diff --git a/notebooks/LPD/PlotFromCalDB.py b/notebooks/LPD/PlotFromCalDB.py
deleted file mode 100644
index 511f0b23f6da63db1114ba029385691154c2fd3a..0000000000000000000000000000000000000000
--- a/notebooks/LPD/PlotFromCalDB.py
+++ /dev/null
@@ -1,232 +0,0 @@
-import sys
-import warnings
-import os
-import h5py
-import numpy as np
-import matplotlib
-import matplotlib.pyplot as plt
-import matplotlib.ticker as ticker
-import datetime
-import dateutil.parser
-
-import seaborn
-from iCalibrationDB import ConstantMetaData, Constants, Conditions, Detectors, Versions
-from cal_tools.cal_tools import gain_map_files, parse_runs, run_prop_seq_from_path, get_notebook_name, get_dir_creation_date, get_constant_from_db
-from cal_tools.influx import InfluxLogger
-from cal_tools.enums import BadPixels
-from cal_tools.plotting import show_overview, plot_badpix_3d, create_constant_overview
-
-warnings.filterwarnings('ignore')
-matplotlib.use("agg")
-
-
-start_date = "2018-06-25" # date to start investigation interval from
-end_date = "now" # date to end investigation interval at, can be "now"
-interval = 3 # interval for evaluation in days
-detector = "LPD1M1" # detector to investigate
-constants = ["Offset", "Noise"] # constants to plot
-cal_db_interface = "tcp://max-exfl016:8015" # the database interface to use
-bias_voltage = 500
-max_cells = 128
-modules = [3]
-out_folder = "/gpfs/exfel/data/scratch/karnem/test/"
-all_ready_printed = {}
-
-
-detector = detector.upper()
-dclass = "AGIPD" if "AGIPD" in detector else "LPD"
-
-
-if modules[0] == -1:
- modules = list(range(16))
-
-
-def get_constant_from_db(device, constant, condition, empty_constant,
- cal_db_interface, creation_time = None,
- print_once=True):
-
- if device:
- metadata = ConstantMetaData()
- metadata.calibration_constant = constant
- metadata.detector_condition = condition
- if creation_time is None:
- metadata.calibration_constant_version = Versions.Now(device=device)
- else:
- metadata.calibration_constant_version = \
- Versions.Timespan(device=device, start=creation_time)
-
- try:
- print ("Send requiests")
- metadata.retrieve(cal_db_interface, when=creation_time.isoformat())
- if constant.name not in all_ready_printed or not print_once:
- all_ready_printed[constant.name] = True
- print("{} was injected on: {}".format(constant.name,
- metadata.calibration_constant_version.begin_at))
- return constant.data
- except Exception as e:
- return empty_constant
- else:
- return empty_constant
-
-
-dt = dateutil.parser.parse(start_date)
-end = datetime.datetime.now() if end_date.upper() == "NOW" else dateutil.parser.parse(end_date)
-step = datetime.timedelta(days=interval)
-
-det = getattr(Detectors, detector)
-dconstants = getattr(Constants, dclass)
-ret_constants = {}
-while dt < end:
- creation_time = dt
- print("Retreiving data from: {}".format(creation_time.isoformat()))
- for const in constants:
- if not const in ret_constants:
- ret_constants[const] = {}
- if (const in ["Offset", "Noise"] or "DARK" in const.upper()):
- dcond = Conditions.Dark
- else:
- Conditions.Illuminated
-
- for i in modules:
- qm = "Q{}M{}".format(i//4+1, i%4+1)
- cdata = get_constant_from_db(getattr(det, qm),
- getattr(dconstants, const)(),
- getattr(dcond, dclass)(memory_cells=max_cells,
- bias_voltage=bias_voltage),
- None,
- cal_db_interface,
- creation_time=creation_time)
-
- print("Found constant {}: {}".format(const, cdata is not None))
-
- if not qm in ret_constants[const]:
- ret_constants[const][qm] = []
-
- if cdata is not None:
- carr = np.zeros((5, max_cells, 3))
- carr_glob = np.zeros((5, 3))
- carr_px = np.zeros((cdata.shape[0], max_cells, 3, 2))
- for g in range(3):
- td = np.nanmean(cdata[...,g], axis=(0,1))
- print (td.shape)
- carr[0,:td.shape[0],g] = td
-
- td = np.nanmedian(cdata[...,g], axis=(0,1))
- carr[1,:td.shape[0],g] = td
-
- td = np.nanmin(cdata[...,g], axis=(0,1))
- carr[2,:td.shape[0],g] = td
-
- td = np.nanmax(cdata[...,g], axis=(0,1))
- carr[3,:td.shape[0],g] = td
-
- td = np.nanstd(cdata[...,g], axis=(0,1))
- carr[4,:td.shape[0],g] = td
-
- td = np.nanmean(cdata[...,g])
- carr_glob[0, g] = td
-
- td = np.nanmedian(cdata[...,g])
- carr_glob[1, g] = td
-
- td = np.nanmin(cdata[...,g])
- carr_glob[2, g] = td
-
- td = np.nanmax(cdata[...,g])
- carr_glob[3, g] = td
-
- td = np.nanstd(cdata[...,g])
- carr_glob[3, g] = td
-
- carr_px[...,g, 0] = np.nanmedian(cdata[...,g], axis=0)
- carr_px[...,g, 1] = np.nanmedian(cdata[...,g], axis=1)
-
- ret_constants[const][qm].append((creation_time,
- (carr, carr_glob, carr_px)))
-
- dt += step
-
-
-types = ["mean", "median", "min", "max", "std"]
-colors = ["red", "green", "orange", "blue"]
-skip = [False, False, False, False, False]
-
-# loop over constat type
-for const, modules in ret_constants.items():
- fig = plt.figure(figsize=(15,7))
- tt = 0
- print (const)
-
- # loop over type of stat parameter
- for typ in range(len(types)):
- if skip[typ]:
- continue
- ax = plt.subplot2grid((np.count_nonzero(~np.array(skip)), 1), (tt, 0))
-
- # loop over modules
- for mod, data in modules.items():
- ctimes, cd = list(zip(*data))
- pmm, glob, _ = list(zip(*cd))
- pma = np.array(pmm)
- ga = np.array(glob)
- d = pma[:,typ,:,:]
-
- if np.allclose(d, 0):
- continue
- dd = pma[:,typ,:,:]#-pma[0,typ,:,:])/pma[0,typ,:,:]
- y = dd.flatten()
- x = np.repeat(np.array(ctimes)[:,None],
- dd[0,:,:].size, axis=1).flatten()
- hue = np.repeat(np.array(['gain 0', 'gain 1', 'gain 2'])[:,None],
- dd[:,:,0].size, axis=1).swapaxes(0,1).flatten()
- seaborn.violinplot(x, y, hue, scale="width", dodge=False, saturation=0.7)
-
- #ax.set_ylim(-0.25, .25)
-
- if typ != len(types)-1:
- ax.axes.get_xaxis().set_visible(False)
- else:
- def format_date(x, pos=None):
- return ctimes[x].strftime('%d-%m')
- ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
- ax.set_xlabel("Date")
- ax.set_ylabel("{}".format(types[typ]))
-
- tt += 1
- plt.subplots_adjust(wspace=0.2, hspace=0.2)
-
- if out_folder != "":
- fig.savefig("{}/{}_time_development.pdf".format(out_folder, const),
- bbox_inches='tight')
-
-
- fig = plt.figure(figsize=(15,7))
- ax = plt.subplot2grid((1, 1), (0, 0))
-
- # loop over modules
- for mod, data in modules.items():
- ctimes, cd = list(zip(*data))
- _, _, px = list(zip(*cd))
- px = np.array(px)
- print (px.shape)
- y = px[:,:,5,0,:].flatten()
- x = np.repeat(np.array(ctimes)[:,None],
- px[0,:,5,0,:].size, axis=1).flatten()
- hue = np.repeat(np.array(['px','py'])[:,None], px[:,:,5,0,0].size,
- axis=1).swapaxes(0,1).flatten()
-
- seaborn.violinplot(x, y, hue, palette="muted", split=True)
-
- def format_date(x, pos=None):
- return ctimes[x].strftime('%d-%m')
- ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
- ax.set_xlabel("Date")
- ax.set_ylabel("Median over pixels")
-
- plt.subplots_adjust(wspace=0.2, hspace=0.2)
-
- if out_folder != "":
- fig.savefig("{}/{}_pxtime_development.pdf".format(out_folder, const),
- bbox_inches='tight')
-
-