', label='Total', lw=4)
 
-    plt.grid(True, which='both')
-    plt.legend(ncol=2)
+    plt.grid(
+        True,
+        which='both',
+        lw = .5,
+        ls = '-',
+        alpha = .5,
+    )
+
+    plt.legend(
+        ncol=2,
+        fontsize = 'small',
+    )
+
     plt.xlabel('Frequency [Hz]')
     plt.ylabel(u"Strain [1/\u221AHz]")
     plt.xlim([min(f), max(f)])