|
App Engine Python SDK
v1.6.9 rev.445
The Python runtime is available as an experimental Preview feature.
|
Classes | |
| class | _State |
Public Member Functions | |
| def | __init__ |
| def | validate |
| def | init_job |
| def | finalize_job |
| def | from_json |
| def | to_json |
| def | create |
| def | finalize |
| def | get_filenames |
| Public Member Functions inherited from google.appengine.ext.mapreduce.output_writers.OutputWriter | |
| def | validate |
| def | init_job |
| def | finalize_job |
| def | from_json |
| def | to_json |
| def | create |
| def | write |
| def | finalize |
| def | get_filenames |
| Public Member Functions inherited from google.appengine.ext.mapreduce.json_util.JsonMixin | |
| def | to_json_str |
| def | from_json_str |
Base class for all file output writers.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.__init__ | ( | self, | |
| filename, | |||
| request_filename | |||
| ) |
Init. Args: filename: writable filename from Files API. request_filename: in the case of GCS files, we need this to compute finalized filename. In the case of blobstore, this is useless as finalized filename can be retrieved from a Files API internal name mapping.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.create | ( | cls, | |
| mr_spec, | |||
| shard_number, | |||
| shard_attempt, | |||
_writer_state = None |
|||
| ) |
Inherit docs.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.finalize | ( | self, | |
| ctx, | |||
| shard_state | |||
| ) |
Finalize writer shard-level state. Args: ctx: an instance of context.Context. shard_state: shard state.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.finalize_job | ( | cls, | |
| mapreduce_state | |||
| ) |
See parent class.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.from_json | ( | cls, | |
| state | |||
| ) |
Creates an instance of the OutputWriter for the given json state. Args: state: The OutputWriter state as a json object (dict like). Returns: An instance of the OutputWriter configured using the values of json.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.get_filenames | ( | cls, | |
| mapreduce_state | |||
| ) |
See parent class.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.init_job | ( | cls, | |
| mapreduce_state | |||
| ) |
Initialize job-level writer state. Args: mapreduce_state: an instance of model.MapreduceState describing current job.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.to_json | ( | self | ) |
Returns writer state to serialize in json. Returns: A json-izable version of the OutputWriter state.
| def google.appengine.ext.mapreduce.output_writers.FileOutputWriterBase.validate | ( | cls, | |
| mapper_spec | |||
| ) |
Validates mapper specification. Args: mapper_spec: an instance of model.MapperSpec to validate. Raises: BadWriterParamsError: if the specification is invalid for any reason.


{% extends "mex/base.html" %} {% load render_table from django_tables2 %} {% block content %}
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@* * Copyright 2021 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.helplinefrontend.config.AppConfig @import uk.gov.hmrc.helplinefrontend.views.html.Layout @this(layout: Layout) @(back: Option[String])(implicit request: Request[_], messages: Messages, appConfig: AppConfig) @layout(pageTitle = Some(s"${messages("child-benefit.title")} ${messages("title.suffix")}")) { @if(back.nonEmpty) { @Messages("back") }
@messages("label.monday-friday"): @messages("child-benefit.hours.monday-friday")
@messages("child-benefit.closed")
@Html(messages("get-help", "https://www.gov.uk/get-help-hmrc-extra-support"))
@Html(messages("call-charges", "https://www.gov.uk/call-charges"))
}


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WITNESS LIST Finance Committee (Subcommittee on Trauma Care) August 30, 2002 - 9:30A Trauma Care ON: Adams, Bill Hospital Administration (Valley Baptist Medical Center), Harlingen, TX Alanis, Heriberto Physician-Emergency Medicine (Emergency Physicians), McAllen, TX Ashton, Bill Director of EMS (EMS), Harlingen, TX Atkins, Francina RN CCRN-Trauma (Edinberg Regional Medical Center), Edinberg, TX Camacho, Jose Executive Director (Texas Association of Community Health Centers), Austin, TX Cardenas, Carlos Physician (TMA/Border Health Caucas), McAllen, TX Clark, Bliss Orthopedic Surgeon (Doctors), Harlingen, TX Dominguez, Dominic CEO, Brownsville Medical Center (Brownsville Medical Center), Brownsville, TX Garcia, Louis Hospital Administrator (McAllen Medical Center), McAllen, TX Garza, Ruben Director of Insurance/Accreditation (Knapp Medical Center), Weslaco, TX Montelongo, Olga Trauma Registar (Mission Hospital), Mission, TX Montemayor, Jose Commissioner of Insurance (Texas Department of Insurance), Austin, TX Pelly, Lorenzo Internal Medicine/Critical Care Special (Valley Doctors Clinic), Brownsville, TX Pisharodi, Madhavan Neurosurgeon (Physicians), Brownsville, TX Quiroga, Javier Training Officer-EMS (Brownsville Fire Department), Harlingen, TX Robles, Robert Cardiologist (Physicians), Brownsville, TX Sexton, Charles Hospital Executive (Valley Regional Medical Center), Brownsville, TX Tello, Carlos (Texas Department of Health Public Health Regional II), Harlingen, TX Registering, but not testifying: On: Cooper, Viraf Pysician/Neurosurgeon (Self), Brownsville, TX Gaitan, Luis Neurologist (BCHC), Brownsville, TX Garza, Mario Hospital Administration (Mission Hospital), McAllen, TX Garza, Rudy Firefighter/EMT (Weslaco Fire/EMS), Weslaco, TX Glenn, Eric Regional Legislative Manager (Humana, Inc.), Austin, TX Gomez, Paula Health Care Administrator (Brownsville Community Health Center), Brownsville, TX Hebner, Dennis President (Texas Association of Air Medical Services), Harlingen, TX Kuri, Jose Neurosurgeon (Self), Brownsville, TX Lakshmikanth, B.N. Surgeon (Self), Brownsville, TX Martinez, Dagoberto M.D. (Doctor's), Brownsville, TX Montano, Pedro Physician (Self), McAllen, TX Perez-Trevino, Emma Senior Reporter ("The Brownsville Herald"), Brownsville, TX Pope, Bill Attorney/Judge (Public), Harlingen, TX Ramos, Medelene Trauma Coordinator (Mission Hospital), McAllen, TX Rodriguez, Amanda Executive Secretary (Hidalgo-Starr Counties Medical Society), McAllen, TX Rodriguez, Juan M.D. (Self), Brownsville, TX Sala, Anthony Chief Operating Officer (Rio Grande Regional Hospital), McAllen, TX Sanchez, Gerardo (Self), Brownsville, TX Silva, Armando Paramedic (Vital Line Inc./Vital Air), Edinburg, TX Soleja, Kitalid Plastic Surgeon (Self), Brownsville, TX Sweitzer, Paul Paramedic/EMS Instructor (Texas State Technical College Harlingen), Harlingen, TX


Please refer document to understand how to raise an issue:
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--- layout: page title: Screeps Alliance Index sitemap: priority: 1.0 changefreq: weekly ---
This data can also be downloaded in json format in alliances.js for use in game or in your own scripts.
Want your alliance listed? Make a pull request!
{% for alliance in site.data.alliances %}
{% if alliance[1].charter %}
Charter
{% endif %}
{% if alliance[1].slack %}
Slack:
#{{ alliance[1].slack }}
{% endif %}
{{ alliance[1].members | size }} members


8 Does isotopic niche of sea snakes change with local fishing intensity?
It is infeasible to to find sites with little to no fishing pressure on mainland India. Hence, it is nigh impossible to conduct a study with controls and test sites with varying levels of fishing pressure.
How do you test the niche shift hypotheses with out spatial replicates?
While the control - test study design failed, fishing effort data was collected from multiple vessels (Gillnet and Trawlers) landing at the Malvan harbour over the period of 1.5 years along side diet, abundance (snakes and prey), and isotopic data. So we ask the following questions:
- Is there a corellation between fishing intensity and isotopic ratios?
- Do niche metrics (width, overlap) vary with fishing pressure (high, medium and low preiods during the year)?
What temporal resolution should be used for the analysis?
- Day, week, month or season.
Which is appropriate and why?
Depending on the tissue being analysed. Scales - month, Plasma - week
8.1 Determining cluster of fishing intensity off the coast of sindhudurg
We used hierarchical clustering based on fishing intensity of both gears, and the position of the cell in the grid to divided the grid into high and low fishing intensity zones.
# loading required libraries
require(tidyverse)
library(sp)
library(raster)
# importing data
<- read.csv(file = "Data/Sea-snakes_fish-dep_2018-19_250720.csv") # snake data
snakes
<- read.csv("./Data/Fishing intensity_dep.csv") # geocoded fishing effort
dep_int
<- read.csv("./Data/snakes-density.csv") # sea snake occurence in bycatch
snakes_den
<- raster::raster("./Data/sampling_extent.tif") # sampling grid
ext
# importing required scripts
source("./Functions/intensity extract.R")
source("./Functions/raster to df.R")
# Calculating fishing intensity
<- dep_int %>%
fi group_by(Gear.Type) %>%
nest() %>%
mutate(m = map(data, ~map.extract(df = ., var = "effort", func = "sum")), mdf = map(m, map.df)) %>%
::select(mdf) %>%
dplyrunnest() %>%
spread(Gear.Type, layer)
## creating distance matrix
<- dist(fi)
dist_fi
## Hierarchical clustering
<- hclust(dist_fi)
clust_fi
plot(clust_fi, hang = -1, labels = F)
## Assigning fishing intensity classes
<- cutree(clust_fi, k = 6) ## cutting the tree 4 times
fi_class
## Naming clasess
<- fi %>%
fi # extracting classes from clustering
mutate(class = as.factor(ifelse(fi_class == 1, "Low", "High")), fic = fi_class) %>%
# reordering classes
mutate(class = fct_relevel(class, c("High", "Medium", "Low")))
## Plotting grid
ggplot(fi, aes(x, y, fill = class)) + geom_tile(col = "black") + scale_fill_brewer(palette = "Set1", name = "Fishing intensity") + labs(x = "Longitude", y = "Latitude") +
theme(text = element_text(size = 10))
8.2 Determining capture grid cell for individual snakes
Using data gathered from fisher surveys, we mapped the location of each fishing trip.
The protocol for geocoding fishing trips is as follows:
- Nearest landmarks are geocoded from google maps API
- Latitude is extracted from landmark geocode
- Match landmark latitude and depth from survey to GEBCO data
- Extract final longitude from GEBCO data
The protocol is encoded in Function/geocode.R
# importing stable isotope data
= read.csv("./Data/Stable Isotope Data_CEAS_final_191020.csv")
sia
# joining sia data to snake data
= sia %>%
sia_snakes filter(Tissue.type == "Plasma" | Tissue.type == "Scales") %>%
left_join(snakes, "Field.Code") %>%
mutate(Lab = "CEAS") %>%
rename(Delta.Carbon = d13C..vpdb., Delta.Nitrogen = d15N..N2.air.) %>%
::select(Field.Code, Species, Snout.to.Vent..cm., Sex, Class, Gear.Type, Fishing.Location, Location.encountered, Depth.Caught..m., Plasma.Color, Delta.Carbon,
dplyr%>%
Delta.Nitrogen, Lab, Tissue.type, Month, Year) # using location encountered where fishing location is unavailable
mutate(Fishing.Location = ifelse(Fishing.Location == "", Location.encountered, Fishing.Location)) %>%
mutate(Fishing.Location = ifelse(Fishing.Location == "Dandi" | Fishing.Location == "Dandi Beach", "Wayari", Fishing.Location))
# selecting relavant variables
= sia_snakes %>%
sia_li ::select(Field.Code, Species, Fishing.Location, Depth.Caught..m., Tissue.type, Delta.Carbon, Delta.Nitrogen) %>%
dplyrfilter(Fishing.Location != "") %>%
drop_na() %>%
droplevels()
## Geocoding si data
source("./Functions/geocode.R")
<- geocode.trips(sia_li, fl = "Fishing.Location", dep = "Depth.Caught..m.")
sia_li
## removing duplicates introduced by fuzzy joining
<- distinct(sia_li, Field.Code, Tissue.type, .keep_all = T)
sia_li
## Assigning grid cells to snakes
source("./Functions/find cell.R") # importing cell.ext function
<- raster::raster("./Data/sampling_extent.tif") # sampling grid
ext
<- sia_li %>%
sia_fi group_by(Field.Code, Species, Tissue.type, Delta.Carbon, Delta.Nitrogen) %>%
nest() %>%
mutate(cell = map(data, cell.ext), celldf = map(cell, as.data.frame)) %>%
::select(celldf) %>%
dplyrunnest() %>%
ungroup()
## Saving data to save time
write.csv(sia_li, "./Data/SIA_fishing intensity.csv")
Note: fuzzyjoin::fuzzy_inner_join()
introduces many duplicates, I have not as yet been able to fix the issue dirrectly. Currently, removing duplicates from output using dplyr::distinct()
.
8.3 Sample size
# adding fishing intensity class
<- sia_fi %>%
sia_li left_join(fi, c("x", "y")) %>%
mutate(intensity = GillNet + Trawler)
# summarising number of samples
table(sia_li$Species, sia_li$Tissue.type, sia_li$class) %>%
as.data.frame() %>%
spread(Var3, Freq) %>%
rename(Species = Var1, Tissue = Var2) %>%
arrange(Species, Tissue)
| Species | Tissue | High | Low |
|---|---|---|---|
| Hydrophis curtus | Plasma | 9 | 7 |
| Hydrophis curtus | Scales | 13 | 10 |
| Hydrophis schistosus | Plasma | 26 | 14 |
| Hydrophis schistosus | Scales | 19 | 18 |
8.4 Variation isotope ratio with fishing intensity
# plotting
%>%
sia_li gather(key = Isotope, c(Delta.Carbon, Delta.Nitrogen), value = ratio) %>%
ggplot(aes(intensity, ratio, col = Species)) + geom_point(size = 3) + geom_smooth(method = lm) + scale_color_brewer(palette = "Set1") + labs(x = "Fishing intensity",
y = "Isotope ratio") + theme(legend.text = element_text(face = "italic")) + facet_grid(Isotope ~ Tissue.type, scale = "free_y")
Both \(\delta^{15}N\) and \(\delta^{13}C\) show strong negatice relationship with increasing fishing intensity.
8.5 Modeling isotope ratios with fishing intensity
<- sia_li %>%
sia_fi_lm gather(key = Isotope, c(Delta.Carbon, Delta.Nitrogen), value = ratio) %>%
group_by(Species, Isotope, Tissue.type) %>%
nest() %>%
mutate(mod1 = map(data, ~lm(ratio ~ intensity, data = .)), summ1 = map(mod1, broom::tidy), r2 = map(mod1, broom::glance)) %>%
::select(summ1, r2) %>%
dplyrunnest() %>%
::select(Species:p.value, adj.r.squared) %>%
dplyrarrange(Species, Tissue.type, adj.r.squared)
library(knitr)
library(kableExtra)
<- sia_fi_lm %>%
sia_fi_lm rename(`Tissue type` = Tissue.type, Parameter = term, Coefficient = estimate, `Standard Error` = std.error, T = statistic, p = p.value, `r_adj^2` = adj.r.squared) %>%
mutate(Parameter = ifelse(Parameter == "(Intercept)", "Intercept", "Fishing intensity"), T = ifelse(Parameter == "Intercept", NA, T), p = ifelse(Parameter == "Intercept",
NA, p))
kbl(sia_fi_lm, booktabs = T, digits = 3) %>%
column_spec(1, italic = T) %>%
collapse_rows(columns = 1:3, row_group_label_position = "stack")
| Species | Tissue type | Isotope | Parameter | Coefficient | Standard Error | T | p | r_adj^2 |
|---|---|---|---|---|---|---|---|---|
| Hydrophis curtus | Plasma | Delta.Nitrogen | Intercept | 13.862 | 0.234 | -0.023 | ||
| Hydrophis curtus | Plasma | Delta.Nitrogen | Fishing intensity | -0.003 | 0.003 | -0.818 | 0.427 | -0.023 |
| Hydrophis curtus | Plasma | Delta.Carbon | Intercept | -15.670 | 0.404 | 0.370 | ||
| Hydrophis curtus | Plasma | Delta.Carbon | Fishing intensity | -0.017 | 0.006 | -3.129 | 0.007 | 0.370 |
| Hydrophis curtus | Scales | Delta.Nitrogen | Intercept | 14.330 | 0.295 | -0.048 | ||
| Hydrophis curtus | Scales | Delta.Nitrogen | Fishing intensity | 0.000 | 0.003 | -0.014 | 0.989 | -0.048 |
| Hydrophis curtus | Scales | Delta.Carbon | Intercept | -15.011 | 0.325 | -0.004 | ||
| Hydrophis curtus | Scales | Delta.Carbon | Fishing intensity | 0.003 | 0.004 | 0.957 | 0.349 | -0.004 |
| Hydrophis schistosus | Plasma | Delta.Nitrogen | Intercept | 14.687 | 0.258 | -0.025 | ||
| Hydrophis schistosus | Plasma | Delta.Nitrogen | Fishing intensity | 0.001 | 0.004 | 0.183 | 0.856 | -0.025 |
| Hydrophis schistosus | Plasma | Delta.Carbon | Intercept | -16.572 | 0.254 | -0.024 | ||
| Hydrophis schistosus | Plasma | Delta.Carbon | Fishing intensity | -0.001 | 0.004 | -0.320 | 0.751 | -0.024 |
| Hydrophis schistosus | Scales | Delta.Nitrogen | Intercept | 14.861 | 0.342 | -0.028 | ||
| Hydrophis schistosus | Scales | Delta.Nitrogen | Fishing intensity | 0.000 | 0.006 | -0.076 | 0.940 | -0.028 |
| Hydrophis schistosus | Scales | Delta.Carbon | Intercept | -14.084 | 0.357 | 0.024 | ||
| Hydrophis schistosus | Scales | Delta.Carbon | Fishing intensity | -0.009 | 0.006 | -1.376 | 0.178 | 0.024 |
Samples sizes for H. curtus are low, however, fishing intensity seems to have a significant depletion effect on plasma isotope ratios in H. schistosus.
8.6 Difference in niche width between sea snakes
See section 4 for more details on analysis with SIBER.
# Loading required libraries
library(SIBER)
#Creating siber data
## Plasma samples
= sia_li%>%
siber_pl_fi filter(Tissue.type == "Plasma")%>% # using plasma values for comparison
::select(Delta.Carbon, Delta.Nitrogen, Species, class)%>%
dplyr# renaming baed on SIBER conventions
rename(iso1 = Delta.Carbon,
iso2 = Delta.Nitrogen,
group = class, # setting fishing intesnity as group
community = Species)%>%
# removing missing data
filter(!is.na(group),
!is.na(iso1),
!is.na(iso2),
== "Hydrophis schistosus" | community == "Hydrophis curtus")%>%
community ungroup()%>%
::select(iso1, iso2, group, community)%>%
dplyrdroplevels()
# Creating SIBER object fo MVN fitting
= createSiberObject(as.data.frame(siber_pl_fi))
siber.plasma.fi
## Scale samples
= sia_li%>%
siber_sc_fi filter(Tissue.type == "Scales")%>% # using plasma values for comparison
::select(Delta.Carbon, Delta.Nitrogen, Species, class)%>%
dplyr# renaming baed on SIBER conventions
rename(iso1 = Delta.Carbon,
iso2 = Delta.Nitrogen,
group = class, # setting fishing intesnity as group
community = Species)%>%
# removing missing data
filter(!is.na(group),
!is.na(iso1),
!is.na(iso2),
== "Hydrophis schistosus" | community == "Hydrophis curtus")%>%
community ungroup()%>%
::select(iso1, iso2, group, community)%>%
dplyrdroplevels()
# Creating SIBER object fo MVN fitting
= createSiberObject(as.data.frame(siber_sc_fi)) siber.scales.fi
8.6.1 Maximum likelihood estimate of SEA
<- groupMetricsML(siber.plasma.fi) # for plamsa samples
SEA.ML_plasma.fi
<- groupMetricsML(siber.scales.fi) # for scale samples
SEA.ML_scales.fi
data.frame(t(SEA.ML_plasma.fi)) %>%
rownames_to_column("Species.FI") %>%
mutate(Tissue = "Plasma") %>%
full_join((data.frame(t(SEA.ML_scales.fi)) %>%
rownames_to_column("Species.FI") %>%
mutate(Tissue = "Scales"))) %>%
group_by(Tissue) %>%
arrange(Species.FI)
| Species.FI | TA | SEA | SEAc | Tissue |
|---|---|---|---|---|
| Hydrophis curtus.High | 2.75500 | 1.589387 | 1.816443 | Plasma |
| Hydrophis curtus.High | 6.65860 | 2.920519 | 3.186021 | Scales |
| Hydrophis curtus.Low | 2.11300 | 1.391784 | 1.670141 | Plasma |
| Hydrophis curtus.Low | 2.27960 | 1.026595 | 1.154919 | Scales |
| Hydrophis schistosus.High | 9.22790 | 2.594212 | 2.702304 | Plasma |
| Hydrophis schistosus.High | 22.84530 | 6.363402 | 6.737720 | Scales |
| Hydrophis schistosus.Low | 5.47320 | 2.130937 | 2.308515 | Plasma |
| Hydrophis schistosus.Low | 9.65475 | 3.288029 | 3.493531 | Scales |
As maximum likelihood can only porivde point estimates of SEA, a bayesian model was used to provide more robust comparison of niche width.
8.6.2 Bayesian estimate of SEA
# options for running jags
<- list()
parms $n.iter <- 2 * 10^4 # number of iterations to run the model for
parms$n.burnin <- 1 * 10^3 # discard the first set of values
parms$n.thin <- 10 # thin the posterior by this many
parms$n.chains <- 2 # run this many chains
parms
# define the priors
<- list()
priors $R <- 1 * diag(2)
priors$k <- 2
priors$tau.mu <- 0.001
priors
# scale samples
<- siberMVN(siber.scales.fi, parms, priors) #fitting multivariate normal model and getting posteriors
scales.fi.post
<- siberEllipses(scales.fi.post) #estimating standard ellipse area from posteriors
SEA.B_scales.fi
<- extractPosteriorMeans(siber.scales.fi, scales.fi.post) #mean isotope values
means.B_scales.fi
<- names(scales.fi.post)
ccc
colnames(SEA.B_scales.fi) <- ccc
# plasma samples
<- siberMVN(siber.plasma.fi, parms, priors) #fitting multivariate normal model and getting posteriors
plasma.fi.post
<- siberEllipses(plasma.fi.post) #estimating standard ellipse area from posteriors
SEA.B_plasma.fi
<- extractPosteriorMeans(siber.plasma.fi, plasma.fi.post) #mean isotope values
means.B_plasma.fi
<- names(plasma.fi.post)
ccc
colnames(SEA.B_plasma.fi) <- ccc
# creating data frame
= data.frame(SEA.B_plasma.fi, check.names = F) %>%
SEA.B_snakes.fi.df rowid_to_column(var = "run") %>%
gather(Species.class, SEA.B, -run) %>%
separate(Species.class, c("Species", "FI.Class"), sep = "([\\.\\?\\:])") %>%
mutate(Tissue = "Plasma") %>%
# appending scale runs
full_join(data.frame(SEA.B_scales.fi, check.names = F) %>%
rowid_to_column(var = "run") %>%
gather(Species.class, SEA.B, -run) %>%
separate(Species.class, c("Species", "FI.Class"), sep = "([\\.\\?\\:])") %>%
mutate(Tissue = "Scale"))
# Summarising SEA estimates
%>%
SEA.B_snakes.fi.df group_by(Species, Tissue, FI.Class) %>%
summarise(SEA.mean = mean(SEA.B), SEA.sd = sd(SEA.B), SEA.se = sd(SEA.B)/sqrt(n()))
| Species | Tissue | FI.Class | SEA.mean | SEA.sd | SEA.se |
|---|---|---|---|---|---|
| Hydrophis curtus | Plasma | High | 1.791498 | 0.6713751 | 0.0106154 |
| Hydrophis curtus | Plasma | Low | 1.614469 | 0.6800886 | 0.0107531 |
| Hydrophis curtus | Scale | High | 3.205167 | 0.9449341 | 0.0149407 |
| Hydrophis curtus | Scale | Low | 1.170616 | 0.4103433 | 0.0064881 |
| Hydrophis schistosus | Plasma | High | 2.707260 | 0.5618308 | 0.0088833 |
| Hydrophis schistosus | Plasma | Low | 2.331352 | 0.6639599 | 0.0104981 |
| Hydrophis schistosus | Scale | High | 6.728280 | 1.6373112 | 0.0258882 |
| Hydrophis schistosus | Scale | Low | 3.500772 | 0.8649369 | 0.0136759 |
8.6.3 Testing difference in species niche area by fishing intensity
%>%
SEA.B_snakes.fi.df spread(key = FI.Class, value = SEA.B) %>%
group_by(Species, Tissue) %>%
summarise(`P(High > Low)` = sum(High > Low)/n())
| Species | Tissue | P(High > Low) |
|---|---|---|
| Hydrophis curtus | Plasma | 0.58950 |
| Hydrophis curtus | Scale | 0.99025 |
| Hydrophis schistosus | Plasma | 0.69125 |
| Hydrophis schistosus | Scale | 0.97400 |
# Currently no medium cells `P(Medium > Low)` = sum(`Medium` > `Low`)/n(), `P(High > Medium)` = sum(`High` > `Medium`)/n())
8.6.4 Visualising difference in niche width across gradiet of fishing intensity
library(gridExtra)
%>%
SEA.B_snakes.fi.df # reordering classes
mutate(FI.Class = fct_relevel(FI.Class, c("High", "Medium", "Low"))) %>%
ggplot(aes(Species, SEA.B, fill = FI.Class)) + geom_violin(alpha = 0.3, position = position_dodge(0.4), width = 0.5) + geom_boxplot(alpha = 0.3, width = 0.05, outlier.alpha = 0,
position = position_dodge(0.4)) + scale_y_continuous(name = "Standard Ellispes Area", guide = guide_axis(n.dodge = 1)) + scale_fill_discrete(name = "Fishing Intensity") +
facet_wrap(~Tissue) + theme(axis.text.x = element_text(face = "italic"))
ggsave(last_plot(), filename = "./Figures and Tables/figure6.png", height = 6, width = 10, device = "png")
Currently many outliers from 5 - 15 on y - axis


Our Hospitality (1923)
Grade: 47
"Our Hospitality" is a silent comedy starring Buster Keaton, one of his first features. Grading this film provides one of the occasions where my grade is much lower than that of the consensus, and it may well be that I have severely undergraded it.
"Our Hospitality" has Keaton returning via a rickety train to the land he left as an infant to claim an inheritance. Keaton's family (the McKays) and a rival family (the Canfields, similarity to Hatfield and McCoys intended) have had a feud spanning several generations. This feud is typically resolved with a shotgun. Upon arrival, the Canfield men make numerous attempts on his life. Keaton is also courting a Canfield daughter. This leads to much slapstick and several stunts, which are hallmarks of Keaton silents.
The plot has some elements later put to use in better Keaton films. A train is central to the story, as in "The General" (1927). Keaton is a stranger entering a family feud (and courting the rival family's daughter), as in "Steamboat Bill, Jr." (1928).
Perhaps the best part of "Our Hospitality" are the scenes with a mock circa-1830s steam train. The sluggish train and its bumpy ride are the butt of many gags. My favorite is when a mule refuses to budge from the train tracks. The train conductor stops the train, and unable to move the mule, he picks up the train track and moves it!
The film has a slow start, and the characters are one-dimensional. The plot also has several repetitive elements, such as the point made about how slow the train is, and especially the Canfields shooting at Keaton in one scene after another. An occasional gag that works, and a spectacular stunt or two, do not have a significant effect on a film's grade.
Some trivia: Keaton's father Joseph and his son Buster Jr. have bit parts. Keaton's wife Natalie Talmadge plays his love interest (this was their only film together). The film's most famous stunt (Keaton swings from a rope to rescue Talmadge from falling off the edge of a waterfall) was executed by Keaton, but a dummy stood in for Talmadge. Keaton was injured performing the stunt.
<EMAIL_ADDRESS>http://members.tripod.com/~Brian_Koller/movies.html
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
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Related links: index of all rec.arts.movies.reviews reviews


---
layout: post
title: Yeats on the Greeks
date: '2010-05-05T11:11:00.000-04:00'
author: RyGuy
tags:
modified_time: '2010-05-05T11:16:10.690-04:00'
blogger_id: tag:blogger.com,1999:blog-2767138550438691941.post-2720562408139219741
blogger_orig_url: https://muchtoilingant.blogspot.com/2010/05/yeats-on-greeks.html
---
Plato thought nature but a spume that plays
Upon a ghostly paradigm of things;
Solider Aristotle played the taws
Upon the bottom of a king of kings;
World-famous golden-thighed Pythagoras
Fingered upon a fiddle-stick or strings
What a star sang and careless Muses heard:
Old clothes upon old sticks to scare a bird.
- From Among School Children, verse 6


new Map(structure, defaultSubKeyValue)
Parameters:
| Name | Type | Argument | Description |
|---|---|---|---|
structure |
object | The key structure of the map. This can be supplied either as an object, with each non-function property in enumeration order becoming a sub-key of the constructed map(e.g. {a: "a", b: "b"}), or an array of key-names (e.g. ["a", "b"]). |
|
defaultSubKeyValue |
* |
<optional> |
An optional default value to use for missing sub-keys in keys supplied to the get and put method. If not supplied, this defaults to "_". |
- Source:
Members
-
clear
-
Clears the map of all key-value associations. Clearing a sub-map obtained from a parent map (through the module:Map.Map#of method) will also clear all corresponding key-value pairs from the parent map.
Alias: removeAll
- Source:
Methods
-
<static> create(structure, defaultSubKeyValue) → {Map}
-
Factory method which creates a map by invoking the constructor with the specified structure and optional default sub-key value.
Parameters:
Name Type Argument Description structure
object The key structure of the map. This can be supplied either as an object, with each non-function property in enumeration order becoming a sub-key of the constructed map(e.g. {a: "a", b: "b"}), or an array of key-names (e.g. ["a", "b"]).
defaultSubKeyValue
* <optional>
An optional default value to use for missing sub-keys in keys supplied to the get and put method. If not supplied, this defaults to "_".
- Source:
Returns:
The constructed map.
- Type
- Map
-
contains(key) → {boolean}
-
Check if this map contains the specified key.
Parameters:
Name Type Description key
object | string The key to check.
- Source:
Returns:
True if the map contains the key, false otherwise.
- Type
- boolean
-
each(iterator, context)
-
Iterates over all key-value mappings in the map and invokes the iterator callback with each key, value and the current map. The value of
this
in the iterator function is set to the context, if provided; otherwise it is set to the current map.Parameters:
Name Type Argument Description iterator
Iterator The iterator function to invoke for each mapping.
context
* <optional>
The optional value of
this
in the iterator function; defaults to the current map.- Source:
-
fields() → {string[]}
-
- Source:
Returns:
a copy of the key structure of this map as an array of string where each string is a name of a field in the key structure in proper order.
- Type
- string[]
-
filter(predicate, context)
-
Returns a new map containing only existing entries for which the predicate function returns true.
Parameters:
Name Type Argument Description predicate
Predicate A predicate function taking the current key, value and map as parameters and returning true if the current entry (key-value pair) should be included in the filtered map, false otherwise.
context
* <optional>
The optional value of
this
in the predicate function; defaults to the current map.- Source:
-
get(key, defaultValue) → {*}
-
Returns the value previously associated to the key, if any. Otherwise, if defaultValue is supplied and it is not a function, return it. If defaultValue is a function, execute it with this map as context and return its return value.
Missing sub-keys in the key are assumed to be equal to the defaultSubKeyValue supplied on construction ("_" by default).
Parameters:
Name Type Argument Description key
object | string The key whose associated value is sought.
defaultValue
* <optional>
An optional value to return if no value was previously associated with the key. If this is a function, it is executed and its return value is returned.
- Source:
Returns:
The value associated to the key or, if none, the supplied defaultValue or its return value (if it is a function) or, barring all this, undefined.
- Type
- *
-
getOrElseUpdate(key, value) → {*}
-
Returns the value previously associated to the key, if any, or otherwise, associate the key to the defaultValue, if supplied. If defaultValue is a function, execute it and associate the key to its return value instead. This method is useful when the map is used as a cache, returning the values of previously associated keys if existing or, when not, computing the value and saving it for subsequent access.
Missing sub-keys in the key are assumed to be equal to the defaultSubKeyValue supplied on construction ("_" by default).
Parameters:
Name Type Description key
object | string The key whose associated value is sought.
value
* The value to associate to the key if no value was previously associated to it. If this is a function, it is executed and its return value is associated to the key.
- Source:
Returns:
The value associated to the key or, if none, the supplied value or its return value (if it is a function) or, barring all this, undefined.
- Type
- *
-
keys(stringForm) → {Array.<object>|Array.<string>}
-
Returns an array of all the keys in the map. If the stringForm parameter is provided and is true, the keys are returned in string form; otherwise they are returned in object form.
Parameters:
Name Type Argument Description stringForm
boolean <optional>
Whether to return the keys in string or object form. Defaults to false (object form).
- Source:
Returns:
an array of all the keys in the map.
- Type
- Array.<object> | Array.<string>
-
of(key, createSubMaps) → {Map|*}
-
This method takes a prefix of the key structure and returns the sub-map reachable by following that prefix. E.g., in a map with key structure
{a, b, c}
,map.of("a:A")
finds all mappings with a = A and returns the corresponding sub-map with the structureb -> c -> values
. This sub-map implements all methods of the top-level map and can be further manipulated. Any changes to the sub-map will be reflected in the original map. When supplied with a full key,of
behaves exactly as module:Map.Map#get.If the optional createSubMaps parameter is set to true (or not provided, in which case it defaults to true), this method will automatically create submaps along the path of the supplied key if such did not exist previously. E.g.
map.of("A/B", false)
will returnundefined
on an empty map. However,map.of("A/B").put("C", "D")
is valid on the same empty map as this method would create the necessary submaps along the path"A/B"
.Note that only consecutive sub-keys are followed; e.g., in
map.of("a:A/c:C")
, the sub-key value c = C will not be followed as it does not follow the sub-keya
in the key structure.Parameters:
Name Type Argument Description key
string | object The prefix (or full) key to follow.
createSubMaps
boolean <optional>
Whether to automatically create submaps along the path of a followed key. Defaults to true.
- Source:
Returns:
Either the sub-map reachable by following the prefix key supplied or, if a full key is supplied, the value associated to it (or undefined if no such association exists).
- Type
- Map | *
-
put(key, value) → {*}
-
Associate a value to a key, replacing the existing association, if any. Missing sub-keys are assumed to be equal to the defaultSubKeyValue supplied on construction ("_" by default)".
Parameters:
Name Type Description key
object | string The key to associate the value to.
value
* The value to associate to the key.
- Source:
Returns:
The previous value associated to the key or undefined if none.
- Type
- *
-
remove(key) → {*}
-
Removes the key and its associated value from the map. Removing a key from a sub-map obtained from a parent map (through the module:Map.Map#of method) will also remove the corresponding key-value pair from the parent map.
Parameters:
Name Type Description key
string | object The key to remove from the map.
- Source:
Returns:
The value previously associated to the key or undefined if none.
- Type
- *
-
size() → {number}
-
- Source:
Returns:
The size (number of key-value pairs) in this map.
- Type
- number
-
toObjectKey(key) → {object}
-
Given a key in string form, this method returns an equivalent key in object form.
A key is normally an object with each property being a sub-key. E.g.
{a: "A", b: "B", c: "C"}
. The same key can be provided as a string as either "A/B/C" where the order of each sub-key value is important or "a:A/b:B/c:C" where any sub-key order may be used. Given a string key this method converts it to an object key. When the string key does not contain the property names, the latter are derived from the position of the sub-key in the key structure of the map.Both type of keys can be mixed with field names provided for only certain sub-keys, e.g., A/b:B/C; the sub-keys without names will be matched to field by position.
In string form, a forward-slash and a colon appearing in a sub-key can be escaped by preceding each with a back-slash ('\/' & '\:', respectively).
If the key is not a string, it is returned unchanged.
Parameters:
Name Type Description key
string | object The key to convert to object form.
- Source:
Returns:
The key converted to object form if it was in string form.
- Type
- object
-
toStringKey(key, includePropertyNames) → {string}
-
This is the inverse of module:Map.Map#toObjectKey: given a key in object form it returns an equivalent key in string form. If includePropertyNames is set to true or not specified, the produced key will contain the property names for each sub-key.
Parameters:
Name Type Argument Description key
object The key in object form. If not in object form, this key is returned unchanged.
includePropertyNames
boolean <optional>
Whether or not to include property names in in the produced key. Defaults to true.
- Source:
- See:
Returns:
A equivalent key in string form.
- Type
- string
-
values() → {object[]}
-
- Source:
Returns:
An array of all values in the map. If the map contains duplicate values, so will this array.
- Type
- object[]


Screen {: .doctitle}
- Screen {: .doctitle}
- Synopsis
- Screen.Init()
- Screen.screens
- Screen.chooseDesktopMedia (sources, callback)
- Event: displayBoundsChanged(screen)
- Event: displayAdded (screen)
- Event: displayRemoved (screen)
- Screen.DesktopCaptureMonitor
- Synopsis
- Screen.DesktopCaptureMonitor.started
- Screen.DesktopCaptureMonitor.start(should_include_screens, should_include_windows)
- Screen.DesktopCaptureMonitor.stop()
- Event: added (id, name, order, type, primary)
- Event: removed (id)
- Event: orderchanged (id, new_order, old_order)
- Event: namechanged (id, name)
- Event: thumbnailchanged (id, thumbnail)
Screen
is an instance of EventEmitter object, and you’re able to use Screen.on(...)
to respond to native screen’s events.
Screen
is a singleton object, need to be initiated once by calling nw.Screen.Init()
Synopsis
//init must be called once during startup, before any function to nw.Screen can be called
nw.Screen.Init();
var screenCB = {
onDisplayBoundsChanged: function(screen) {
console.log('displayBoundsChanged', screen);
},
onDisplayAdded: function(screen) {
console.log('displayAdded', screen);
},
onDisplayRemoved: function(screen) {
console.log('displayRemoved', screen)
}
};
// listen to screen events
nw.Screen.on('displayBoundsChanged', screenCB.onDisplayBoundsChanged);
nw.Screen.on('displayAdded', screenCB.onDisplayAdded);
nw.Screen.on('displayRemoved', screenCB.onDisplayRemoved);
Screen.Init()
Init the Screen singleton object, you only need to call this once
Screen.screens
Get the array of screen (number of screen connected to the computer)
screen has following structure:
screen {
// unique id for a screen
id: int,
// physical screen resolution, can be negative, not necessarily start from 0,depending on screen arrangement
bounds: {
x: int,
y: int,
width: int,
height: int
},
// useable area within the screen bound
work_area: {
x: int,
y: int,
width: int,
height: int
},
scaleFactor: float,
isBuiltIn: bool,
rotation: int,
touchSupport: int
}
Screen.chooseDesktopMedia (sources, callback)
sources
{String[]}
array of source types. Two types are supported by this API:"screen"
and"window"
.callback
{Function}
callback function with chosed streamId. streamId will befalse
if failed to execute or existing session is alive.
Note
Screen sharing by selection; Currently only working in Windows and OSX and some linux distribution.
Example:
nw.Screen.Init(); // you only need to call this once
nw.Screen.chooseDesktopMedia(["window","screen"],
function(streamId) {
var vid_constraint = {
mandatory: {
chromeMediaSource: 'desktop',
chromeMediaSourceId: streamId,
maxWidth: 1920,
maxHeight: 1080
},
optional: []
};
navigator.webkitGetUserMedia({audio: false, video: constraint}, success_func, fallback_func);
}
);
Event: displayBoundsChanged(screen)
Emitted when the screen resolution, arrangement is changed, the callback is called with 1 argument screen
. See Screen.screens for the format.
Event: displayAdded (screen)
Emitted when a new screen added, the callback is called with 1 argument screen
. See Screen.screens for the format.
Event: displayRemoved (screen)
Emitted when existing screen removed, the callback is called with 1 argument screen
. See Screen.screens for the format.
Screen.DesktopCaptureMonitor
This API behaves similar functions as Screen.chooseDesktopMedia
. But it doesn’t have GUI. You can use this API to monitor the changes of screens and windows on desktop and implement your own UI.
Screen.DesktopCaptureMonitor
is an instance of EventEmitter
. You can use Screen.DesktopCaptureMonitor.on()
to listen to the events.
Synopsis
nw.Screen.Init();
nw.Screen.DesktopCaptureMonitor.on("added", function (id, name, order, type) {
//select first stream and shutdown
var constraints = {
audio: {
mandatory: {
chromeMediaSource: "system",
chromeMediaSourceId: id
}
},
video: {
mandatory: {
chromeMediaSource: 'desktop',
chromeMediaSourceId: id,
}
}
};
// TODO: call getUserMedia with contraints
nw.Screen.DesktopCaptureMonitor.stop();
});
nw.Screen.DesktopCaptureMonitor.on("removed", function (id) { });
nw.Screen.DesktopCaptureMonitor.on("orderchanged", function (id, new_order, old_order) { });
nw.Screen.DesktopCaptureMonitor.on("namechanged", function (id, name) { });
nw.Screen.DesktopCaptureMonitor.on("thumbnailchanged", function (id, thumbnail) { });
nw.Screen.DesktopCaptureMonitor.start(true, true);
Screen.DesktopCaptureMonitor.started
Boolean of whether the DesktopCaptureMonitor is started.
Screen.DesktopCaptureMonitor.start(should_include_screens, should_include_windows)
should_include_screens
{Boolean}
whether should include screensshould_include_windows
{Boolean}
whether should include windows
The DesktopCaptureMonitor
will start monitoring the system and trigger the the events. The screen may flicker if while DesktopCaptureMonitor
is running.
Screen.DesktopCaptureMonitor.stop()
The DesktopCaptureMonitor
will stop monitoring the system. The id
provided can be passed into chromeMediaSourceId
in getUserMedia
constraints. DesktopCaptureMonitor
should be stopped after a stream is selected.
Event: added (id, name, order, type, primary)
id
{String}
is unique id that can be passed as chromeMediaSourceIdname
{String}
is the title of the window or screenorder
{Integer}
is the z-order of the windows, if screens are selected they will appear firsttype
{String}
type of the stream: “screen”, “window”, “other” or “unknown”primary
{Boolean}
Windows OS only this will betrue
if the source is the primary monitor
Emit when a new source was added.
Event: removed (id)
id
{String}
is the chromeMediaSourceId of the screen or monitor that is no longer capturable
Emit when a source was removed.
Event: orderchanged (id, new_order, old_order)
id
{String}
is the chromeMediaSourceId of the screen or window that has changed z-ordernew_order
{Integer}
is the new z-orderold_order
{Integer}
is the old z-order
Emit when the Z-order of a source changed (this may change for windows as others are focused).
Event: namechanged (id, name)
id
{String}
is the chromeMediaSourceId of the screen or window that has a name changedname
{String}
is the new new name of the screen or window
Emit when the name of the source has changed. This can happen when a window changes title.
Event: thumbnailchanged (id, thumbnail)
id
{String}
is the chromeMediaSourceId of the screen or window that has an updated thumbnailthumbnail
{String}
is the base64 encoded png of the thumbnail
Emit when the thumbnail of a source changed.


Eagle-eyed Coronation Street fans spot 'familiar face' in Question Time audience
Viewers thought they recognised a member of the audience
by Lottie GibbonsCoronation Street fans believed they spotted a familiar face on BBC's Question Time tonight.
Jeremy Corbyn, Boris Johnson, Nicola Sturgeon and Jo Swinson took part in a political debate with a live audience tonight - with all party leaders receiving a grilling.
But a number of eagle-eyed Coronation Street fans were shocked when they recognised a member of the audience.
Referred to as 'the lady in the red jacket', the woman from Sheffield quizzed Liberal Democrats leader Ms Swinson over the party's policies on Universal Credit.
Whilst the woman eloquently discussed the negative affects of the benefit - users on Twitter were distracted by her resemblance.
Brenda said: "Was she a detective in #corrie recently? I'm sure I remember her questioning David Platt."
Another user wrote: "Who was that woman that asked Swinson a question with the red on? I know her face?"
One eagle-eyed super fan tried to clear things up in the comments section claiming: "From arresting Carla Connor to grilling Jo Swinson on benefits, this is one busy detective."
Fans believe the woman is Sheffield actress Kate Rutter who appeared on the Cobbles between March and July 2019 while investigating the collapse of Underworld's roof.
Fans may know her as DS Beckett on the soap.
She also starred as 'Ann' in the politically-charged drama film I, Daniel Blake.
According to her Twitter profile, she is a Labour supporter.


Mindset | Mental Health Matters.
Home
(current)
Register for Mindset
If you are a counselor, enter
additional information here.
Add All Counselor Names
Create Your Account
Made with ❤ in Minnesota
By Jorge Calderon, Lierin Hanuman, James Jorissen, Isabell Danell, Foos Mahamud and Anusha Dhamera


This is a simple hero unit, a simple jumbotron-style component for calling extra attention to featured content or information.
| Name | Description | Skils Used |
|---|---|---|
| SAP Salesforce Integration | Integration with Primary SAP and AMR SAP servers in Salesforce | Force.com, Segmentation |
| Inkstroke Toolkit | Simple inkstroke lib made in JS to display a predfined eSignature submission | JS, NodeJS and CSS |
| Dash Docset Generation | VistaJS offline documentation | Python and mySQLite |
| Email Server Domain | Intern Email Server project | C/C++ |
| Laughing Bacchus Winecellars | Yoshi Tannamuri | Canada |
| Magazzini Alimentari Riuniti | Giovanni Rovelli | Italy |


Home
CV
Proyects
Links
Contact
Automating Doge to MXN
Techonologies
Bash
Vim
API's
Skills
Programming
File management
Operating Systems
Problems solved
Understanding how API's work
Debugging


The Architecture department of Universidad de los Andes, provided all the basic data used in this project. The first step was the basic analysis and data characterization in order to stablish the boundaries of the study and any other alternative data required to execute the analysis.
After the data characterization and the tasks required by the user, begin the data analysis process, where the team stablish the tools and visualization that allows to fulfill the tasks and presents valuable insights.
After all the analysis, the final results are presented in order to stablish the validity of the hypothesis, Does the school’s environment affects students performance?.


Module
BasicTemperature
lib/basic_temperature.rb
lib/basic_temperature/temperature.rb
lib/basic_temperature/temperature/additional_helpers.rb
lib/basic_temperature/temperature/assertions.rb
lib/basic_temperature/temperature/casting.rb
lib/basic_temperature/temperature/errors.rb
lib/basic_temperature/temperature/initialization.rb
lib/basic_temperature/temperature/memoization.rb
lib/basic_temperature/temperature/rounding.rb
lib/basic_temperature/version.rb
Namespace
CLASS
BasicTemperature::Temperature
Constants
VERSION
=
'0.2.2'


We can't find what you are looking for {{component | replaceDash | capitalize}} is not available in this version of the Collab UI Library. Try one of the other libraries below.


python-documentcloud¶
A simple Python wrapper for the DocumentCloud API
Features¶
- Retrieve and edit documents and projects, both public and private, from documentcloud.org
- Upload PDFs into your documentcloud.org account and organize them into projects
- Download text, images and entities extracted from your PDFs by DocumentCloud
Documentation¶
Contributing¶
- Code repository: https://github.com/datadesk/python-documentcloud
- Issues: https://github.com/datadesk/python-documentcloud/issues
- Packaging: https://pypi.python.org/pypi/python-documentcloud
- Testing: https://travis-ci.org/datadesk/python-documentcloud
- Coverage: https://coveralls.io/r/datadesk/python-documentcloud


image by Casey Horner
image by Dave Hoefler
image by Dave Hoefler
image by Greg Rakozy
image by Kace Rodriguez
image by Philip Swinburn
image by Nick Chung
image by v2osk
image by Kunal Shinde
image by Casey Horner
image by Dave Hoefler
image by Dave Hoefler
image by Greg Rakozy
image by Kace Rodriguez
image by Philip Swinburn
image by Nick Chung
image by v2osk
image by Kunal Shinde


dwr.util.removeAllRows(id);
Removes all the rows in a table element specified by id. For worked examples see the tables documentation.


Image gallery
Upload photos that highlight your business.
Business details
Business tags
Select relevant tags from each section to describe your business.
Cuisines
Categories
Food specifications
Announcements
Add any important updates about your business here.
Business story
Share your story with your community.
Business hours
Set open hours for your business by adding days and times.


Welcome to Use My Tech Stuff
Here at Use My Tech Stuff we are bridging the gap between renters and owners of high-end tech gear.
Use My Tech Stuff was created by people who desired to improve the connection between renters and owners . Our app allows people in need of high-end tech gear to temporarily rent them. This will allow those who have high-end tech gear to earn extra money.


| Invoice # | |
| Date | |
| Amount Due |
{{ subTotal()-invoice.paid | currency}}
|
| Client: | |
| Subject: |
| Subtotal |
{{subTotal() | currency}}
|
| Total |
{{subTotal() | currency}}
|
| Amount Paid | |
| Balance Due |
{{subTotal() - invoice.paid | currency}}
|


YG Entertainment confirms Taeyang and Daesung will be discharged next week
by jennywillYG Entertainment has officially confirmed Taeyang and Daesung's discharge date.
The label wrote, "Hello, this is YG Entertainment. We are letting you know details about Big Bang's Taeyang's and Daesung's discharge. According to the Ministry of Defense on the 4th, Taeyang and Daesung will be discharged on November 10th from Gyeonggi-do Yongin's Ground Operation Headquarters. Their current locations are one of the locations being cared for the ASF virus, and because fans and media are expected to come to their discharge, the Ministry of Defense decided to change where they will be discharged. Additionally, it will be hard to have parking at their changed location as well, and the location is very small, and there is concern of safety for both fans and media. We ask that you do not come visit. We sincerely thank everyone who has been waiting for Taeyang and Daesung's discharge, and we ask once again for your understanding and cooperation. Thank you."
Are you excited for the two of them to be discharged?


Everyone has a Price
Got this email this morning:
From: Andrew
To<EMAIL_ADDRESS>Subject: Have a minute to talk about npmjs.org?
Hello,
We have a client interested in npmjs.org. Would you
consider selling the site?
Please let me know a day, time and phone number
you could speak about this possibility and we'll try
to make it work on our end.
I look forward to speaking with you.
Regards,
My reply:
From: Isaac Schlueter
To: Andrew
I will sell npmjs.org for USD $1,000,000,000.00.
Just so you know. If npmjs.org ever suddenly turns into some random e-commerce site or something, and I’m nowhere to be found, it’s because I’m crazy rich now and give zero fucks.


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/ml.20methods.20in.20interactive.20theorem.20proving.html ---
interesting paper here: "GamePad: A Learning Environment for Theorem Proving" https://arxiv.org/abs/1806.00608
unfortunately the conclusion is the same as it has been for the past 30 years... not quite there yet, needs more funding and research :)
"We also note that position evaluation <omitted> should assign a high number to proof states which do not yet contain the requisite hypotheses to prove the current goal." This metric (representing how far someone is from completing a proof) seems so silly - sadly I can't check how well this works in practice without compiling their entire project because their results sub-chapter doesn't say much :(.
i wish they had dealt with have
statements properly. in a way, they can be regarded as additional lemmas
I can't get it to compile. I wanted to check how many steps would be predicted for FLT to reaffirm myself in the belief that this is an incredibly random metric :).
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


| Top |
| guint | soup_get_major_version () |
| guint | soup_get_minor_version () |
| guint | soup_get_micro_version () |
| gboolean | soup_check_version () |
| #define | SOUP_MAJOR_VERSION |
| #define | SOUP_MINOR_VERSION |
| #define | SOUP_MICRO_VERSION |
| #define | SOUP_CHECK_VERSION() |
| #define | SOUP_VERSION_MIN_REQUIRED |
| #define | SOUP_VERSION_MAX_ALLOWED |
| #define | SOUP_VERSION_2_24 |
| #define | SOUP_VERSION_2_26 |
| #define | SOUP_VERSION_2_28 |
| #define | SOUP_VERSION_2_30 |
| #define | SOUP_VERSION_2_32 |
| #define | SOUP_VERSION_2_34 |
| #define | SOUP_VERSION_2_36 |
| #define | SOUP_VERSION_2_38 |
| #define | SOUP_VERSION_2_40 |
| #define | SOUP_VERSION_2_42 |
| #define | SOUP_VERSION_2_44 |
| #define | SOUP_VERSION_2_46 |
guint
soup_get_major_version (void
);
Returns the major version number of the libsoup library. (e.g. in libsoup version 2.42.0 this is 2.)
This function is in the library, so it represents the libsoup library your code is running against. Contrast with the SOUP_MAJOR_VERSION macro, which represents the major version of the libsoup headers you have included when compiling your code.
Since 2.42
guint
soup_get_minor_version (void
);
Returns the minor version number of the libsoup library. (e.g. in libsoup version 2.42.0 this is 42.)
This function is in the library, so it represents the libsoup library your code is running against. Contrast with the SOUP_MINOR_VERSION macro, which represents the minor version of the libsoup headers you have included when compiling your code.
Since 2.42
guint
soup_get_micro_version (void
);
Returns the micro version number of the libsoup library. (e.g. in libsoup version 2.42.0 this is 0.)
This function is in the library, so it represents the libsoup library your code is running against. Contrast with the SOUP_MICRO_VERSION macro, which represents the micro version of the libsoup headers you have included when compiling your code.
Since 2.42
gboolean soup_check_version (guint major
,guint minor
,guint micro
);
Like SOUP_CHECK_VERSION, but the check for soup_check_version is at runtime instead of compile time. This is useful for compiling against older versions of libsoup, but using features from newer versions.
major |
the major version to check |
|
minor |
the minor version to check |
|
micro |
the micro version to check |
TRUE
if the version of the libsoup currently loaded
is the same as or newer than the passed-in version.
Since 2.42
#define SOUP_MAJOR_VERSION (2)
Like soup_get_major_version()
, but from the headers used at
application compile time, rather than from the library linked
against at application run time.
Since 2.42
#define SOUP_MINOR_VERSION (47)
Like soup_get_minor_version()
, but from the headers used at
application compile time, rather than from the library linked
against at application run time.
Since 2.42
#define SOUP_MICRO_VERSION (4)
Like soup_get_micro_version()
, but from the headers used at
application compile time, rather than from the library linked
against at application run time.
Since 2.42
#define SOUP_CHECK_VERSION(major, minor, micro)
Macro to test the version of libsoup being compiled against.
major |
major version (e.g. 2 for version 2.42.0) |
|
minor |
minor version (e.g. 42 for version 2.42.0) |
|
micro |
micro version (e.g. 0 for version 2.42.0) |
TRUE
if the version of the libsoup header files
is the same as or newer than the passed-in version.
Since 2.42
# define SOUP_VERSION_MIN_REQUIRED (SOUP_VERSION_CUR_STABLE)
A macro that should be defined by the user prior to including
libsoup.h. The definition should be one of the predefined libsoup
version macros: SOUP_VERSION_2_24
, SOUP_VERSION_2_26
, ...
This macro defines the earliest version of libsoup that the package is required to be able to compile against.
If the compiler is configured to warn about the use of deprecated
functions, then using functions that were deprecated in version
SOUP_VERSION_MIN_REQUIRED
or earlier will cause warnings (but
using functions deprecated in later releases will not).
Since 2.42
# define SOUP_VERSION_MAX_ALLOWED (SOUP_VERSION_CUR_STABLE)
A macro that should be defined by the user prior to including
libsoup.h. The definition should be one of the predefined libsoup
version macros: SOUP_VERSION_2_24
, SOUP_VERSION_2_26
, ...
This macro defines the latest version of the libsoup API that the package is allowed to make use of.
If the compiler is configured to warn about the use of deprecated
functions, then using functions added after version
SOUP_VERSION_MAX_ALLOWED
will cause warnings.
Unless you are using SOUP_CHECK_VERSION()
or the like to compile
different code depending on the libsoup version, then this should be
set to the same value as SOUP_VERSION_MIN_REQUIRED
.
Since 2.42
#define SOUP_VERSION_2_24 (SOUP_ENCODE_VERSION (2, 24))
A macro that evaluates to the 2.24 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_26 (SOUP_ENCODE_VERSION (2, 26))
A macro that evaluates to the 2.26 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_28 (SOUP_ENCODE_VERSION (2, 28))
A macro that evaluates to the 2.28 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_30 (SOUP_ENCODE_VERSION (2, 30))
A macro that evaluates to the 2.30 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_32 (SOUP_ENCODE_VERSION (2, 32))
A macro that evaluates to the 2.32 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_34 (SOUP_ENCODE_VERSION (2, 34))
A macro that evaluates to the 2.34 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_36 (SOUP_ENCODE_VERSION (2, 36))
A macro that evaluates to the 2.36 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_38 (SOUP_ENCODE_VERSION (2, 38))
A macro that evaluates to the 2.38 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_40 (SOUP_ENCODE_VERSION (2, 40))
A macro that evaluates to the 2.40 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_42 (SOUP_ENCODE_VERSION (2, 42))
A macro that evaluates to the 2.42 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.42
#define SOUP_VERSION_2_44 (SOUP_ENCODE_VERSION (2, 44))
A macro that evaluates to the 2.44 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.44
#define SOUP_VERSION_2_46 (SOUP_ENCODE_VERSION (2, 46))
A macro that evaluates to the 2.46 version of libsoup, in a format
that can be used by SOUP_VERSION_MIN_REQUIRED
and
SOUP_VERSION_MAX_ALLOWED
.
Since 2.46


class ItemHolder : MaterialPopupMenuBuilder.AbstractItemHolder
Holds section item info for the builder. This gets converted to MaterialPopupMenu.PopupMenuItem.
ItemHolder()
Holds section item info for the builder. This gets converted to MaterialPopupMenu.PopupMenuItem. |
var hasNestedItems: Boolean
Optional. If set to true this will show a "menu-end" icon, which indicates that there might be a submenu shown. false by default. |
|
var icon: Int
Optional icon to be displayed together with the label. |
|
var iconColor: Int
Optional icon tint color. |
|
var iconDrawable: Drawable?
Optional icon to be displayed together with the label. |
|
var label: CharSequence?
Item label. |
|
var labelColor: Int
Optional text color of the label. If not set or 0 the default color will be used. |
|
var labelRes: Int
Item label. |
var callback: () -> Unit
Callback to be invoked once an item gets selected. |
|
var dismissOnSelect: Boolean
Whether to dismiss the popup once an item gets selected.
Defaults to |
|
var viewBoundCallback: (View) -> Unit
Callback to be invoked once the item view gets created and bound. It is to be used when some views inside need to be updated once inflated. |
fun toString(): String |
fun resolveViewBoundCallback(): ViewBoundCallback |


Ping-Pong
About Ping Pong
Created by Derrick
Play?
Learn More
See magic
Let's play!
Rules:
Ping pong will count all your numbers from 1 with the following exceptions
Numbers divisible by 3 become "ping"
Numbers divisible by 5 become "pong"
Numbers divisible by both 3 and 5 become "pingpong"
Enter your number here:
Ping Pong


public class CustomPasswordFilter
extends java.lang.Object
| Modifier and Type | Method and Description |
|---|---|
static CustomPasswordFilter |
getInstance(java.lang.String alphabetSet,
int minAlphabets,
java.lang.String digitSet,
int minDigits,
java.lang.String symbolSet,
int minSymbols,
int minCharacter,
int maxCharacter)
This function returns an instance of CustomPasswordFilter.
|
public static CustomPasswordFilter getInstance(java.lang.String alphabetSet, int minAlphabets, java.lang.String digitSet, int minDigits, java.lang.String symbolSet, int minSymbols, int minCharacter, int maxCharacter) throws InvalidFormatException
alphabetSet
- String of alphabets that the password may contain. Separate alphabets for uppercase and lowercase. The alphabets need to be put sequentially without any space.
For example, "ABCdef" will check for A,B,C,d,e,f and will not allow a,b,c,D,E,F.
minAlphabets
- The minimum number of alphabet characters that the custom password may contain.digitSet
- String of digits that the password may contain. The digits need to be put sequentially without any space.
For example, "0178" will check for 0,1,7,8.
minDigits
- The minimum number of digit characters that the custom password may contain.symbolSet
- String of symbols that the password may contain. The set of symbols permitted are $,@,!,%,*,#,?,& The digits need to be put sequentially without any space.minSymbols
- The minimum number of symbol characters that the custom password may contain.minCharacter
- Total number of minimum characters the password might contain.maxCharacter
- Total number of maximum characters the password might contain.
In case of unrestricted maximum characters, put maxCharacter as 0.InvalidFormatException
- Throws exception if any of the input strings of alphabets, digits or symbols are invalid.


{% include head.html%} {% include head_custom.html%}
{% include asu_header.html %} {% include navigation_outer.html %}
{% include main_image.html%} {{ content }}
{% include footer.html %} {% include foot.html %} {% include foot_custom.html %}


The goal of this framework is to allow modders to make generic materials for creatures much quicker and easier than the old method of "Create Creature with Material(s), Create new Tissue_Templates to use the generic material(s), create BDPs that use new templates" which if you wanted to do more than one type of generic material (white meat, red meat, reptiles, avians, canines, etc) it's a lot of cloning of templates just to do that.
That is where these Creature Vartiant files come into play, now you don't need to touch too much of vanilla (BDPs, Templates) you just need to setup your creatures that have the materials you want, then override the existing tissues in the creatures you want. Will there still be a lot of find/replace and fine tuning, yes, but now you don't have to worry about creating a whole batch of templates and other things to get it done.
This can also be used on a smaller scale, say you wanted to make Holy dwarves, Demon Dwarves, Hill Dwarves. And you didn't want there to be 3-4 or 50 dwarf materials, you can use this framework to say Holy Dwarves use vanilla DWARF materials, and now you've already cut down on the number of materials, but still keeping the core list of vanilla intact.
This is normally CHITIN but can be anything you want
This is basically used for FAT layers
This is basically MUSCLE layers
This will add to all tissue ids (even the ones passed in) to be _"SUFFIX" that you pass in, so basically if you used [BODY_DETAIL_PLAN:this-method:CHITIN:FAT:MUSCLE:TOUGH] the inner workings would translate say a line like this: [BP_LAYERS:BY_CATEGORY:BODY:ARG3_ARG4:6:ARG2_ARG4:1:ARG1_ARG4:2] into [BP_LAYERS:BY_CATEGORY:BODY:MUSCLE_TOUGH:6:FAT_TOUGH:1:CHITIN_TOUGH:2] of course all organ or hard references will also get suffixed with _"SUFFIX"
Filled example:
b_detail_plan_0_basic
MOLLUSC_TISSUE_LAYERS_SUFFIX
<skin_tissue_layer>
<fat_tissue_layer>
<muscle_tissue_layer>
<tissue_id_suffix>
This is normally SKIN but can be anything you want
This is basically used for FAT layers
This is basically MUSCLE layers
This will add to all tissue ids (even the ones passed in) to be _"SUFFIX" that you pass in, so basically if you used [BODY_DETAIL_PLAN:this-method:SKIN:FAT:MUSCLE:TOUGH] the inner workings would translate say a line like this: [BP_LAYERS:BY_CATEGORY:BODY:ARG3_ARG4:6:ARG2_ARG4:1:ARG1_ARG4:2] into [BP_LAYERS:BY_CATEGORY:BODY:MUSCLE_TOUGH:6:FAT_TOUGH:1:SKIN_TOUGH:2] of course all organ or hard references will also get suffixed with _"SUFFIX"
Filled example:
b_detail_plan_0_basic
VERTEBRATE_TISSUE_LAYERS_CARTILAGE_SUFFIX
<skin_tissue_layer>
<fat_tissue_layer>
<muscle_tissue_layer>
<bone_tissue_layer>
<tissue_id_suffix>
This is normally SKIN but can be anything you want
This is basically used for FAT layers
This is basically MUSCLE layers
This is basically BONE layers
This will add to all tissue ids (even the ones passed in) to be _"SUFFIX" that you pass in, so basically if you used [BODY_DETAIL_PLAN:this-method:SKIN:FAT:MUSCLE:BONE:TOUGH] the inner workings would translate say a line like this: [BP_LAYERS:BY_CATEGORY:LEG_UPPER:ARG4_ARG5:25:ARG3_ARG5:25:ARG2_ARG5:5:ARG1_ARG5:1] into [BP_LAYERS:BY_CATEGORY:LEG_UPPER:BONE_TOUGH:25:MUSCLE_TOUGH:25:FAT_TOUGH:5:SKIN_TOUGH:1] of course all organ or hard references will also get suffixed with _"SUFFIX"
*** This method assumes there is a CARTILAGE_"SUFFIX" tissue, and will apply it as it would with vanilla's VERTEBRATE_TISSUE_LAYERS if ARG5 was CARTILAGE instead of SUFFIX.
Filled example:
c_variation_0_tissue_generic
ADD_TISSUE
<tissue_id>
<tissue_template>
<material>
Can be anything as long as it hasn't been used before example would be SKIN.
This will be the TISSUE_TEMPLATE that this tissue will use.
The material that will override the tissue's material, however as it is a CV you will have to use '|' pipes in place of ':' colons. Example CREATURE_MAT|DOG|LEATHER or INORGANIC|IRON
Filled example:
c_variation_0_tissue_generic
ADD_TISSUE_NAME
<tissue_id>
<tissue_template>
<material>
<tissue_name>
Can be anything as long as it hasn't been used before example would be SKIN.
This will be the TISSUE_TEMPLATE that this tissue will use, so to match with 1. you'd use SKIN_TEMPLATE but it can honestly be any other template you want FAT_TEMPLATE, etc.
The material that will override the tissue's material, however as it is a CV you will have to use '|' pipes in place of ':' colons. Example CREATURE_MAT|DOG|LEATHER or INORGANIC|IRON
This will override the tissues name to what is given membrane|NP so like the example from 1. this would create a tissue with the ID of SKIN using the SKIN_TEMPLATE the Material would be IRON but instead of being called "skin" it will be called "membrane".
Filled example:
c_variation_0_basic
BLOOD_TYPE
<blood_type>
<blood_type> can be one of these values: RED, BLUE, AQUA, YELLOW, ICHOR, GOO
Filled example:
c_variation_0_tissue_vanilla_clone
CHITIN_CREATURE_TISSUES
<creature_id>
This will be the creature that will be used to set the material, it also assumes that the <tissue_id> also matches the material_id, like the above example of FAT in vanilla there is a FAT material, FAT tissue template, and then the FAT tissue that is built from the tissue template and uses the FAT material.
*** This method basically adds all tissues that vanilla's BDP CHITIN_TISSUES adds, only sets the material to that of the picked creature
Filled example:
c_variation_0_tissue_generic
COPY_CREATURE_TISSUE
<creature_id>
<tissue_id>
This will be the creature that will be used to set the material, it also assumes that the <tissue_id> also matches the material_id, like the above example of FAT in vanilla there is a FAT material, FAT tissue template, and then the FAT tissue that is built from the tissue template and uses the FAT material.
This method goes off the assumption that the <tissue_id> will also match a "tissue_id_TEMPLATE" Example is FAT this method assumes there is a FAT_TEMPLATE to use, however using something like IRONSKIN there will need to be an IRONSKIN_TEMPLATE which in vanilla does not exist.
*** This method is mostly used in cases where you might want to USE an already familar vanilla material/tissue combo like having a bird use the FEATHER of another bird, so that you don't clutter up the number of materials in game (BIRD has FEATHER material, BIRD_EVIL_VERSION uses the FEATHER material from BIRD for its FEATHER tissue)
Filled example:
c_variation_0_tissue_generic
COPY_CREATURE_TISSUE_TEMPLATE
<creature_id>
<tissue_id>
<tissue_template>
Same as COPY_CREATURE_TISSUE arguement 1
Same as COPY_CREATURE_TISSUE arguement 2
Tissue_Template that should be used to copy an existing tissue
Filled example:
c_variation_0_tissue_generic
COPY_CREATURE_TISSUE_TEMPLATE_NAME
<creature_id>
<tissue_id>
<tissue_template>
<tissue_name>
Same as COPY_CREATURE_TISSUE arguement 1
Same as COPY_CREATURE_TISSUE arguement 2
Tissue_Template that should be used to copy an existing tissue
Name the tissue should use.
Filled example:
c_variation_0_tissue_generic
COPY_TWO_CREATURE_TISSUES
<creature_id>
<tissue_id>
<tissue_id>
Exactly like COPY_TISSUE_CREATURE only you can copy two tissues at the same time, mostly used for HOOF and HORN combos.
Filled example:
c_variation_0_basic
EGG_LAYERS_LEATHERY_SIZE
<creature_id>
<is_leathery>
<eggsize>
Creature to take the egg materials from.
This can be only two values, YES or NO. YES will make the eggshell from a EGGSHELL_LEATHERY material, if it is NO it will make the eggshell with a EGGSHELL material. If this is any other value the egg will only have WHITE and YOLK
Size of the egg(s) in cm3
Filled example:
c_variation_0_tissue_modular
EYE_FEATURES_TISSUE_CREATURE
<creature_id>
Creature to take the HAIR materials from.
*** this will also apply the eyebrows and eye lashes
Filled example:
c_variation_0_tissue_modular
FACIAL_HAIR_TISSUE_CREATURE
<creature_id>
Creature to take the HAIR materials from.
*** unlike EYE_FEATURES_TISSUE_CREATURE this will not apply the tissues, please use [BODY_DETAIL_PLAN:FACIAL_HAIR_TISSUE_LAYERS] like usual.
Filled example:
c_variation_0_tissue_generic
MOD_TISSUE_MAT
<tissue_id>
<material>
Tissue to start to modify.
The material that will override the tissue's material, however as it is a CV you will have to use '|' pipes in place of ':' colons. Example CREATURE_MAT|DOG|LEATHER or INORGANIC|IRON
Filled example:
c_variation_0_tissue_generic
MOD_TISSUE_MAT_NAME
<tissue_id>
<material>
<tissue_name>
Tissue to start to modify.
The material that will override the tissue's material, however as it is a CV you will have to use '|' pipes in place of ':' colons. Example CREATURE_MAT|DOG|LEATHER or INORGANIC|IRON
This will override the tissues name to what is given.
Filled example:
c_variation_0_tissue_modular
NAIL_TISSUE_CREATURE
<creature_id>
<nail_type>
<layer_on_fingers>
<layer_on_toes>
Creature to take the materials from.
Nail type to use which is NAIL, CLAW, or TALON.
If this is YES it will then apply this tissue to the FRONT of all bodyparts categorized as FINGER
If this is YES it will then apply this tissue to the FRONT of all bodyparts categorized as TOE
Filled example:
c_variation_0_basic
PUS_INFECTWOUNDS_INFECTROT
<infections_from_wounds>
<infections_from_rot>
Does this creature get infections from wounds, YES
Does this creature get infections from rot, YES
*** This method will always apply the [PUS] tag.
Filled example:
c_variation_0_tissue_vanilla_clone
STANDARD_CREATURE_TISSUES
<creature_id>
Creature to take the materials from.
Filled example:
c_variation_0_tissue_vanilla_clone
STANDARD_CREATURE_TISSUES_LITE
<creature_id>
Creature to take the materials from.
*** This version only adds internal materials like organs,
Filled example:
c_variation_0_tissue_modular
STRAND_TISSUES_CREATURE
<creature_id>
<strand_type>
Creature to take the materials from.
strand type to use which is HAIR, FUR, WOOL, or FEATHER. (however FEATHER is not a tissue_layer:strands, they are still regarded to act like hair like tissues)
Filled example:
c_variation_0_basic
SWEAT_CRY_SPIT
<sweats>
<cries>
<spits>
Does this creature have SKIN and can sweat if over exterted, YES
Does this creature cry when under stress, YES
Does this creature spit when angry or tormented, YES
Filled example:
c_variation_0_tissue_modular
TENDONS_LIGAMENTS_CREATURE
<creature_id>
<healing_rate>
Creature to use SINEW from.
Rate in which tendons and ligaments will heal at, default is 200 (twice as long as SKIN)
Filled example:
c_variation_0_tissue_modular
TENDONS_LIGAMENTS_DEFAULT
No Arguments
Uses a Generic Creatures SINEW material, does everything for you.
Filled example:


Forum: CompilerIssue: COMPILE-FILE-HANDLING-OF-TOP-LEVEL-FORMS
References: CLtL pages 66-70, 143
Category: CLARIFICATION
Edit history: V1, 07 Oct 1987 Sandra Loosemore
V2, 15 Oct 1987 Sandra Loosemore
V3, 15 Jan 1988 Sandra Loosemore
V4, 06 May 1988 Sandra Loosemore
V5, 20 May 1988 Sandra Loosemore
V6, 09 Jun 1988 Sandra Loosemore
V7, 16 Dec 1988 Sandra Loosemore
(Comments from Pitman, change DEFCONSTANT, etc.)
V8, 31 Dec 1988 Sandra Loosemore
(CLOS additions, etc.)
V9, 23 Jan 1989 Sandra Loosemore
(remove the CLOS additions again)
Status: Proposal CLARIFY passed Jan 89
Problem Description:
Standard programming practices assume that, when calls to defining
macros such as DEFMACRO and DEFVAR are processed by COMPILE-FILE,
certain side-effects occur that affect how subsequent forms in the
file are compiled. However, these side-effects are not mentioned in
CLtL, except for a passing mention that macro definitions must be
``seen'' by the compiler before it can compile calls to those macros
correctly. In order to write portable programs, users must know
exactly which defining macros have compile-time side-effects and what
those side-effects are.
Inter-file compilation dependencies are distinct from, and not
addressed by, this issue.
Proposal: COMPILE-FILE-HANDLING-OF-TOP-LEVEL-FORMS:CLARIFY
(1) Clarify that defining macros such as DEFMACRO or DEFVAR, appearing
within a file being processed by COMPILE-FILE, normally have
compile-time side effects which affect how subsequent forms in the
same file are compiled. A convenient model for explaining how these
side effects happen is that the defining macro expands into one or
more EVAL-WHEN forms, and that the calls which cause the compile-time
side effects to happen appear in the body of an (EVAL-WHEN (COMPILE)
...) form.
(2) The affected defining macros and their specific side effects are
as follows. In each case, it is identified what users must do to
ensure that their programs are conforming, and what compilers must do
in order to correctly process a conforming program.
DEFTYPE: Users must ensure that the body of a DEFTYPE form is
evaluable at compile time if the type is referenced in subsequent type
declarations. The compiler must ensure that the DEFTYPE'd type
specifier is recognized in subsequent type declarations. If the
expansion of a type specifier is not defined fully at compile time
(perhaps because it expands into an unknown type specifier or a
SATISFIES of a named function that isn't defined in the compile-time
environment), an implementation may ignore any references to this type
in declarations and/or signal a warning.
DEFMACRO, DEFINE-MODIFY-MACRO: The compiler must store macro
definitions at compile time, so that occurrences of the macro later on
in the file can be expanded correctly. Users must ensure that the
body of the macro is evaluable at compile time if it is referenced
within the file being compiled.
DEFUN: DEFUN is not required to perform any compile-time side effects.
In particular, DEFUN does not make the function definition available
at compile time. An implementation may choose to store information
about the function for the purposes of compile-time error-checking
(such as checking the number of arguments on calls), or to enable the
function to be expanded inline.
DEFVAR, DEFPARAMETER: The compiler must recognize that the variables
named by these forms have been proclaimed special. However, it must
not evaluate the initial value form or SETQ the variable at compile
time.
DEFCONSTANT: The compiler must recognize that the symbol names a
constant. An implementation may choose to evaluate the value-form at
compile time, load time, or both. Therefore users must ensure that
the value-form is evaluable at compile time (regardless of whether or
not references to the constant appear in the file) and that it always
evaluates to the same value.
DEFSETF, DEFINE-SETF-METHOD: The compiler must make SETF methods
available so that it may be used to expand calls to SETF later on in
the file. Users must ensure that the body of DEFINE-SETF-METHOD and
the complex form of DEFSETF are evaluable at compile time if the
corresponding place is referred to in a subsequent SETF in the same
file. The compiler must make these SETF methods available to
compile-time calls to GET-SETF-METHOD when its environment argument is
a value received as the &ENVIRONMENT parameter of a macro.
DEFSTRUCT: The compiler must make the structure type name recognized
as a valid type name in subsequent declarations (as for DEFTYPE) and
make the structure slot accessors known to SETF. In addition, the
compiler must save enough information about the structure type so that
further DEFSTRUCT definitions can :INCLUDE a structure type defined
earlier in the file being compiled. The functions which DEFSTRUCT
generates are not defined in the compile time environment, although
the compiler may save enough information about the functions to code
subsequent calls inline. The #S reader syntax may or may not be
available at compile time.
DEFINE-CONDITION: The rules are essentially the same as those for
DEFSTRUCT; the compiler must make the condition type recognizable as a
valid type name, and it must be possible to reference the condition
type as the parent-type of another condition type in a subsequent
DEFINE-CONDITION in the file being compiled.
DEFPACKAGE: All of the actions normally performed by this macro at load
time must also be performed at compile time.
(3) The compile-time side effects may cause information about the
definition to be stored differently than if the defining macro had
been processed in the "normal" way (either interpretively or by loading
the compiled file).
In particular, the information stored by the defining macros at
compile time may or may not be available to the interpreter (either
during or after compilation), or during subsequent calls to COMPILE or
COMPILE-FILE. For example, the following code is nonportable because
it assumes that the compiler stores the macro definition of FOO where
it is available to the interpreter:
(eval-when (eval compile load)
(print (foo '(a b c))))
A portable way to do the same thing would be to include the macro
definition inside the EVAL-WHEN:
(eval-when (eval compile load)
(print (foo '(a b c))))
Rationale:
The proposal generally reflects standard programming practices. The
primary purpose of the proposal is to make an explicit statement that
CL supports the behavior that most programmers expect and many
implementations already provide.
The primary point of controversy on this issue has been the treatment
of the initial value form by DEFCONSTANT, where there is considerable
variance between implementations. The effect of the current wording is
to legitimize all of the variants.
Current Practice:
Many (probably most) Common Lisp implementations, including VaxLisp
and Lucid Lisp, are already largely in conformance.
In VaxLisp, macro definitions that occur as a side effect of compiling
a DEFMACRO form are available to the compiler (even on subsequent
calls to COMPILE or COMPILE-FILE), but are not available to the
interpreter (even within the file being compiled).
By default, Kyoto Common Lisp evaluates *all* top level forms as they
are compiled, which is clearly in violation of the behavior specified
on p 69-70 of CLtL. There is a flag to disable the compile-time
evaluation, but then macros such as DEFMACRO, DEFVAR, etc. do not make
their definitions available at compile-time either.
Cost to implementors:
The intent of the proposal is specifically not to require the compiler
to have special knowledge about each of these macros. In
implementations whose compilers do not treat these macros as special
forms, it should be fairly straightforward to use EVAL-WHENs in their
expansions to obtain the desired compile-time side effects.
Cost to users:
Since CLtL does not specify whether and what compile-time side-effects
happen, any user code which relies on them is, strictly speaking,
nonportable. In practice, however, most programmers already expect
most of the behavior described in this proposal and will not find it
to be an incompatible change.
Benefits:
Adoption of the proposal will provide more definite guidelines on how
to write programs that will compile correctly under all CL
implementations.
Discussion:
Reaction to a preliminary version of this proposal on the common-lisp
mailing list was overwhelmingly positive. More than one person
responded with comments to the effect of "but doesn't CLtL already
*say* that somewhere?!?" Others have since expressed a more lukewarm
approval.
It has been suggested that this proposal should also include PROCLAIM.
However, since PROCLAIM is not a macro, its compile-time side effects
cannot be handled using the EVAL-WHEN mechanism. A separate proposal
seems more appropriate.
Item (3) allows for significant deviations between implementations.
While there is some sentiment to the effect that the compiler should
store definitions in a manner identical to that of the interpreter,
other people believe strongly that compiler side-effects should be
completely invisible to the interpreter. The author is of the opinion
that since this is a controversial issue, further attempts to restrict
this behavior should be considered as separate proposals.
It should be noted that user-written code-analysis programs must
generally treat these defining macros as special forms and perform
similar "compile-time" actions in order to correctly process
conforming programs.


join - Create a string by joining together list elements
join list ?joinString?
The list argument must be a valid Tcl list.
This command returns the string
formed by joining all of the elements of list together with
joinString separating each adjacent pair of elements.
The joinString argument defaults to a space character.
Making a comma-separated list:
set data {1 2 3 4 5}
join $data ", "
→ 1, 2, 3, 4, 5
Using join to flatten a list by a single level:
set data {1 {2 3} 4 {5 {6 7} 8}}
join $data
→ 1 2 3 4 5 {6 7} 8
list, lappend, split
element, join, list, separator
Copyright © 1995-1997 Roger E. Critchlow Jr.
Copyright © 1993 The Regents of the University of California.
Copyright © 1994-1996 Sun Microsystems, Inc.


"LIME" The Hebrew word so rendered means “boiling” or “effervescing.” From Isaiah 33:12 it appears that lime was made in a kiln lighted by thorn-bushes. In Amos 2:1 it is recorded that the king of Moab “burned the bones of the king of Edom into lime.” The same Hebrew word is used in Deuteronomy 27:2-4, and is there rendered “plaster.” Limestone is the chief constituent of the mountains of Syria.
"LIME" The Hebrew word so rendered means “boiling” or “effervescing.” From Isaiah 33:12 it appears that lime was made in a kiln lighted by thorn-bushes. In Amos 2:1 it is recorded that the king of Moab “burned the bones of the king of Edom into lime.” The same Hebrew word is used in Deuteronomy 27:2-4, and is there rendered “plaster.” Limestone is the chief constituent of the mountains of Syria.


HDFS supports writing to off-heap memory managed by the Data Nodes. The Data Nodes will flush in-memory data to disk asynchronously thus removing expensive disk IO and checksum computations from the performance-sensitive IO path, hence we call such writes Lazy Persist writes. HDFS provides best-effort persistence guarantees for Lazy Persist Writes. Rare data loss is possible in the event of a node restart before replicas are persisted to disk. Applications can choose to use Lazy Persist Writes to trade off some durability guarantees in favor of reduced latency.
This feature is available starting with Apache Hadoop 2.6.0 and was developed under Jira HDFS-6581.
The target use cases are applications that would benefit from writing relatively low amounts of data (from a few GB up to tens of GBs depending on available memory) with low latency. Memory storage is for applications that run within the cluster and collocated with HDFS Data Nodes. We have observed that the latency overhead from network replication negates the benefits of writing to memory.
Applications that use Lazy Persist Writes will continue to work by falling back to DISK storage if memory is insufficient or unconfigured.
This section enumerates the administrative steps required before applications can start using the feature in a cluster.
First decide the amount of memory to be dedicated for replicas stored in memory. Set dfs.datanode.max.locked.memory accordingly in hdfs-site.xml. This is the same setting used by the Centralized Cache Management feature. The Data Node will ensure that the combined memory used by Lazy Persist Writes and Centralized Cache Management does not exceed the amount configured in dfs.datanode.max.locked.memory.
E.g. To reserve 32 GB for in-memory replicas
<property> <name>dfs.datanode.max.locked.memory</name> <value>34359738368</value> </property>
This memory is not allocated by the Data Node on startup.
On Unix-like systems, the “locked-in-memory size” ulimit (ulimit -l) of the Data Node user also needs to be increased to match this parameter (see the related section on OS Limits). When setting this value, please remember that you will need space in memory for other things as well, such as the Data Node and application JVM heaps and the operating system page cache. You will also need memory for YARN containers if there is a YARN Node Manager process running on the same node as the Data Node.
Initialize a RAM disk on each Data Node. The choice of RAM Disk allows better data persistence across Data Node process restarts. The following setup will work on most Linux distributions. Using RAM disks on other platforms is not currently supported.
Linux supports using two kinds of RAM disks - tmpfs and ramfs. The size of tmpfs is limited by the Linux kernel while ramfs grows to fill all available system memory. There is a downside to tmpfs since its contents can be swapped to disk under memory pressure. However many performance-sensitive deployments run with swapping disabled so we do not expect this to be an issue in practice.
HDFS currently supports using tmpfs partitions. Support for adding ramfs is in progress (See HDFS-8584).
Mount the RAM Disk partition with the Unix mount command. E.g. to mount a 32 GB tmpfs partition under /mnt/dn-tmpfs/
sudo mount -t tmpfs -o size=32g tmpfs /mnt/dn-tmpfs/
It is recommended you create an entry in the /etc/fstab so the RAM Disk is recreated automatically on node restarts. Another option is to use a sub-directory under /dev/shm which is a tmpfs mount available by default on most Linux distributions. Ensure that the size of the mount is greater than or equal to your dfs.datanode.max.locked.memory setting else override it in /etc/fstab. Using more than one tmpfs partition per Data Node for Lazy Persist Writes is not recommended.
Tag the tmpfs directory with the RAM_DISK storage type via the dfs.datanode.data.dir configuration setting in hdfs-site.xml. E.g. On a Data Node with three hard disk volumes /grid/0, /grid/1 and /grid/2 and a tmpfs mount /mnt/dn-tmpfs, dfs.datanode.data.dir must be set as follows:
<property> <name>dfs.datanode.data.dir</name> <value>/grid/0,/grid/1,/grid/2,[RAM_DISK]/mnt/dn-tmpfs</value> </property>
This step is crucial. Without the RAM_DISK tag, HDFS will treat the tmpfs volume as non-volatile storage and data will not be saved to persistent storage. You will lose data on node restart.
Ensure that the global setting to turn on Storage Policies is enabled as documented here. This setting is on by default.
Applications indicate that HDFS can use Lazy Persist Writes for a file with the LAZY_PERSIST storage policy. Administrative privileges are not required to set the policy and it can be set in one of three ways.
Setting the policy on a directory causes it to take effect for all new files in the directory. The hdfs storagepolicies command can be used to set the policy as described in the Storage Policies documentation.
hdfs storagepolicies -setStoragePolicy -path <path> -policy LAZY_PERSIST
Starting with Apache Hadoop 2.8.0, an application can programmatically set the Storage Policy with FileSystem.setStoragePolicy. E.g.
fs.setStoragePolicy(path, "LAZY_PERSIST");
An application can pass CreateFlag#LAZY_PERSIST when creating a new file with FileSystem#create API. E.g.
FSDataOutputStream fos = fs.create( path, FsPermission.getFileDefault(), EnumSet.of(CreateFlag.CREATE, CreateFlag.LAZY_PERSIST), bufferLength, replicationFactor, blockSize, null);


{% load static %}
November 29 & 30 - 2017
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Easy Install Using A Public Cloud Provider
You can try ManageIQ in one of the public clouds that are supported. The benefits of this option are that you don’t need any hardware yourself, and that you can also use the same public cloud as the platform to be managed.
In the instructions below we will use the Google Cloud Platform. The ManageIQ project publishes ready-to-use images on Google Storage. We will assume that you have a Google account with an active payment method or a free trial. You also need to make sure that you have a default keypair installed.
The ManageIQ project is working on making it easy to try out ManageIQ on other clouds as well.
Step 1: Create a new image
From console.cloud.google.com, go to “Compute Engine”, “Images” and then click on “Create Image”:
Fill in the following data:
Name: manageiq-jansa-2
Family: centos-7
Source: cloud storage file
Cloud storage file: manageiq/jansa-2.tar.gz
Step 2: Create a new instance using the image you created
Once the image is created, you can create a new instance based on this image.
It’s recommended to select the 2 CPU / 7.5GB instance. Under “boot disk”, select the image that you created above. You also need to make sure that HTTP traffic is enabled.
Now hit “Create” to start the instance.
ManageIQ is now up and running.
Next step is to perform some basic configuration.


Time series: - return column named time or time_sec (in UTC), as a unix time stamp or any sql native date data type. You can use the macros below. - return column(s) with numeric datatype as values - (Optional: return column named metric to represent the series name. If no column named metric is found the column name of the value column is used as series name) Table: - return any set of columns Macros: - $__timeFilter(@column@) -> UNIX_TIMESTAMP(time_date_time) ≥<PHONE_NUMBER> AND UNIX_TIMESTAMP(time_date_time) ≤<PHONE_NUMBER> Example of group by and order by with $__timeGroup: SELECT $__time(timestamp_col) AS time, sum(value_double) as value FROM yourtable GROUP BY 1 ORDER BY 1


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object --+ | exceptions.BaseException --+ | exceptions.Exception --+ | exceptions.StandardError --+ | exceptions.RuntimeError --+ | NSExceptionError
Python Error wrapping an ObjC/NSException
.
Used to wrap uncaught ObjC/NSException
s, see setUncaughtExceptionHandler.
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Inherited from Inherited from Inherited from |
| Class Variables | |
NS = None hash(x) |
| Properties | |
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datetime Get the time stamp as "YYYY-MM-DD HH:MM:SS.MIL" ( str ).
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name Get the name of the exception ( str ).
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info Get additional info about the exception (Adict) or None .
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reason Get the reason for the exception ( str ) or
None .
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callstack Get the callstack of this exception ( iter ), most recent
last.
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timestamp Get the time stamp of this exception ( float ).
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versionstr Get the PyCocoa, Python, etc. |
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Inherited from Inherited from |
| Method Details |
New NSExceptionError wrapper.
|
| Property Details |
datetimeGet the time stamp as "YYYY-MM-DD HH:MM:SS.MIL"
(
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nameGet the name of the exception (
See Also: NSExceptionName. |
infoGet additional info about the exception (Adict) or
|
reasonGet the reason for the exception (
|
callstackGet the callstack of this exception (
|
timestampGet the time stamp of this exception (
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versionstrGet the PyCocoa, Python, etc. versions (
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