add temp testing script

diff --git a/python-lib/test-data/chip01/foo.py b/python-lib/test-data/chip01/foo.py
new file mode 100644 (file)
index 0000000..7e52b4e
--- /dev/null
+++ b/python-lib/test-data/chip01/foo.py
@@ -0,0 +1,136 @@
+#!/usr/bin/env python
+
+from pylab import *
+
+import os
+from glob import glob
+from random import sample as rand_sample
+
+
+cal_values = []
+cal_outs = []
+cal_nevals = []
+
+infiles = sorted(glob('*.npz'))
+#N_RUNS = min(len(infiles), 8)
+N_RUNS = 0
+sample_runs = sorted(rand_sample(range(len(infiles)), N_RUNS))
+#N_PLOTS = 4
+N_PLOTS = 0
+#sample_channels = sorted(rand_sample(range(48), N_PLOTS))
+sample_channels = range(N_PLOTS)
+#N_COLS = 4
+N_COLS = 0
+nrun = 0
+for infile in infiles:
+#for infile in sorted(glob('*.npz')):
+#for infile in sorted(glob('2012-09-03_1*.npz')):
+    d = np.load(infile)
+
+    #print infile, d.keys()
+
+    guesses = d['guesses']
+    results = d['results']
+    nevals = d['nevals']
+
+    d.close() # close file descriptor
+    
+    if nrun in sample_runs:
+        for i,k in enumerate(sample_channels):
+            g = guesses[:, 0, k]
+            r = 1e3*(2.5/2/2**13)*results[:, 0, k]
+
+            subplot(N_PLOTS, N_COLS, N_COLS*i+1)
+            plot(g[:nevals[0,k]+1], '-')
+            ylim((0, 127))
+            ylabel('Channel %02i-A' % k)
+
+            subplot(N_PLOTS, N_COLS, N_COLS*i+2)
+            plot(r[:nevals[0,k]+1], '-')
+
+    cal_values.append(guesses[-1, :, :])
+
+    # results are zeros after [nevals:]
+    # pick off the last real measurement
+    r = zeros_like(results[-1, :, :])
+    for i in range(r.shape[0]):
+        for j in range(r.shape[1]):
+            r[i, j] = results[nevals[i,j]-1, i, j]
+    cal_outs.append(r)
+
+    map(cal_nevals.append, nevals.flat)
+
+    #cal_outs.append(results[-1, :, :])
+    nrun += 1
+
+cv = array(cal_values)
+co = array(cal_outs)
+
+
+
+
+if 0:
+    figure()
+    for i,k in enumerate(sample_channels):
+        subplot(N_PLOTS, N_COLS, N_COLS*i+3)
+        data = cv[:, 0, k]
+        hist(data, bins=range(128), align='left')
+        xlim((data.min()-1, data.max()+1))
+        xlim((0, 127))
+
+        subplot(N_PLOTS, N_COLS, N_COLS*i+4)
+        data = 1e3*(2.5/2/2**13)*co[:, 0, k]
+        dm = max((abs(data.min()), abs(data.max())))
+        print dm
+        dm = max(dm, 50)
+        hist(data, bins=100, range=(-dm, dm), align='left')
+        xlim((-dm, dm))
+        #ylim((0, 50))
+
+    subplot(N_PLOTS, N_COLS, 1)
+    title('Offset DAC value')
+    subplot(N_PLOTS, N_COLS, (N_PLOTS-1)*N_COLS+1)
+    xlabel('Iteration step')
+
+    subplot(N_PLOTS, N_COLS, 2)
+    title('Vout (mV)')
+    subplot(N_PLOTS, N_COLS, (N_PLOTS-1)*N_COLS+2)
+    xlabel('Iteration step')
+
+    subplot(N_PLOTS, N_COLS, 3)
+    title('Offset DAC histogram')
+    subplot(N_PLOTS, N_COLS, (N_PLOTS-1)*N_COLS+3)
+    xlabel('OTA tuning DAC')
+
+    subplot(N_PLOTS, N_COLS, 4)
+    title('Vout (mV) histogram')
+    subplot(N_PLOTS, N_COLS, (N_PLOTS-1)*N_COLS+4)
+    xlabel('Residual Voos (mV)')
+
+    suptitle('Calibration data from %s\nNruns = %i' %
+            (os.path.basename(os.getcwd()),
+                len(infiles)))
+
+interactive(False)
+
+if 1:
+    figure()
+    data = cv.flatten()
+    hist(data, bins=range(128), align='left')
+    xlabel('OTA tuning DAC value')
+    title('Channel offset tuning histogram\n48x2 channels x %i runs' %
+            (len(infiles),))
+    savefig('caldac-hist.pdf')
+
+
+    figure()
+    data = co.flatten()
+    hist(data, bins=range(-1500, 1500, 10), align='left')
+    xlabel('Tuned channel output offset voltage (mV)')
+    title('Channel offset tuning histogram\n48x2 channels x %i runs' %
+            (len(infiles),))
+    savefig('calout-hist.pdf')
+
+print sample_runs
+print [infiles[s] for s in sample_runs]
+