Finally merging #85

docs/listing_2.py

@@ -16,11 +16,11 @@
 # Image attributes are also stored in this series:
 w_x2 = ser['side','absorption','OD','Gaussian_XW']
 
-# If we want actual measurement data, we'll have to instantiate a Run object:
-run = Run(path)
+# If we want actual measurement data, we'll have to instantiate a Shot object:
+shot = Shot(path)
 
 # Obtaining a trace:
-t, mot_fluorecence = run.get_trace('mot fluorecence')
+t, mot_fluorecence = shot.get_trace('mot fluorecence')
 
 # Now we might do some analysis on this data. Say we've written a
 # linear fit function (or we're calling some other libaries linear
@@ -43,4 +43,4 @@
 
 # We might wish to save this result so that we can compare it across
 # shots in a multishot analysis:
-run.save_result('mot loadrate', c)
+shot.save_result('mot loadrate', c)

docs/source/api/index.rst

@@ -12,4 +12,4 @@ API Reference
    lyse.dataframe_utilities
    lyse.figure_manager
    lyse.tempfile2clipboard
-   lyse.__main__
+   lyse.__main__

docs/source/examples.rst

@@ -24,11 +24,11 @@ An analysis on a single shot
 	# Image attributes are also stored in this series:
 	w_x2 = ser['side','absorption','OD','Gaussian_XW']
 
-	# If we want actual measurement data, we'll have to instantiate a Run object:
-	run = Run(path)
+	# If we want actual measurement data, we'll have to instantiate a Shot object:
+	shot = Shot(path)
 
 	# Obtaining a trace:
-	t, mot_fluorecence = run.get_trace('mot fluorecence')
+	t, mot_fluorecence = shot.get_trace('mot fluorecence')
 
 	# Now we might do some analysis on this data. Say we've written a
 	# linear fit function (or we're calling some other libaries linear
@@ -51,7 +51,7 @@ An analysis on a single shot
 
 	# We might wish to save this result so that we can compare it across
 	# shots in a multishot analysis:
-	run.save_result('mot loadrate', c)
+	shot.save_result('mot loadrate', c)
 
 Single shot analysis with global file opening
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -60,11 +60,11 @@ Single shot analysis with global file opening
 
 	from lyse import *
 
-	# Instantiate Run object and open
+	# Instantiate Shot object and open
 	# Globally opening the shot keeps the h5 file open
 	# This prevents excessive opening and closing of the file
 	# which can slow down the analysis
-	with Run(path).open('r+') as shot:
+	with Shot(path).open('r+') as shot:
 
 		# Obtaining a trace:
 		t, mot_fluorecence = shot.get_trace('mot fluorecence')

docs/source/introduction.rst

@@ -3,7 +3,7 @@ Introduction
 
 **Lyse** is a data analysis system which gets *your code* running on experimental data as it is acquired. It is fundamenally based around the ideas of experimental *shots* and analysis *routines*. A shot is one trial of an experiment, and a routine is a ``Python`` script, written by you, that does something with the measurement data from one or more shots.
 
-Analysis routines can be either *single-shot* or *multi-shot*. This determines what data and functions are available to your code when it runs. A single-shot routine has access to the data from only one shot, and functions available for saving results only to the hdf5 file for that shot. A a multi-shot routine has access to the entire dataset from all the runs that are currently loaded into **lyse**, and has functions available for saving results to an hdf5 file which does not belong to any of the shots---it's a file that exists only to save the "meta results".
+Analysis routines can be either *single-shot* or *multi-shot*. This determines what data and functions are available to your code when it runs. A single-shot routine has access to the data from only one shot, and functions available for saving results only to the hdf5 file for that shot. A a multi-shot routine has access to the entire dataset from all the shots that are currently loaded into **lyse**, and has functions available for saving results to an hdf5 file which does not belong to any of the shots---it's a file that exists only to save the "meta results".
 
 Actually things are far less magical than that. The only enforced difference between a single shot routine and a multi-shot routine is a single variable provided to your code when **lyse** runs it. Your code runs in a perfectly clean ``Python`` environment with this one exception: a variable in the global namespace called ``path``, which is a path to an hdf5 file. If you have told **lyse** that your routine is a singleshot one, then this path will point to the hdf5 file for the current shot being analysed. On the other hand, if you've told **lyse** that your routine is a multishot one, then it will be the path to an h5 file that has been selected in **lyse** for saving results to.