class Block(object): def __init__(self, size): self.size = size self.path = set() self.zones = set() def build(self): self.root = Region((0,0), self.size) self.regions = self.root.split_to_size(1000) self.graph = RegionGraph(self.regions) self.zones = self.graph.assign_zones(3) self.build_structures() self.starter_zone = random.choice(list(self.zones)) def build_structures(self): for zone in self.zones.copy(): self.zones.remove(zone) self.zones.add(zone.define()) for zone in self.zones: zone.construct() structure_graph = RegionGraph(self.root.search_down(), self.root) for zone in self.zones: zone.determine_interior_edges(self.graph) zone.update_structures(structure_graph) for zone in self.zones: for edge in zone.connections: edge.owner.edges.add(edge) for zone in self.zones: zone.draw_path() for zone in self.zones: for structure in zone.structures: structure.draw()
def instances_fee():
try:
from gcp import fee
auth = Auth()
auth.get_service(request)
data = request.args.to_dict()
ebs = list(eval(data['ebs']))
instance_type = data['instance_type']
os = data['os']
quantity = int(data['quantity'])
total_compute = round(
fee.instance_price[instance_type]['price'][
Region().get_region_name(auth.region)] * quantity, 2)
total_ebs = 0
for each_ebs in ebs:
total_ebs += round(
fee.disk_price[each_ebs['type']][Region().get_region_name(
auth.region)] * int(each_ebs['size']), 2)
total = total_compute + total_ebs
res = {'compute': total_compute, 'ebs': total_ebs, 'total': total}
return jsonify(res)
except errors.HttpError as e:
msg = json.loads(e.content)
return jsonify(msg=msg['error']['message']), msg['error']['code']
def build(self): self.root = Region((0,0), self.size) self.regions = self.root.split_to_size(1000) self.graph = RegionGraph(self.regions) self.zones = self.graph.assign_zones(3) self.build_structures() self.starter_zone = random.choice(list(self.zones))
def plot_graphs_for_year(year_str):
'''
This function will create 7 plots for the input year which includes 1 box plot for that year and 6 hostograms for each region
'''
#try:
countries = pd.read_csv('../countries.csv', sep=',')
income = pd.read_excel('../indicator gapminder gdp_per_capita_ppp.xlsx', index_col=0)
income = income.transpose()
list_region_objects = []
list_of_region_income_data = []
year = int(year_str)
directory_name = create_new_directory(year_str)
print
print "------------------------------------------------------------------------------------------------------"
print
print "Analysis for the year ", year_str, " started ..."
print
regions_data = merge_by_year(year, income, countries)
grouped_region_data = regions_data.groupby('Region')
region_names = regions_data['Region'].unique()
#below for loop will create Region type objects for each individual region
for region_name in region_names:
region_data = grouped_region_data.get_group(region_name)
region_object = Region(region_name, region_data) # Instance creation of Region class
list_region_objects.append(region_object)
#creating list of lists having data of each region income for the Box Plot
for i in range(len(list_region_objects)):
list_of_region_income_data.append(list_region_objects[i].region_income)
print "Plotting and saving histograms for each region ...In Progress..."
for i in range(len(list_region_objects)):
Region.plot_Hist_Graphs(list_region_objects[i], year_str, directory_name)
print "Histograms for each region are plotted and saved successfully ...Completed !!!"
print
print "Plotting and saving Box Plot ...In Progress..."
Region.plot_BoxPlots(region_names, list_of_region_income_data, year_str, directory_name)
print "Box Plt is plotted and saved successfully ...Completed !!!"
print
def create_regions(s, rids, rcolors, refpts, slevels, pids, task):
if task:
task.updateStatus('Making ID table')
id_to_index = dict([(id, i) for i, id in enumerate(rids)])
if task:
task.updateStatus('Collecting child region IDs')
id_to_child_ids = {}
n = len(rids)
for i in range(n):
pid = pids[i]
if pid > 0:
if pid in id_to_child_ids:
id_to_child_ids[pid].append(rids[i])
else:
id_to_child_ids[pid] = [rids[i]]
if task:
task.updateStatus('Ordering IDs')
from regions import Region
ids = depth_order(rids, id_to_child_ids, set())
rlist = []
for c, rid in enumerate(ids):
if rid in id_to_child_ids:
children = [s.id_to_region[cid] for cid in id_to_child_ids[rid]]
else:
children = []
i = id_to_index[rid]
r = Region(s, rid, refpts[i], children)
# TODO: Get wrappy error setting surface piece color to numpy array.
r.color = tuple(rcolors[i])
if not slevels is None:
r.smoothing_level = slevels[i]
rlist.append(r)
if task and c % 1000 == 0:
task.updateStatus('Created %d of %d regions' % (c, n))
if not slevels is None:
s.smoothing_level = max(slevels)
return rlist
def init_sections_state(self):
net_manager.init_devices()
for section in self.vbox.get_children():
if section.show_or_hide():
section.section_show()
section.init_state()
else:
section.section_hide()
slider._append_page(Region(), "region")
from setting_page_ui import SettingUI
self.setting_page_ui = SettingUI(None, None)
slider._append_page(self.setting_page_ui, "setting")
def copy_regions(regions, bin_size, seg):
from regions import Region
rlist = []
for r in regions:
if r.rid in seg.id_to_region:
rc = seg.id_to_region[r.rid]
else:
cc = copy_regions(r.children(), bin_size, seg)
max_point = tuple([b * i for b, i in zip(bin_size, r.max_point)])
rc = Region(seg, r.rid, max_point, cc)
rlist.append(rc)
return rlist
def make_some_data(self):
img_path="data_sim/boulder.png"
region_coordinates={'latmin':0,'latmax':0,'lonmin':0,'lonmax':0}
Boulder=Region('Boulder',img_path,region_coordinates)
Boulder.initPointTargets()
Boulder.generateLayers()
total_targets=np.zeros((100,100,100))
for i, (gt_layer,sb_layer,pb_layer) in enumerate(zip(Boulder.ground_truth_layers,Boulder.shake_base_layers,Boulder.pixel_bleed_layers)):
total_targets=total_targets+gt_layer+sb_layer+pb_layer
total=total_targets+Boulder.noise_layer+Boulder.structured_noise_layer+Boulder.shotgun_noise_layer
return total
def initialise_regions(self) -> None:
"""Create all the region data classes"""
f = open("data/country_names.csv")
data = f.readlines()
for line in data[1:]:
name, continent = DataSet.parse_csv_line(line)
region = Region(
name=name,
continent=continent
)
self.regions[name] = region
f.close()
# To ensure consistency between different data sets,
# some names will be changed
uk = self.regions["United Kingdom of Great Britain & Northern Ireland"]
del self.regions["United Kingdom of Great Britain & Northern Ireland"]
self.regions["United Kingdom"] = uk
us = self.regions["United States of America"]
del self.regions["United States of America"]
self.regions["United States"] = us