Index: branches/trigger_burst_research/plot_basic_ratescan_info.py
===================================================================
--- branches/trigger_burst_research/plot_basic_ratescan_info.py	(revision 18302)
+++ 	(revision )
@@ -1,95 +1,0 @@
-import sys
-import numpy as np
-import matplotlib as mpl
-mpl.use('Agg')
-import matplotlib.pyplot as plt
-import pandas as pd
-from astropy.io import fits
-from calculate_burst_ratio_file import get_trigger_rates, fjd
-
-
-night_string = sys.argv[1]
-night_int = int(night_string)
-OFFSET=719163
-
-runs = pd.DataFrame.from_csv(
-    'foo.bar', 
-    infer_datetime_format=True, 
-    parse_dates=['fRunStart', 'fRunStop']
-    ).dropna()
-
-runs = runs.loc[runs.fNight==night_int]
-
-trigger_rates = get_trigger_rates(night_int, 
-    base_path='/fact/aux/')
-
-fig, ax1 = plt.subplots(figsize=(16, 9))
-ax1.set_xlabel("Time")
-ax1.set_yscale('log')
-ax1.set_ylabel("Rate [Hz]")
-ax1.grid()
-
-plt.title("basic Ratescan information from: " + night_string)
-
-plot_0 = ax1.plot_date(
-    trigger_rates['Time']+OFFSET, 
-    np.median(trigger_rates['BoardRate'], axis=1), 
-    'r.', ms=4.,
-    label="median BoardRate"
-    )
-
-plot_1 = ax1.plot_date(
-    trigger_rates['Time']+OFFSET, 
-    trigger_rates['TriggerRate'], 
-    'g.', ms=4.,
-    label="Camera TriggerRate"
-    )
-
-for runs_index in range(len(runs)):
-    this_run = runs.iloc[runs_index]
-    run_number = this_run['fRunID']
-
-    a = fjd(this_run['fRunStart'])+OFFSET
-    e = fjd(this_run['fRunStop'])+OFFSET
-    
-    ax1.axvline(a, color='g', linestyle='dashed')
-    ax1.axvline(e, color='r', linestyle='dashed')
-    ax1.text(a + (e-a)/2., 900, 
-        "{0}".format(run_number),
-        horizontalalignment='center',
-        verticalalignment='center',
-        fontsize=7,
-        )
-
-    med = this_run['median_of_board_rates']
-    std_dev = this_run['std_dev_of_board_rates']
-    
-    ax1.plot_date(
-        [a, e], 
-        [med+3*std_dev, med+3*std_dev], 
-        'm-')
-    
-
-
-plt.xlim((
-    fjd(runs.iloc[0]['fRunStart'])+OFFSET,
-    fjd(runs.iloc[-1]['fRunStop'])+OFFSET 
-    ))
-plt.ylim(1e-1, 1e6)
-
-plt.legend(
-    handles=[plot_0[0], plot_1[0]],
-    loc='lower left')
-
-plt.tight_layout()
-plt.savefig("board_rate_overview_"+night_string+'.png', 
-    dpi=300)
-
-plt.figure()
-plt.title("fHighBoardTriggerRateRatio distribution from {0}".format(night_int))
-plt.hist(runs.fBoardTriggerRateRatioAboveThreshold.values, 
-    bins=np.arange(0,0.6,1./60.), 
-    log=True )
-plt.grid()
-plt.xlabel("fHighBoardTriggerRateRatio")
-plt.savefig("ratio_dist_"+night_string+'.png')
Index: branches/trigger_burst_research/plot_rates_and_ratio_for_night.py
===================================================================
--- branches/trigger_burst_research/plot_rates_and_ratio_for_night.py	(revision 18303)
+++ branches/trigger_burst_research/plot_rates_and_ratio_for_night.py	(revision 18303)
@@ -0,0 +1,95 @@
+import sys
+import numpy as np
+import matplotlib as mpl
+mpl.use('Agg')
+import matplotlib.pyplot as plt
+import pandas as pd
+from astropy.io import fits
+from calculate_burst_ratio_file import get_trigger_rates, fjd
+
+
+night_string = sys.argv[1]
+night_int = int(night_string)
+OFFSET=719163
+
+runs = pd.DataFrame.from_csv(
+    'foo.bar', 
+    infer_datetime_format=True, 
+    parse_dates=['fRunStart', 'fRunStop']
+    ).dropna()
+
+runs = runs.loc[runs.fNight==night_int]
+
+trigger_rates = get_trigger_rates(night_int, 
+    base_path='/fact/aux/')
+
+fig, ax1 = plt.subplots(figsize=(16, 9))
+ax1.set_xlabel("Time")
+ax1.set_yscale('log')
+ax1.set_ylabel("Rate [Hz]")
+ax1.grid()
+
+plt.title("basic Ratescan information from: " + night_string)
+
+plot_0 = ax1.plot_date(
+    trigger_rates['Time']+OFFSET, 
+    np.median(trigger_rates['BoardRate'], axis=1), 
+    'r.', ms=4.,
+    label="median BoardRate"
+    )
+
+plot_1 = ax1.plot_date(
+    trigger_rates['Time']+OFFSET, 
+    trigger_rates['TriggerRate'], 
+    'g.', ms=4.,
+    label="Camera TriggerRate"
+    )
+
+for runs_index in range(len(runs)):
+    this_run = runs.iloc[runs_index]
+    run_number = this_run['fRunID']
+
+    a = fjd(this_run['fRunStart'])+OFFSET
+    e = fjd(this_run['fRunStop'])+OFFSET
+    
+    ax1.axvline(a, color='g', linestyle='dashed')
+    ax1.axvline(e, color='r', linestyle='dashed')
+    ax1.text(a + (e-a)/2., 900, 
+        "{0}".format(run_number),
+        horizontalalignment='center',
+        verticalalignment='center',
+        fontsize=7,
+        )
+
+    med = this_run['median_of_board_rates']
+    std_dev = this_run['std_dev_of_board_rates']
+    
+    ax1.plot_date(
+        [a, e], 
+        [med+3*std_dev, med+3*std_dev], 
+        'm-')
+    
+
+
+plt.xlim((
+    fjd(runs.iloc[0]['fRunStart'])+OFFSET,
+    fjd(runs.iloc[-1]['fRunStop'])+OFFSET 
+    ))
+plt.ylim(1e-1, 1e6)
+
+plt.legend(
+    handles=[plot_0[0], plot_1[0]],
+    loc='lower left')
+
+plt.tight_layout()
+plt.savefig("board_rate_overview_"+night_string+'.png', 
+    dpi=300)
+
+plt.figure()
+plt.title("fHighBoardTriggerRateRatio distribution from {0}".format(night_int))
+plt.hist(runs.fBoardTriggerRateRatioAboveThreshold.values, 
+    bins=np.arange(0,0.6,1./60.), 
+    log=True )
+plt.grid()
+plt.xlabel("fHighBoardTriggerRateRatio")
+plt.savefig("ratio_dist_"+night_string+'.png')