diff --git a/doc/BOZ analysis part I parameters determination.ipynb b/doc/BOZ analysis part I parameters determination.ipynb
index 82f8741b4c106321dbadebfe1404186de0fdafb1..0ccc5807432373fe9ff6c5d60aa996794f337ddc 100644
--- a/doc/BOZ analysis part I parameters determination.ipynb
+++ b/doc/BOZ analysis part I parameters determination.ipynb
@@ -48,7 +48,9 @@
"darkrun = 478\n",
"run = 477\n",
"module = 15\n",
- "gain = 0.5"
+ "gain = 0.5\n",
+ "sat_level = 500\n",
+ "rois_th = 1"
]
},
{
@@ -174,9 +176,11 @@
"metadata": {},
"outputs": [],
"source": [
- "h, f = boz.inspect_histogram(params.proposal, params.run, params.module,\n",
+ "h, f = boz.inspect_histogram(params.arr,\n",
+ " params.arr_dark,\n",
" mask=params.get_mask() #, extra_lines=True\n",
" )\n",
+ "f.suptitle(f'p:{params.proposal} r:{params.run} d:{params.darkrun}')\n",
"f.savefig(path+f'p{params.proposal}-r{params.run}-d{params.darkrun}-histogram.png', dpi=300)"
]
},
@@ -187,18 +191,6 @@
"adding guide to the eye"
]
},
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "ax = f.gca()\n",
- "pf = np.polyfit([60, 220], [7, 4], 1)\n",
- "ax.plot([40, 400], 2*10**np.polyval(pf, [40, 400]))\n",
- "ax.plot([40, 400], 0.25*2*10**np.polyval(pf, [40, 400]))"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -212,7 +204,7 @@
"metadata": {},
"outputs": [],
"source": [
- "params.rois_th = 4\n",
+ "params.rois_th = rois_th\n",
"params.rois = boz.find_rois_from_params(params)"
]
},
@@ -265,7 +257,7 @@
"metadata": {},
"outputs": [],
"source": [
- "params.sat_level = 511\n",
+ "params.sat_level = sat_level\n",
"res = boz.average_module(params.arr, dark=dark,\n",
" ret='mean', mask=params.get_mask(), sat_roi=params.rois['sat'],\n",
" sat_level=params.sat_level)\n",
diff --git a/scripts/boz_parameters_job.sh b/scripts/boz_parameters_job.sh
index a8c8013f123d31420b0a4f9f3c4d4e3f13d86edc..0d6dbedef745aa4f30c3923fb7d1571852ea2ce5 100644
--- a/scripts/boz_parameters_job.sh
+++ b/scripts/boz_parameters_job.sh
@@ -9,6 +9,7 @@ PROPOSAL=2619
DARK=$1
RUN=$2
GAIN=$3
+ROISTH=${4:-1}
MODULE=15
source /etc/profile.d/modules.sh
@@ -16,7 +17,7 @@ module load exfel
module load exfel_anaconda3/1.1
echo processing run $RUN
-mkdir r$RUN
-papermill 'BOZ analysis part I parameters determination.ipynb' r$RUN/output.ipynb \
+mkdir ../../processed_runs/r$RUN
+papermill 'BOZ analysis part I parameters determination.ipynb' ../../processed_runs/r$RUN/output.ipynb \
-p proposal $PROPOSAL -p darkrun $DARK -p run $RUN -p module $MODULE \
- -p gain $GAIN -k xfel
+ -p gain $GAIN -p rois_th $ROISTH -k xfel
diff --git a/src/toolbox_scs/routines/boz.py b/src/toolbox_scs/routines/boz.py
index 398dc703e9d649359566fad9b4ccc82bc7e3bbab..e208e61347800c610086d1a978d4d7d0c825fe06 100644
--- a/src/toolbox_scs/routines/boz.py
+++ b/src/toolbox_scs/routines/boz.py
@@ -497,29 +497,18 @@ def inspect_rois(data_mean, rois, threshold=None, allrois=False):
return fig
-def histogram_module(proposalNB, runNB, moduleNB, mask=None):
+def histogram_module(arr, mask=None):
"""Compute a histogram of the 9 bits raw pixel values over a module.
Inputs
------
- proposalNB: proposal number
- runNB: run number
- moduleNB: module number
+ arr: dask array of reshaped dssc data (trainId, pulseId, x, y)
mask: optional bad pixel mask
Returns
-------
histogram
"""
- run = open_run(proposal=proposalNB, run=runNB)
-
- # DSSC
- source = f'SCS_DET_DSSC1M-1/DET/{moduleNB}CH0:xtdf'
- key = 'image.data'
-
- arr = run[source, key].dask_array()
- arr = arr.rechunk((100, -1, -1, -1))
-
if mask is not None:
w = da.repeat(da.repeat(da.array(mask[None, None, :, :]),
arr.shape[1], axis=1), arr.shape[0], axis=0)
@@ -529,30 +518,37 @@ def histogram_module(proposalNB, runNB, moduleNB, mask=None):
return da.bincount(arr.ravel(), minlength=512).compute()
-def inspect_histogram(proposalNB, runNB, moduleNB,
- mask=None, extra_lines=False):
+def inspect_histogram(arr, arr_dark=None, mask=None, extra_lines=False):
"""Compute and plot a histogram of the 9 bits raw pixel values.
Inputs
------
- proposalNB: proposal number
- runNB: run number
- moduleNB: module number
+ arr: dask array of reshaped dssc data (trainId, pulseId, x, y)
+ arr: dask array of reshaped dssc dark data (trainId, pulseId, x, y)
mask: optional bad pixel mask
extra_lines: boolean, default False, plot extra lines at period values
Returns
-------
- histogram
+ (h, hd): histogram of arr, arr_dark
figure
"""
- h = histogram_module(proposalNB, runNB, moduleNB, mask=mask)
from matplotlib.ticker import MultipleLocator
f = plt.figure(figsize=(6, 3))
- plt.plot(np.arange(2**9), h, marker='o',
+ h = histogram_module(arr, mask=mask)
+ Sum_h = np.sum(h)
+ plt.plot(np.arange(2**9), h/Sum_h, marker='o',
ms=3, markerfacecolor='none', lw=1)
+ if arr_dark is not None:
+ hd = histogram_module(arr_dark, mask=mask)
+ Sum_hd = np.sum(hd)
+ plt.plot(np.arange(2**9), hd/Sum_hd, marker='o',
+ ms=3, markerfacecolor='none', lw=1, c='k', alpha=.5)
+ else:
+ hd = None
+
if extra_lines:
for k in range(50, 271):
if not (k - 2) % 8:
@@ -563,17 +559,14 @@ def inspect_histogram(proposalNB, runNB, moduleNB,
plt.axvline(k, c='r', alpha=0.3, ls='--')
plt.axvline(271, c='C1', alpha=0.5, ls='--')
- plt.fill_between(np.arange(2**9)[30:51], h[30:51], 1, alpha=0.5)
- plt.ylim([1, None])
plt.xlim([0, 2**9-1])
plt.yscale('log')
plt.axes().xaxis.set_minor_locator(MultipleLocator(10))
plt.xlabel('DSSC pixel value')
- plt.ylabel('counts')
- plt.title(f'p{proposalNB} run {runNB}')
+ plt.ylabel('count frequency')
- return h, f
+ return (h, hd), f
def load_dssc_module(proposalNB, runNB, moduleNB=15,