def get_imagefilters(filter_list):
image_filters = []
for filters_item in filter_list:
if type(filters_item) == str:
image_filters.append(filters.get_filter(filters_item))
if type(filters_item) == list:
filter_name = filters_item[0]
params = filters_item[1:]
args = []
kwargs = {}
if len(params) == 1 and type(params[0]) == list:
# ["filtername", ["value1", "value2"]]
args = params[0]
elif len(params) == 1 and type(params[0]) == dict:
# ["filtername", {param1: "value1", "param2": "value2"}]
kwargs = params[0]
else:
# ["filtername", "value1", "value2"]
args = params
_image_filter = filters.get_filter(filter_name)
image_filters.append(
lambda frame: _image_filter(frame, *args, **kwargs)
)
return image_filters
def parse_filter(fltr):
ret = {
'klass': None,
'params': {},
}
ret['klass'] = get_filter(fltr.get('filter', 'dummy'))
ret['params'] = fltr.get('params', {})
return ret
def get_imagefilters(filter_list):
image_filters = []
for filters_item in filter_list:
if type(filters_item) == str:
image_filters.append(filters.get_filter(filters_item))
if type(filters_item) == list:
filter_name = filters_item[0]
params = filters_item[1:]
_args = []
_kwargs = {}
if len(params) == 1 and type(params[0]) == list:
# ["filtername", ["value1", "value2"]]
_args = params[0]
elif len(params) == 1 and type(params[0]) == dict:
# ["filtername", {param1: "value1", "param2": "value2"}]
_kwargs = params[0]
else:
# ["filtername", "value1", "value2"]
_args = params
_image_filter = filters.get_filter(filter_name)
if not _image_filter:
continue
def filter_with_parameters(_image_filter=_image_filter,
_args=_args,
_kwargs=_kwargs,
*args,
**kwargs):
# Using default parameters is neccessary to work with
# a copy of _image_filter, _args and _kwargs instead of
# a reference
args = list(args)
for arg in _args:
args.append(arg)
for key in _kwargs:
if not key in kwargs:
kwargs[key] = _kwargs[key]
return _image_filter(*args, **kwargs)
image_filters.append(filter_with_parameters)
return image_filters
def filter_mod(self):
if issubclass_(self.filter, Filter):
filter = self.filter(self.mean_dens, self.delta_c, self.lnk, self._lnP_0,
**self.filter_params)
elif isinstance(self.filter, basestring):
filter = get_filter(self.filter, rho_mean=self.mean_dens,
delta_c=self.delta_c, lnk=self.lnk, lnp=self._lnP_0,
**self.filter_params)
return filter
def filter_mod(self):
if issubclass_(self.filter, Filter):
filter = self.filter(self.mean_dens, self.delta_c, self.lnk,
self._lnP_0, **self.filter_params)
elif isinstance(self.filter, basestring):
filter = get_filter(self.filter,
rho_mean=self.mean_dens,
delta_c=self.delta_c,
lnk=self.lnk,
lnp=self._lnP_0,
**self.filter_params)
return filter
def get_objects(self,table_name,**kwargs):
""" Get all objects/rows from table
Args
table_name: String. Name of table(model)
filter: String. Type of filter to use on results
Notes:
Queries use ad-hoc filtering so it's expected that results aren't cached (TODO: But it might be worthwhile to do so)
"""
if 'filter' in kwargs:
filter = filters.get_filter(kwargs['filter'])
statement = "SELECT * from {0} WHERE {1} {2} {3}".format(table_name,filter[0],filter[1],filter[2])
else:
statement = "SELECT * from {0}".format(table_name)
print statement
self.execute(statement)
results = self.fetchall()
return results
import numpy as np
from film import get_film_layers
from filters import get_filter
# Films
EBT2 = get_film_layers('EBT2')
EBT3 = get_film_layers('EBT3')
HDV2 = get_film_layers('HDV2')
HD810= get_film_layers('HD810')
# Filters
Al = get_filter('Al', 6)
Fe = get_filter('Fe', 250)
Fe_thick = get_filter('Fe', 500)
def get_SCAP_stack(shot, flatten=True):
if shot < 5193:
print('Shot number too low!')
return []
if shot > 5238:
print ('Shot number too high!')
layers = [
Al,
HDV2, HDV2, HDV2, HDV2,
Fe,
HDV2, EBT3,
Fe,
HDV2, EBT3,
Fe,
#!/usr/bin/env python
import sys
import argparse
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import events
import filters
from collections import defaultdict
from matplotlib.colors import ColorConverter
parser = argparse.ArgumentParser(description='Print histogram of events')
filters.add_all_filters(parser)
args = parser.parse_args()
filter = filters.get_filter(args)
# x_range = (1029553.184, 1029553.190)
#x_range = (1029333.805010, 1029333.825010)
x_range = None
fig, ax = plt.subplots()
palette = {
events.TimelineElement.RUNNING: 'green',
events.TimelineElement.SLEEPING: 'white',
events.TimelineElement.SLEEPING_UNINTERRUPTIBLY: 'lightblue',
events.TimelineElement.PREEMPTED: 'lightgrey',
events.TimelineElement.WOKEN: 'red',
}
rgb_palette = dict((k, ColorConverter().to_rgb(c)) for k, c in palette.iteritems())
