added readme

README.md

@@ -1,2 +1,78 @@
 # dispersiveXanes
 
+```python
+# BEFORE GETTING STARTED
+# 1. if at LCLS load the anaconda session
+# source ~marcoc/setups/ana-marco3k-setup.sh
+# 2. start ipython
+# ipython3
+
+# there are two files:
+# 1. alignment.py (deals with images)
+# 2. xanes_analyzeRun.py (deals with run and images reading)
+
+# the experiment name is defined in xanes_analyzeRun.py
+# change to the right value before loading
+
+%matplotlib nbagg
+import matplotlib
+import matplotlib.pylab as plt
+matplotlib.style.use("ggplot")
+import pprint
+import numpy as np
+np.warnings.simplefilter('ignore')
+
+import xanes_analyzeRun
+import alignment
+
+#Doing first alignment on "hole"
+
+# define starting parameters for analysis; passed directly to iminuit so things like
+# limits, or fix_scalex=True, etc. can be used
+pars = dict( scalex = 0.6, intensity = 0.1, iblur1=2,fix_iblur1 = False )
+# default parameters can be found in alignment.g_fit_default_kw
+# you can have a look by uncommenting the following line:
+# pprint.pprint(alignment.g_fit_default_kw)
+
+# define the run object
+#### NOTE : for mec run swapx=True,swapy=False
+r = xanes_analyzeRun.AnalyzeRun(190,initAlign=pars,swapx=True,swapy=False)
+
+# data are d.spec1 and d.spec2 (spec1 is the one **upbeam**)
+# align one shot
+
+# show = True: show only output; showInit=True: show also starting parameters
+r0fit=r.doShot(shot=0,calib=0,showInit=True,doFit=True)
+
+# save as default transformation for run (used when reloading without initAlign keywork)
+r.saveTransform();
+
+# do more shots without fitting (using last r.initAlign)
+# the return value is a list with lots of stuff for each shot
+res = r.doShots(slice(100),doFit=False)
+print(list(res.keys()))
+
+print(list(res["parameters"].keys()))
+
+alignment.plotRatios(res["ratio"])
+ref = np.nanmedian(res["ratio"],axis=0)
+trash = plt.xlim(400,600)
+trash = plt.ylim(0,2)
+
+
+# analyze another run using previous alignment
+
+rShot = xanes_analyzeRun.AnalyzeRun(192,initAlign="mecl3616_init_pars/run0190_transform.npy",swapx=True,swapy=False)
+
+out = rShot.doShots(slice(0,5))
+ratios = out["ratio"]
+plt.figure()
+for i,r in enumerate(ratios):
+  plt.plot(r/ref,label="Shot %d"%i)
+trash = plt.ylim(0,1)
+trash = plt.legend(loc=2)
+
+# save results in hdf file for Andy's happiness
+rShot.save(overwrite=True)
+
+```