def __init__(self, conf=None, props=None):
""" Input: conf = output properties
props = input properties """
NodeSet.__init__(self)
ElementSet.__init__(self)
self.groups = []
self.groupNames = IndexedOrderedDict()
self.ngroups = 0
if conf and props:
# Get Props
myProps = props.getProps("mesh")
myConf = conf.makeProps("mesh")
self.path = myProps.get("file")
self.type = myProps.get("type", "Gmsh")
self.rank = myProps.get("rank", 2)
self.doElemGroups = myProps.get("doElemGroups", False)
myConf.set("file", self.path)
myConf.set("type", self.type)
myConf.set("rank", self.rank)
myConf.set("doElemGroups", self.doElemGroups)
# Read Mesh
self.readMesh(self.type, self.path, self.rank, self.doElemGroups)
# Initialize DofSpace
DofSpace.__init__(self, self.nnod, self.rank)
def __init__(self, verbose=False, handle_errors=False):
"""See help(AnalysisHandler)."""
self.fns_to_run = []
self.fn_params_list = []
self.fn_kwargs_list = []
self.results = IndexedOrderedDict()
self.verbose = verbose
self.handle_errors = handle_errors
self._was_error = False
def __init__(self, year_of_advent, calendar="ACNA_BCP2019"):
self.calendar = Calendar.objects.filter(abbreviation=calendar).first()
self.start_year = year_of_advent
self.end_year = year_of_advent + 1
self.dates = IndexedOrderedDict()
start_date = advent(year_of_advent)
end_date = advent(year_of_advent + 1) - timedelta(days=1)
self.start_date = start_date
self.end_date = end_date
self.seasons = self._get_seasons()
self.season_tracker = None
# create each date
for single_date in self.daterange(start_date, end_date):
name = single_date.strftime("%Y-%m-%d")
self.dates[name] = CalendarDate(single_date,
calendar=self.calendar,
year=self)
# add commemorations to date
commemorations = (Commemoration.objects.select_related(
"rank", "cannot_occur_after__rank").filter(
calendar__abbreviation=calendar).all())
already_added = []
for commemoration in commemorations:
if not commemoration.can_occur_in_year(self.start_year):
continue
try:
self.dates[commemoration.initial_date_string(
self.start_year)].add_commemoration(commemoration)
already_added.append(commemoration.pk)
except KeyError:
pass
for key, calendar_date in self.dates.items():
# seasons
self._set_season(calendar_date)
# apply transfers
transfers = calendar_date.apply_rules()
new_date = (calendar_date.date +
timedelta(days=1)).strftime("%Y-%m-%d")
if new_date in self.dates.keys():
self.dates[new_date].required = transfers + self.dates[
new_date].required
SetNamesAndCollects(self)
def unique_pattern_counter(reading):
"""Returns an IndexedOrderedDict of unique sub-patterns in a reading"""
counter = IndexedOrderedDict()
idx = 0
for row in reading:
if counter.get(str(idx) + '_' + convert_row_to_key(row)):
counter[str(idx) + '_' + convert_row_to_key(row)] += 1
else:
idx += 1
counter[str(idx) + '_' + convert_row_to_key(row)] = 1
return counter
def __init__(self, ordering=None):
"""
Constructs a HashedParameterArray
Args:
ordering (list): initial ordering of hashable
objects to be stored in the array
"""
# Construct IndexedOrderedDict
self._iod = IndexedOrderedDict()
if ordering:
self.extend(ordering)
class PaletteParser():
paletteDict = IndexedOrderedDict()
regexp = r"\D+(?P<shadeNumber>\d)\D+#(?P<hexValue>\S{6})\D+(?P<rgbValue>\d+\D+\d+\D+\d+)\D+(?P<rgbaValue>\d+\D+\d+\D+\d+\D+\d+)"
def parseDocument(self, filePath):
paletteFile = open(filePath, 'r')
prog = re.compile(self.regexp)
paletteDict = IndexedOrderedDict()
sectionDict = IndexedOrderedDict()
shadeDict = IndexedOrderedDict()
section = ''
shade = ''
for line in paletteFile:
if "*** Primary color:" in line:
section = 'primary'
sectionDict = IndexedOrderedDict()
elif "*** Secondary color (1):" in line:
section = 'secondary_1'
sectionDict = IndexedOrderedDict()
elif "*** Secondary color (2):" in line:
section = 'secondary_2'
sectionDict = IndexedOrderedDict()
elif "*** Complement color:" in line:
section = 'complementary'
sectionDict = IndexedOrderedDict()
# only if a section has been detected, the line is not empty and it's not a comment
elif line != "" and "#####" not in line:
res = prog.match(line)
if res:
shadeNum = res.group('shadeNumber')
shadeDict['hex'] = res.group('hexValue')
shadeDict['rgb'] = res.group('rgbValue')
shadeDict['rgba'] = res.group('rgbaValue')
sectionDict[shadeNum] = shadeDict
shadeDict = IndexedOrderedDict()
if section != "":
paletteDict[section] = sectionDict
# store changes
self.paletteDict = paletteDict
def performance_iodict_build():
#tag access
global dt_root, max_items
dt = IndexedOrderedDict()
#append itertree with items
for i in range(max_items):
dt['%i' % i] = 0
dt_root = dt
def f_jumping_modulo(n, m=10):
idxs = list(range(1, n*m+1))
# vals_mod = np.arange(0, n) % m
vals = IndexedOrderedDict([(i, -1) for i in range(1, n*m+1)]) # {i: -1 for i in range(1, n*m+1)}
vals_mod = [i for j in range(1, 30+1) for i in range(0, j)]
smallest_idx = 0
largest_idx = 0
idx_now = 0
# for i, v in enumerate(vals_mod[:50]):
j = 1
max_reached = False
while not max_reached:
for v in range(j-1, -1, -1):
# for v in range(0, j):
if v > idx_now:
idx_now += v
else:
idx_now -= v
if idx_now >= len(idxs):
max_reached = True
break
idx = idxs.pop(idx_now)
vals[idx] = v
print("idx_now: {}, idx: {}, v: {}".format(idx_now, idx, v))
if smallest_idx < idxs[0]:
smallest_idx = idxs[0]
# if largest_idx < idx:
# largest_idx = idx
# lst_temp = list(vals.values())[:largest_idx]
# print("i: {}, lst_temp:\n{}".format(i, lst_temp))
j += 1
lst = list(vals.values())[:smallest_idx-1]
# print("lst: {}".format(lst))
# print("idxs: {}".format(idxs))
# arr = np.array(lst[:smallest_idx-1]) # % m
# arr = np.array(lst[:smallest_idx-1]) # % m
return lst
def treatment_create(request):
if request.method == 'POST':
form = TxAttendanceForm(request.POST)
else:
form = TxAttendanceForm()
context = IndexedOrderedDict()
context['treatment'] = form.instance
context = add_forms_to_context((form,), context)
return save_ajax_form(request, context=context,
form_template='treatment/includes/partial_treatment_create.html',
list_template='treatment/includes/partial_treatment_list.html')
def treatment_update(request, pk):
treatment = get_object_or_404(TxAttendance, pk=pk)
if request.method == 'POST':
form = TxAttendanceForm(request.POST, instance=treatment)
else:
form = TxAttendanceForm(instance=treatment)
context = IndexedOrderedDict()
context['treatment'] = form.instance
context = add_forms_to_context((form,), context)
return save_ajax_form(request, context=context,
form_template='treatment/includes/partial_treatment_update.html',
list_template='treatment/includes/partial_treatment_list.html')
def calculate_rgb_pixs(self):
print("Getting all data in pix_float array")
shape = self.arr_xy_real_imag.shape + (3, )
self.pixs1_dict = IndexedOrderedDict([
("f", np.ones(shape)),
("f_mod", np.ones(shape)),
("angle", np.ones(shape)),
("abs", np.ones(shape)),
("abs_mod", np.ones(shape)),
("x", np.ones(shape)),
("x_mod", np.ones(shape)),
("y", np.ones(shape)),
("y_mod", np.ones(shape)),
])
self.pixs1_dict["f"][:, :, 0] = self.arrs["angle"]
self.pixs1_dict["f"][:, :, 2] = self.arrs["abs"] * 1 / 3 + 2 / 3
self.pixs1_dict["f_mod"][:, :, 0] = self.arrs["angle"]
self.pixs1_dict["f_mod"][:, :, 2] = self.arrs["abs_mod"]
keys = ["angle", "abs", "abs_mod", "x", "x_mod", "y", "y_mod"]
for key in keys:
self.pixs1_dict[key][:, :, 0] = self.arrs[key]
hsv_to_rgb_vectorized = np.vectorize(colorsys.hsv_to_rgb)
print("Convert hsv to rgb and convert to uint8")
self.pixs1_dict_rgb = IndexedOrderedDict()
for key, value in self.pixs1_dict.items():
pix_float_rgb = np.dstack(
hsv_to_rgb_vectorized(value[..., 0], value[..., 1], value[...,
2]))
self.pixs1_dict_rgb[key] = (pix_float_rgb * 255.9).astype(np.uint8)
self.pixs1 = [v for v in self.pixs1_dict_rgb.values()]
self.imgs_orig = [Image.fromarray(pix.copy()) for pix in self.pixs1]
def __init__(self, datasets, variable_activities=False):
self.samples = IndexedOrderedDict()
self.samples_file_descriptors = []
self.variable_activities = variable_activities
for i, dataset in enumerate(datasets, start=1):
self.samples_file_descriptors.append(open(dataset, 'r'))
d = csv.reader(self.samples_file_descriptors[i - 1])
self.header = next(d)
self.samples['sample' + str(i)] = d
self.extract_all_labels()
self.reset_file_descriptors()
self.attach_readings_to_labels()
def objective_update(request, pk):
objectives = get_object_or_404(Objectives, pk=pk)
if request.method == 'POST':
form = ObjectivesForm(request.POST, instance=objectives)
else:
form = ObjectivesForm(instance=objectives)
context = IndexedOrderedDict()
context['objectives'] = form.instance
context = add_forms_to_context((form,), context)
return save_ajax_form(request, context=context,
form_template='treatment/includes/partial_objectives_update.html',
list_template='treatment/includes/partial_objectives_list.html')
class TaburuState(State):
def __init__(self):
self.parameters = IndexedOrderedDict()
self.methods = IndexedOrderedDict()
def apply(self, event):
if isinstance(event, ParametersAdded):
if event.table_name in self.parameters:
self.parameters[event.table_name].append(event.parameters)
else:
self.parameters[event.table_name] = ParameterTable(
event.parameters)
elif isinstance(event, MethodAdded):
if self.methods.get(event.name) is None:
self.methods[event.name] = event.parameter_indices
else:
print("Method name already exists")
return False
return True
def __str__(self):
return self.__repr__()
def __repr__(self):
parameters = [
'{} {}: {}'.format(n, parameter_name, len(table))
for n, (parameter_name,
table) in enumerate(self.parameters.items())
]
methods = [
"{}: {}".format(method_name, parameters)
for method_name, parameters in self.methods.items()
]
output = "Parameters:\n "
output += "\n ".join(parameters)
output += "\nMethods:\n "
output += "\n ".join(methods)
return output
def court_date_create(request):
if request.method == 'POST':
form = CourtDateForm(request.POST)
else:
form = CourtDateForm()
context = IndexedOrderedDict()
context['court_date'] = form.instance
context = add_forms_to_context((form, ), context)
return save_ajax_form(
request,
context=context,
list_template='court/includes/partial_court_list.html',
form_template='court/includes/partial_court_create.html')
def court_date_update(request, pk):
court = get_object_or_404(CourtDates, pk=pk)
if request.method == 'POST':
form = CourtDateForm(request.POST, instance=court)
else:
form = CourtDateForm(instance=court)
context = IndexedOrderedDict()
context['court_date'] = form.instance
context = add_forms_to_context((form, ), context)
return save_ajax_form(
request,
context=context,
list_template='court/includes/partial_court_list.html',
form_template='court/includes/partial_court_update.html')
def __init__(self, year):
first_year = year - 1
second_year = year
first_year = ChurchYear(first_year)
second_year = ChurchYear(second_year)
dates = IndexedOrderedDict(
list(first_year.dates.items()) + list(second_year.dates.items()))
base = datetime(year, 1, 1)
date_list = [base + timedelta(days=x) for x in range(0, 365)]
self.dates = [dates[date.strftime("%Y-%m-%d")] for date in date_list]
def client_note(request, pk):
client = get_object_or_404(Client, pk=pk)
if request.method == 'POST':
form = NoteForm(request.POST, initial={'note_type': 'General'})
else:
form = NoteForm(initial={'note_type': 'General'})
context = IndexedOrderedDict()
context['client'] = client
context['forms'] = {'note_form': form}
return save_ajax_form(
request,
list_template='intake/includes/partial_client_list.html',
form_template='intake/includes/partial_client_note.html',
context=context)
def calculate_arrs(self):
print("Calculate self.arr_f and self.arr_scales")
self.arr_f, self.arr_scales = np.vectorize(self.f)(
self.arr_xy_real_imag)
print("Calculate arr")
arr_angle = np.angle(self.arr_f)
idx = arr_angle < 0
arr_angle[idx] = arr_angle[idx] + np.pi * 2
print("np.min(arr_angle): {}".format(np.min(arr_angle)))
print("np.max(arr_angle): {}".format(np.max(arr_angle)))
arr_angle_norm = arr_angle / (np.pi * 2)
print("np.min(arr_angle_norm): {}".format(np.min(arr_angle_norm)))
print("np.max(arr_angle_norm): {}".format(np.max(arr_angle_norm)))
print("Calculate abs")
arr_abs = np.abs(self.arr_f)
arr_abs_mod = arr_abs * self.arr_scales
arr_abs_norm = arr_abs / np.max(arr_abs)
arr_abs_mod_norm = arr_abs_mod / np.max(arr_abs_mod)
print("Calculate x and y")
f_norm_axis = lambda v: (lambda v2: v / np.max(v))(v - np.min(v))
arr_x = self.arr_f.real
arr_y = self.arr_f.imag
arr_x_mod = arr_x * self.arr_scales
arr_y_mod = arr_y * self.arr_scales
arr_x_norm = f_norm_axis(arr_x)
arr_y_norm = f_norm_axis(arr_y)
arr_x_mod_norm = f_norm_axis(arr_x_mod)
arr_y_mod_norm = f_norm_axis(arr_y_mod)
self.arrs = IndexedOrderedDict([
("angle", arr_angle_norm),
("abs", arr_abs_norm),
("abs_mod", arr_abs_mod_norm),
("x", arr_x_norm),
("x_mod", arr_x_mod_norm),
("y", arr_y_norm),
("y_mod", arr_y_mod_norm),
])
def court_date_note(request, pk):
client = get_object_or_404(Client, pk=pk)
initial = {'client': client, 'note_type': 'Court'}
if request.method == 'POST':
form = NoteForm(request.POST, initial=initial)
else:
form = NoteForm(initial=initial)
context = IndexedOrderedDict()
context['court_date'] = form.instance
context['client'] = client
context = add_forms_to_context((form, ), context)
return save_ajax_form(
request,
context=context,
list_template='court/includes/partial_court_list.html',
form_template='intake/includes/partial_client_note.html')
def client_create(request):
"""
Handle GET/POST requests and instantiate forms.
"""
if request.method == 'POST':
client_form = ClientForm(request.POST)
referral_form = ReferralForm(request.POST)
else:
client_form = ClientForm()
referral_form = ReferralForm()
forms = (client_form, referral_form)
context = IndexedOrderedDict()
context['client'] = client_form.instance
context = add_forms_to_context(forms, context)
return save_ajax_form(
request,
context=context,
list_template='intake/includes/partial_client_list.html',
form_template='intake/includes/partial_client_create.html')
def parse_video_list(video_list_file):
"""
This function parses the video list.
We assume the video list is in the following format.
So there should be not be any space in the video directory names
=======
num_videos
video_0_directory video_0_num_frames (video_0_label)
video_1_directory video_1_num_frames (video_1_label)
video_2_directory video_2_num_frames (video_2_label)
...
...
=======
(labels) are optional
"""
video_dict = IndexedOrderedDict()
if hasattr(video_list_file, 'read'):
lst_file = video_list_file.read().split('\n')
elif isinstance(video_list_file, str):
lst_file = open(video_list_file)
else:
raise TypeError('incorrect type of video list file!')
items = [x.strip().split() for x in lst_file]
print(items[0])
num_videos = int(items[0][0])
for it in items[1:]:
video_key = it[0]
video_num_frame = int(it[1])
video_path = video_key
# write the video record to the indexedOrderedDict
video_dict[video_key] = (video_path, video_num_frame)
assert num_videos == len(video_dict)
print("all videos indexed. got {} videos".format(len(video_dict)))
return video_dict
def client_evaluate(request, pk):
"""
"""
referral = get_object_or_404(Referral, pk=pk)
decisions = referral.decisions
if request.method == 'POST':
forms = (DecisionForm(request.POST, instance=decision)
for decision in decisions)
else:
forms = (DecisionForm(instance=decision) for decision in decisions)
context = IndexedOrderedDict()
context['client'] = referral.client
context['referral'] = referral
context['forms'] = forms
return save_ajax_form(
request,
context=context,
list_template='intake/includes/partial_client_list.html',
form_template='intake/includes/partial_client_evaluate.html')
def client_update(request, pk):
"""
"""
client = get_object_or_404(Client, pk=pk)
if request.method == 'POST':
client_form = ClientForm(request.POST, instance=client)
referral_form = ReferralForm(request.POST, instance=client.referral)
else: # GET Request (loadForm)
client_form = ClientForm(instance=client)
referral_form = ReferralForm(instance=client.referral)
forms = (client_form, referral_form)
context = IndexedOrderedDict()
context['client'] = client
context = add_forms_to_context(forms, context)
return save_ajax_form(
request,
context=context,
list_template='intake/includes/partial_client_list.html',
form_template='intake/includes/partial_client_update.html')
def __init__(self):
self.parameters = IndexedOrderedDict()
self.methods = IndexedOrderedDict()
import os
from indexed import IndexedOrderedDict
clear = lambda :os.system('cls')
d={1:'One',2:'Two',3:'Three'}
ix = IndexedOrderedDict(sorted(d.items(),key=lambda t:t[0]))
def generateIndexedOrderedDict(self):
return IndexedOrderedDict(
sorted(self.rom_val_dict.items(), key=lambda t: t[0]))
def reset_results(self):
"""Reset the results."""
self.results = IndexedOrderedDict()
import sqlalchemy as sql
import sqlalchemy.orm as orm
from sqlalchemy.ext.declarative import declarative_base
DeclarativeBase = declarative_base()
NIB_URL = 'https://kartverket.maplytic.no/tile/_nib/{zoom}/{x}/{y}.jpeg'
TOPO4_URL = 'https://opencache.statkart.no/gatekeeper/gk/gk.open_gmaps?layers=topo4&zoom={zoom}&x={x}&y={y}'
PROJECTS = IndexedOrderedDict([
('DTM50', projects.DigitalHeightModel(key='DTM50', name='Terrain model (50 m)')),
('DTM10', projects.DigitalHeightModel(key='DTM10', name='Terrain model (10 m)')),
('DTM1', projects.DigitalHeightModel(key='DTM1', name='Terrain model (1 m)')),
('DOM50', projects.DigitalHeightModel(key='DOM50', name='Object model (50 m)')),
('DOM10', projects.DigitalHeightModel(key='DOM10', name='Object model (10 m)')),
('DOM1', projects.DigitalHeightModel(key='DOM1', name='Object model (1 m)')),
('NIB', projects.TiledImageModel(key='NIB', name='Norge i bilder', url=NIB_URL)),
('TOPO4', projects.TiledImageModel(key='TOPO4', name='Karverket Topo4', url=TOPO4_URL)),
])
filesystem.create_directories(project.key for project in PROJECTS.values())
class Polygon(DeclarativeBase):
"""ORM representation of a polygon."""
__tablename__ = 'polygon'
id = sql.Column(sql.Integer, primary_key=True)
name = sql.Column(sql.String, nullable=False)
class AnalysisHandler(object):
"""
Hold functions to run and the parameters to use for them.
Attributes
----------
fns_to_run : list of functions
The functions to run
fn_param_list : list of tuples
The arguments to pass to these functions.
The arguments are passed in order, so these are positional.
fn_kwargs_list : list of dicts
Keyword arguments to pass to the functions to run.
results : indexed.IndexedOrderedDict
The results of the function calls
verbose : bool
Whether to print more information while running the functions.
handle_errors : bool
Whether to handle errors during runtime of underlying functions,
or to crash on error.
Parameters
----------
verbose : bool, optional
Sets the value of the verbose attribute, defaults to False.
handle_errors : bool, optional
Sets the value of the handle_errors attribute, defaults to False.
"""
def __init__(self, verbose=False, handle_errors=False):
"""See help(AnalysisHandler)."""
self.fns_to_run = []
self.fn_params_list = []
self.fn_kwargs_list = []
self.results = IndexedOrderedDict()
self.verbose = verbose
self.handle_errors = handle_errors
self._was_error = False
def set_handle_errors(self, handle_errors):
"""Set the value of self.handle_errors."""
self.handle_errors = handle_errors
def set_verbose(self, verbose):
"""Set the value of self.verbose."""
self.verbose = verbose
def get_results(self):
"""Return the results."""
return self.results
def run_all(self):
"""Alias for run_all_fns."""
self.run_all_fns()
def run_all_fns(self, pbar=False):
"""Run all of the established functions."""
self._was_error = False
if pbar:
pbar_ = tqdm(range(len(self.fns_to_run)))
for i in pbar_:
fn = self.fns_to_run[i]
fn_params = self.fn_params_list[i]
fn_kwargs = self.fn_kwargs_list[i]
self._run_fn(fn, *fn_params, **fn_kwargs)
else:
fn_zipped = zip(self.fns_to_run, self.fn_params_list,
self.fn_kwargs_list)
for (fn, fn_params, fn_kwargs) in fn_zipped:
self._run_fn(fn, *fn_params, **fn_kwargs)
if self._was_error:
logging.warning("A handled error occurred while running analysis")
self._was_error = False
def reset(self):
"""Reset this object, clearing results and function list."""
self.reset_func_list()
self.reset_results()
def reset_func_list(self):
"""Reset all functions and parameters."""
self.fns_to_run = []
self.fn_params_list = []
self.fn_kwargs_list = []
def reset_results(self):
"""Reset the results."""
self.results = IndexedOrderedDict()
def add_fn(self, fn, *args, **kwargs):
"""
Add the function fn to the list with the given args and kwargs.
Parameters
----------
fn : function
The function to add.
*args : positional arguments
The positional arguments to run the function with.
**kwargs : keyword arguments
The keyword arguments to run the function with.
Returns
-------
None
"""
self.fns_to_run.append(fn)
self.fn_params_list.append(args)
self.fn_kwargs_list.append(kwargs)
def save_results(self, output_location):
"""
Save the results of analysis to the given output location.
Parameters
----------
output_location : string
Path to a csv to save results to.
Returns
-------
None
"""
with open(output_location, "w") as f:
print("Saving results to {}".format(output_location))
for k, v in self.results.items():
f.write(k.replace(" ", "_").replace(",", "_") + "\n")
o_str = save_mixed_dict_to_csv(v, None, save=False)
f.write(o_str)
def _run_fn(self, fn, *args, **kwargs):
"""
Run the function with *args and **kwargs, not usually publicly called.
Pass simuran_save_result as a keyword argument to control
if the result of the function is saved or not.
Parameters
----------
fn : function
The function to run.
Returns
-------
object
The return value of the function
"""
if self.verbose:
print("Running {} with params {} kwargs {}".format(
fn, *args, **kwargs))
if self.handle_errors:
try:
result = fn(*args, **kwargs)
except BaseException as e:
log_exception(
e,
"Running {} with args {} and kwargs {}".format(
fn.__name__, args, kwargs),
)
self._was_error = True
result = "SIMURAN-ERROR"
else:
result = fn(*args, **kwargs)
ctr = 1
save_result = kwargs.get("simuran_save_result", True)
save_name = str(fn.__name__)
if save_result:
while save_name in self.results.keys():
save_name = str(fn.__name__) + "_{}".format(ctr)
ctr = ctr + 1
self.results[save_name] = result
return result
def __str__(self):
"""String representation of this class."""
return "{} with functions:\n {}, args:\n {}, kwargs:\n {}".format(
self.__class__.__name__,
self.fns_to_run,
self.fn_params_list,
self.fn_kwargs_list,
)
