Last updated: 2020-06-16
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|---|---|---|---|---|
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| html | 66b45bb | Peter Carbonetto | 2020-06-16 | Added simulated data set to Corner signal plot in “gaussmeanest” |
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| Rmd | 049dcbb | Peter Carbonetto | 2018-11-08 | Moved around some files and revised TOC in home page. |
In this analysis, we assess the ability of different signal denoising methods to recover the true signal after being provided with Gaussian-distributed observations of the signal. We consider scenarios in which the data have homoskedastic errors (constant variance) and heteroskedastic errors (non-constant variance).
Since the simulation experiments are computationally intensive, here we only illustrate the application of the signal denoising methods, and create plots summarizing the results of the full experiments; the full experiments were implemented separately. (For instructions on re-running these simulation experiments, see the README in the “dsc” directory of the git repository).
Load the ggplot2 and cowplot packages, and the functions definining the mean and variances used to simulate the data.
library(plyr)
library(smashr)
library(ggplot2)
library(cowplot)
source("../code/signals.R")
source("../code/gaussmeanest.functions.R")
theme_set(theme_cowplot())
Load the results of the simulation experiments.
load("../output/dscr.RData")
This plot reproduces Fig. 2 of the manuscript, which compares the accuracy of the mean curves estimated from the data sets that were simulated using the “Spikes” mean function with constant variance and a signal-to-noise ratio of 3.
First, extract the results used to generate this plot, and transform them into a data frame suitable for plotting using ggplot2.
pdat <- get.results.homosked(res,"sp.3.v1")
Create the combined boxplot and violin plot using ggplot2.
pdat <-
transform(pdat,
method = factor(method,
names(sort(tapply(pdat$mise,pdat$method,mean),
decreasing = TRUE))))
p <- ggplot(pdat,aes(x = method,y = mise,fill = method.type)) +
geom_violin(fill = "skyblue",color = "skyblue") +
geom_boxplot(width = 0.15,outlier.shape = NA) +
scale_y_continuous(breaks = seq(6,16,2)) +
scale_fill_manual(values = c("darkorange","dodgerblue","gold"),
guide = FALSE) +
coord_flip() +
labs(x = "",y = "MISE") +
theme(axis.line = element_blank(),
axis.ticks.y = element_blank())
print(p)
From this plot, we see that the three variants of SMASH all outperformed EbayesThresh and TI thresholding in this setting.
These plots summarize the results for all 7 simulation scenarios and the two signal-to-noise ratios (1 and 3), including the “Spikes” scenario shown in greater detail in the violin plot above.
create.bar.plots.homosked(rbind(
data.frame(sim = "sp", snr = 1,get.results.homosked(res,"sp.1.v1")),
data.frame(sim = "bump",snr = 1,get.results.homosked(res,"bump.1.v1")),
data.frame(sim = "blkp",snr = 1,get.results.homosked(res,"blk.1.v1")),
data.frame(sim = "ang", snr = 1,get.results.homosked(res,"ang.1.v1")),
data.frame(sim = "dop", snr = 1,get.results.homosked(res,"dop.1.v1")),
data.frame(sim = "blip",snr = 1,get.results.homosked(res,"blip.1.v1")),
data.frame(sim = "cor", snr = 1,get.results.homosked(res,"cor.1.v1")),
data.frame(sim = "sp", snr = 3,get.results.homosked(res,"sp.3.v1")),
data.frame(sim = "bump",snr = 3,get.results.homosked(res,"bump.3.v1")),
data.frame(sim = "blkp",snr = 3,get.results.homosked(res,"blk.3.v1")),
data.frame(sim = "ang", snr = 3,get.results.homosked(res,"ang.3.v1")),
data.frame(sim = "dop", snr = 3,get.results.homosked(res,"dop.3.v1")),
data.frame(sim = "blip",snr = 3,get.results.homosked(res,"blip.3.v1")),
data.frame(sim = "cor", snr = 3,get.results.homosked(res,"cor.3.v1"))))
Next, we compare the same methods in simulated data sets with heteroskedastic errors.
In this scenario, the data sets were simulated using the “Spikes” mean function and the “Clipped Blocks” variance function. The next two plots reproduce part of Fig. 3 in the manuscript.
This plot shows the mean function as an orange line, the +/- 2 standard deviations as dashed, light blue lines, and an example simulated data set (black circles):
t <- (1:1024)/1024
mu <- spike.fn(t,"mean")
sigma.ini <- sqrt(cblocks.fn(t,"var"))
sd.fn <- sigma.ini/mean(sigma.ini) * sd(mu)/3
x.sim <- rnorm(1024,mu,sd.fn)
par(cex.axis = 1,cex.lab = 1.25)
plot(mu,type = "l", ylim = c(-0.05,1),col = "darkorange",
xlab = "position",ylab = "",lwd = 1.75,xaxp = c(0,1024,4),
yaxp = c(0,1,4))
lines(mu + 2*sd.fn,col = "dodgerblue",lty = "dashed",lwd = 1.75)
lines(mu - 2*sd.fn,col = "dodgerblue",lty = "dashed",lwd = 1.75)
points(x.sim,cex = 0.7,pch = 1,col = "black")
| Version | Author | Date |
|---|---|---|
| bc790ae | Peter Carbonetto | 2020-06-16 |
Next, we plot the ground-truth signal (the mean function, drawn as a black line), and the signals recovered by TI thresholding (light blue line) and SMASH (the red line) for the example simulated data set.
mu.smash <- smash(x.sim,family = "DaubLeAsymm",filter.number = 8)
mu.ti <- ti.thresh(x.sim,method = "rmad",family = "DaubLeAsymm",
filter.number = 8)
par(cex.axis = 1)
plot(mu,type = "l",col = "black",lwd = 3,xlab = "position",ylab = "",
ylim = c(-0.05,1),xaxp = c(0,1024,4),yaxp = c(0,1,4))
lines(mu.ti,col = "dodgerblue",lwd = 3)
lines(mu.smash,col = "orangered",lwd = 3)
Extract the results from running the simulations.
hetero.data.smash <-
res[res$.id == "sp.3.v5" & res$method == "smash.s8",]
hetero.data.smash.homo <-
res[res$.id == "sp.3.v5" & res$method == "smash.homo.s8",]
hetero.data.tithresh.homo <-
res[res$.id == "sp.3.v5" & res$method == "tithresh.homo.s8",]
hetero.data.tithresh.rmad <-
res[res$.id == "sp.3.v5" & res$method == "tithresh.rmad.s8",]
hetero.data.tithresh.smash <-
res[res$.id == "sp.3.v5" & res$method == "tithresh.smash.s8",]
hetero.data.tithresh.true <-
res[res$.id == "sp.3.v5" & res$method == "tithresh.true.s8",]
hetero.data.ebayes <-
res[res$.id == "sp.3.v5" & res$method == "ebayesthresh",]
hetero.data.smash.true <-
res[res$.id == "sp.3.v5" & res$method == "smash.true.s8",]
Transform these results into a data frame suitable for ggplot2.
pdat <-
rbind(data.frame(method = "smash",
method.type = "est",
mise = hetero.data.smash$mise),
data.frame(method = "smash.homo",
method.type = "homo",
mise = hetero.data.smash.homo$mise),
data.frame(method = "tithresh.rmad",
method.type = "tithresh",
mise = hetero.data.tithresh.rmad$mise),
data.frame(method = "tithresh.smash",
method.type = "tithresh",
mise = hetero.data.tithresh.smash$mise),
data.frame(method = "tithresh.true",
method.type = "tithresh",
mise = hetero.data.tithresh.true$mise),
data.frame(method = "ebayesthresh",
method.type = "homo",
mise = hetero.data.ebayes$mise),
data.frame(method = "smash.true",
method.type = "true",
mise = hetero.data.smash.true$mise))
pdat <-
transform(pdat,
method = factor(method,
names(sort(tapply(pdat$mise,pdat$method,mean),
decreasing = TRUE))))
Create the combined boxplot and violin plot using ggplot2.
p <- ggplot(pdat,aes(x = method,y = mise,fill = method.type)) +
geom_violin(fill = "skyblue",color = "skyblue") +
geom_boxplot(width = 0.15,outlier.shape = NA) +
scale_fill_manual(values=c("darkorange","dodgerblue","limegreen","gold"),
guide = FALSE) +
coord_flip() +
scale_y_continuous(breaks = seq(10,70,10)) +
labs(x = "",y = "MISE") +
theme(axis.line = element_blank(),
axis.ticks.y = element_blank())
print(p)
In this scenario, we see that SMASH, when allowing for heteroskedastic errors, outperforms EbayesThresh and all variants of TI thresholding (including TI thresholding when provided with the true variance). Further, SMASH performs almost as well when estimating the variance compared to when provided with the true variance.
In this next scenario, the data sets were simulated using the “Corner” mean function and the “Doppler” variance function. These plots were also used in Figure 3 of the manuscript.
This plot shows the mean function as an orange line, the +/- 2 standard deviations as dashed, light blue lines, and an example simulated data set (black circles):
t <- (1:1024)/1024
mu <- cor.fn(t,"mean")
sigma.ini <- sqrt(doppler.fn(t,"var"))
sd.fn <- sigma.ini/mean(sigma.ini) * sd(mu)/3
x.sim <- rnorm(1024,mu,sd.fn)
plot(mu,type = "l",col = "darkorange",ylim = c(-0.05,1),
xlab = "position",ylab = "",lwd = 1.75,xaxp = c(0,1024,4),
yaxp = c(0,1,4))
lines(mu + 2*sd.fn,col = "dodgerblue",lty = "dashed",lwd = 1.75)
lines(mu - 2*sd.fn,col = "dodgerblue",lty = "dashed",lwd = 1.75)
points(x.sim,cex = 0.7,pch = 1,col = "black")
Now, we plot the ground-truth signal (the mean function, drawn as a black line) and the signals recovered by TI thresholding (light blue line) and SMASH (the red line) for one simulated dataset as an illustration
mu.smash <- smash(x.sim,family = "DaubLeAsymm",filter.number = 8)
mu.ti <- ti.thresh(x.sim,method = "rmad",family = "DaubLeAsymm",
filter.number = 8)
par(cex.axis = 1)
plot(mu,type = "l",col = "black",lwd = 3,xlab = "position",ylab = "",
ylim = c(-0.05,1),xaxp = c(0,1024,4),yaxp = c(0,1,4))
lines(mu.ti,col = "dodgerblue",lwd = 3)
lines(mu.smash,col = "orangered",lwd = 3)
Extract the results from running these simulations.
hetero.data.smash.2 <-
res[res$.id == "cor.3.v3" & res$method == "smash.s8",]
hetero.data.smash.homo.2 <-
res[res$.id == "cor.3.v3" & res$method == "smash.homo.s8",]
hetero.data.tithresh.homo.2 <-
res[res$.id == "cor.3.v3" & res$method == "tithresh.homo.s8",]
hetero.data.tithresh.rmad.2 <-
res[res$.id == "cor.3.v3" & res$method == "tithresh.rmad.s8",]
hetero.data.tithresh.smash.2 <-
res[res$.id == "cor.3.v3" & res$method == "tithresh.smash.s8",]
hetero.data.tithresh.true.2 <-
res[res$.id == "cor.3.v3" & res$method == "tithresh.true.s8",]
hetero.data.ebayes.2 <-
res[res$.id == "cor.3.v3" & res$method == "ebayesthresh",]
hetero.data.smash.true.2 <-
res[res$.id == "cor.3.v3" & res$method == "smash.true.s8",]
Transform these results into a data frame suitable for ggplot2.
pdat <-
rbind(data.frame(method = "smash",
method.type = "est",
mise = hetero.data.smash.2$mise),
data.frame(method = "smash.homo",
method.type = "homo",
mise = hetero.data.smash.homo.2$mise),
data.frame(method = "tithresh.rmad",
method.type = "tithresh",
mise = hetero.data.tithresh.rmad.2$mise),
data.frame(method = "tithresh.smash",
method.type = "tithresh",
mise = hetero.data.tithresh.smash.2$mise),
data.frame(method = "tithresh.true",
method.type = "tithresh",
mise = hetero.data.tithresh.true.2$mise),
data.frame(method = "ebayesthresh",
method.type = "homo",
mise = hetero.data.ebayes.2$mise),
data.frame(method = "smash.true",
method.type = "true",
mise = hetero.data.smash.true.2$mise))
pdat <-
transform(pdat,
method = factor(method,
names(sort(tapply(pdat$mise,pdat$method,mean),
decreasing = TRUE))))
Create the combined boxplot and violin plot using ggplot2.
p <- ggplot(pdat,aes(x = method,y = mise,fill = method.type)) +
geom_violin(fill = "skyblue",color = "skyblue") +
geom_boxplot(width = 0.15,outlier.shape = NA) +
scale_fill_manual(values=c("darkorange","dodgerblue","limegreen","gold"),
guide = FALSE) +
coord_flip() +
scale_y_continuous(breaks = seq(1,5)) +
labs(x = "",y = "MISE") +
theme(axis.line = element_blank(),
axis.ticks.y = element_blank())
print(p)
Similar to the “Spikes” scenario, we see that the SMASH method, when allowing for heteroskedastic variances, outperforms both the TI thresholding and EbayesThresh approaches.
These plots summarize the results from all combinations of test functions and a signal-to-noise ratio of 1.
create.bar.plots.heterosked(rbind(
data.frame(mean="sp", var="v2",get.results.heterosked(res,"sp.1.v2")),
data.frame(mean="sp", var="v3",get.results.heterosked(res,"sp.1.v3")),
data.frame(mean="sp", var="v4",get.results.heterosked(res,"sp.1.v4")),
data.frame(mean="sp", var="v5",get.results.heterosked(res,"sp.1.v5")),
data.frame(mean="bump",var="v2",get.results.heterosked(res,"bump.1.v2")),
data.frame(mean="bump",var="v3",get.results.heterosked(res,"bump.1.v3")),
data.frame(mean="bump",var="v4",get.results.heterosked(res,"bump.1.v4")),
data.frame(mean="bump",var="v5",get.results.heterosked(res,"bump.1.v5")),
data.frame(mean="blk", var="v2",get.results.heterosked(res,"blk.1.v2")),
data.frame(mean="blk", var="v3",get.results.heterosked(res,"blk.1.v3")),
data.frame(mean="blk", var="v4",get.results.heterosked(res,"blk.1.v4")),
data.frame(mean="blk", var="v5",get.results.heterosked(res,"blk.1.v5")),
data.frame(mean="ang", var="v2",get.results.heterosked(res,"ang.1.v2")),
data.frame(mean="ang", var="v3",get.results.heterosked(res,"ang.1.v3")),
data.frame(mean="ang", var="v4",get.results.heterosked(res,"ang.1.v4")),
data.frame(mean="ang", var="v5",get.results.heterosked(res,"ang.1.v5")),
data.frame(mean="dop", var="v2",get.results.heterosked(res,"dop.1.v2")),
data.frame(mean="dop", var="v3",get.results.heterosked(res,"dop.1.v3")),
data.frame(mean="dop", var="v4",get.results.heterosked(res,"dop.1.v4")),
data.frame(mean="dop", var="v5",get.results.heterosked(res,"dop.1.v5")),
data.frame(mean="blip",var="v2",get.results.heterosked(res,"blip.1.v2")),
data.frame(mean="blip",var="v3",get.results.heterosked(res,"blip.1.v3")),
data.frame(mean="blip",var="v4",get.results.heterosked(res,"blip.1.v4")),
data.frame(mean="blip",var="v5",get.results.heterosked(res,"blip.1.v5")),
data.frame(mean="cor", var="v2",get.results.heterosked(res,"cor.1.v2")),
data.frame(mean="cor", var="v3",get.results.heterosked(res,"cor.1.v3")),
data.frame(mean="cor", var="v4",get.results.heterosked(res,"cor.1.v4")),
data.frame(mean="cor", var="v5",get.results.heterosked(res,"cor.1.v5"))))
These plots summarize the results from data sets simulated using a signal-to-noise ratio of 3.
create.bar.plots.heterosked(rbind(
data.frame(mean="sp", var="v2",get.results.heterosked(res,"sp.3.v2")),
data.frame(mean="sp", var="v3",get.results.heterosked(res,"sp.3.v3")),
data.frame(mean="sp", var="v4",get.results.heterosked(res,"sp.3.v4")),
data.frame(mean="sp", var="v5",get.results.heterosked(res,"sp.3.v5")),
data.frame(mean="bump",var="v2",get.results.heterosked(res,"bump.3.v2")),
data.frame(mean="bump",var="v3",get.results.heterosked(res,"bump.3.v3")),
data.frame(mean="bump",var="v4",get.results.heterosked(res,"bump.3.v4")),
data.frame(mean="bump",var="v5",get.results.heterosked(res,"bump.3.v5")),
data.frame(mean="blk", var="v2",get.results.heterosked(res,"blk.3.v2")),
data.frame(mean="blk", var="v3",get.results.heterosked(res,"blk.3.v3")),
data.frame(mean="blk", var="v4",get.results.heterosked(res,"blk.3.v4")),
data.frame(mean="blk", var="v5",get.results.heterosked(res,"blk.3.v5")),
data.frame(mean="ang", var="v2",get.results.heterosked(res,"ang.3.v2")),
data.frame(mean="ang", var="v3",get.results.heterosked(res,"ang.3.v3")),
data.frame(mean="ang", var="v4",get.results.heterosked(res,"ang.3.v4")),
data.frame(mean="ang", var="v5",get.results.heterosked(res,"ang.3.v5")),
data.frame(mean="dop", var="v2",get.results.heterosked(res,"dop.3.v2")),
data.frame(mean="dop", var="v3",get.results.heterosked(res,"dop.3.v3")),
data.frame(mean="dop", var="v4",get.results.heterosked(res,"dop.3.v4")),
data.frame(mean="dop", var="v5",get.results.heterosked(res,"dop.3.v5")),
data.frame(mean="blip",var="v2",get.results.heterosked(res,"blip.3.v2")),
data.frame(mean="blip",var="v3",get.results.heterosked(res,"blip.3.v3")),
data.frame(mean="blip",var="v4",get.results.heterosked(res,"blip.3.v4")),
data.frame(mean="blip",var="v5",get.results.heterosked(res,"blip.3.v5")),
data.frame(mean="cor", var="v2",get.results.heterosked(res,"cor.3.v2")),
data.frame(mean="cor", var="v3",get.results.heterosked(res,"cor.3.v3")),
data.frame(mean="cor", var="v4",get.results.heterosked(res,"cor.3.v4")),
data.frame(mean="cor", var="v5",get.results.heterosked(res,"cor.3.v5"))))
sessionInfo()
# R version 3.6.2 (2019-12-12)
# Platform: x86_64-apple-darwin15.6.0 (64-bit)
# Running under: macOS Catalina 10.15.5
#
# Matrix products: default
# BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
# LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
#
# Random number generation:
# RNG: Mersenne-Twister
# Normal: Inversion
# Sample: Rounding
#
# locale:
# [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
#
# other attached packages:
# [1] cowplot_1.0.0 ggplot2_3.3.0 smashr_1.2-5 plyr_1.8.5
#
# loaded via a namespace (and not attached):
# [1] Rcpp_1.0.3 pillar_1.4.3 compiler_3.6.2 later_1.0.0
# [5] git2r_0.26.1 workflowr_1.6.2 bitops_1.0-6 tools_3.6.2
# [9] digest_0.6.23 tibble_2.1.3 lifecycle_0.1.0 evaluate_0.14
# [13] gtable_0.3.0 lattice_0.20-38 pkgconfig_2.0.3 rlang_0.4.5
# [17] Matrix_1.2-18 yaml_2.2.0 xfun_0.11 invgamma_1.1
# [21] withr_2.1.2 dplyr_0.8.3 stringr_1.4.0 knitr_1.26
# [25] fs_1.3.1 caTools_<IP_ADDRESS> tidyselect_0.2.5 rprojroot_1.3-2
# [29] grid_3.6.2 glue_1.3.1 data.table_1.12.8 R6_2.4.1
# [33] rmarkdown_2.0 mixsqp_0.3-43 irlba_2.3.3 farver_2.0.1
# [37] purrr_0.3.3 ashr_2.2-50 magrittr_1.5 whisker_0.4
# [41] scales_1.1.0 backports_1.1.5 promises_1.1.0 htmltools_0.4.0
# [45] MASS_7.3-51.4 assertthat_0.2.1 colorspace_1.4-1 httpuv_1.5.2
# [49] labeling_0.3 wavethresh_4.6.8 stringi_1.4.3 munsell_0.5.0
# [53] truncnorm_1.0-8 SQUAREM_2017.10-1 crayon_1.3.4


--- layout: layout_responsive category: 404 title: Not Found meta: Page not found permalink: 404.html ---


I Love to develop and create fun projects I have lots of amazing ideas and I love to help and colaboate with other developers I am also lots of fun to work with. I will listen to how you want your project done and ill do it to the best of my ability.
If you have a project that you would like an opinion on id love to share my thoughts and help you with any challenges you may have, I Have lots of experience useing HTML, CSS and Javascript and Npm and I am currently learning React a Javascript Framework.
View ResumeThis is one of my many CSS Grid Layouts that I did while I was learning to code.
This is a Background Generator that I made with javascript while I was learning the Javascript programming language.
This is a cool little Robo Friends React Project that I made when I was learning the React.js Framework.
Feel Free to send me an email ill respond as soon as possible.
Send me an Email


hesseflux¶
hesseflux
provides functions used in the processing and post-processing of
the Eddy covariance flux data of the ICOS ecosystem site FR-Hes.
About hesseflux¶
hesseflux
collects functions used for processing Eddy covariance data of the
ICOS ecosystem site FR-Hes.
The post-processing functionality for Eddy flux data is similar to the R-package REddyProc and includes basically the steps described in Papale et al. (Biogeosciences, 2006) plus some extensions such as the daytime method of flux partitioning (Lasslop et al., Global Change Biology 2010).
Documentation¶
The complete documentation for hesseflux
is available at:
Quick usage guide¶
Post-processing Eddy covariance data that is in europe-fluxdata.eu format¶
An example script that makes all the steps described in Papale et al. (Biogeosciences, 2006) is given in the example directory. It is simply called:
python postproc_europe-fluxdata.py hesseflux_example.cfg
The script is governed by a configuration file in Python’s standard configparser format. The example configuration file hesseflux_example.cfg is highly commented. See the User Guide for a step by step guide through the script and the configuration file.
Installation¶
The easiest way to install is via pip:
pip install hesseflux
License¶
hesseflux
is distributed under the MIT License. See the LICENSE file for
details.
Copyright (c) 2009-2022 Matthias Cuntz
The project structure hesseflux
has borrowed heavily from welltestpy
by Sebastian Müller.


| Level | Component | Effect | Type |
|---|---|---|---|
| 7 | Wardstone | 7% Elemental, 15% Bleed Resistance | Amulet & Medal |
| 15 | Silk Swatch | 18% Pierce & Bleed Resistance | Shoulder, Chest & Leg Armor |
| 15 | Imbued Silver | 20% Chaos Resistance & 15% Bleeding Resistance | Mainhand/Offhand (Toggled Item Skill) |
| 15 | Purified Salt | 20% Aether Resistance | Mainhand/Offhand (Toggled Item Skill) |
| 15 | Antivenom Salve | 20% Poison & Acid | All Armor |
| 15 | Unholy Inscription | 10% Vitality, 15% Bleeding | Hand Armor |
| 20 | Runestone | 12% Aether & 12% Elemental Resist | Head Armor |
| 20 | Soul Shard | 20% Vitality Resistance | Ring, Amulet, Medal |
| 20 | Mark of the Traveler | 8% Movement Speed & 10% Slow Resistance | Boots |
| 24 | Sanctified Bone | 18% Vitality, 12% Chaos | Chest & Head |
| 24 | Aether Soul | 16% Aether Resistance | Amulet & Medal |
The factions a player gets Honored and Revered with first are generally: Devil's Crossing, Rovers, Homestead, Black Legion, Order/Kymon, and Coven of Ugdenbog. I'm listing some of the most popular defensive Augments below for reference, which can greatly help in surviving both Elite and especially Ultimate.
| Level | Item | Effect | Type | Faction |
|---|---|---|---|---|
| 40 | Arkovian Rose Powder | 10% Elemental Res | Rings/Amulet | Rovers Honored |
| 40 | Slith Venom | 15% Poison, Acid & Bleeding Res | Rings/Amulet | Devil's Honored |
| 40 | Gazer Eye | 10% Aether Res | Rings/Amulet | Devil's Honored |
| 40 | Corpsefiend Tentacle | 10% Vitality Res | Rings/Amulet | Devil's Honored |
| 40 | Divine Flame | 10% Elemental Res | Rings/Amulet | Kymon's Honored |
| 40 | Blessed Ashes | 15% Fire & Lightning Res | Rings/Amulet | Kymon's Honored |
| 40 | Consecrated Silver | 12% Chaos Res | Rings/Amulet | Kymon's Honored |
| 40 | Necrotic Flesh | 15% Bleeding Res | Rings/Amulet | Order Honored |
| 40 | Chillheart Powder | 15% Cold & Vitality Res | Rings/Amulet | Order Honored |
| 70 | Venomguard Powder | 15% Poison & Acid Res | All Armor | Rovers Revered |
| 70 | Nightshade Powder | 7% Pierce & 10% Cold Res | All Armor | Rovers Revered |
| 70 | Bladeward Powder | 10% Pierce Res | All Armor | Devil's Revered |
| 70 | Mogdrogen's Touch | 10% Poison & Acid Res, 7% Vitality Res | All Armor | Devil's Revered |
| 70 | Kymon's Blessing | 15% Fire Res | All Armor | Kymon's Revered |
| 70 | Kymon's Conduit | 15% Lightning Res | All Armor | Kymon's Revered |
| 70 | Demonbane Powder | 7% Vitality & Chaos Res | All Armor | Kymon's Revered |
| 70 | Mankind's Vigil | 7% Aether Res, 7% Chaos Res | All Armor | Black Legion Revered |
| 70 | Kingsguard Powder | 7% Pierce Res, 10% Poison/Acid Res | All Armor | Black Legion Revered |
| 70 | Flameweave Powder | 7% Pierce Res, 10% Fire Res | All Armor | Homestead Revered |
| 70 | Solarstorm Powder | 10% Fire Res, 10% Lightning Res | All Armor | Homestead Revered |
| 70 | Wraithtouch Powder | 15% Cold Res | All Armor | Order Revered |
| 70 | Spiritguard Powder | 10% Vitality Res | All Armor | Order Revered |
| 70 | Spellward Powder | 10% Lightning Res, 7% Aether Res | All Armor | Order Revered |
| 90 | Coven Warding Powder | 7% Elemental Res | All Armor | Coven Revered |
| 90 | Coven Black Ash | 8% Pierce and Chaos Res | All Armor | Coven Revered |


---
layout: definitions
---
A system of equations
$$\begin{align*}
a_{11}x_{1}+\dots + a_{1n}x_n&=y_1 \\
a_{21}x_1+\dots + a_{2n}x_n&=y_2 \\
\vdots \\
a_{m1}x_{1}+\dots + a_{mn}x_{n}&=y_{m}
\end{align*}$$ is homogeneous if $y_1=y_2=\dots = y_m=0$.
Concepts
Coming soon
Used In
Coming soon
Hypothesis
Coming soon
Results
Coming soon


Ford Bronco Trademark Application Filed In Europe
Ford hasn’t officially said if Europe would get the new SUV.
by Anthony AlanizWhen Ford released its second-quarter earnings earlier this year, a slideshow previewed the company’s roadmap through 2020. Missing from that was any indication Europe would receive the Ford Bronco. However, Ford Authority has turned up an exciting trademark application with the European Union Intellectual Property Office – the Bronco. The filing says it’s for “Land motor vehicles, namely, passenger automobiles, pick-up trucks, sport utility vehicles.” What changed?
The Latest Ford Bronco News:
The application is surprising, considering the Dearborn-based automaker has made no indication the Bronco will need a passport. However, Ford only showed its roadmap through next year, which means European plans for a Bronco could be beyond that. There was other information missing from the slideshow, too, such as the rumored Bronco hybrid. Both could happen in 2021 or later.
The Bronco is one of Ford’s most anticipated reveals in years as excitement around the iconic nameplate builds ahead of its reveal next spring. Ford has billed the Bronco as a tried-and-true off-road machine with both two- and four-door configurations. Ford has also filed several Bronco-related patents and trademarks over the years, too, which has only fueled speculation and excitement.
Gallery: Ford Bronco Mule Spy Photos
Ford previewed the Bronco with the Bronco R racing truck earlier this month, which Ford will take racing portions of this year’s Baja 1000 after Ford puts the truck through its paces with a 1,000-mile torture test. The R rides on a modified version of the Bronco’s chassis with an overhauled suspension, and 37-inch BF Goodrich tires.
The Ford Bronco will debut sometime next spring, likely ahead of the Detroit Auto Show in June, where it could make its first public appearance. While we’ve seen countless spy photos of the SUV in various stages of development, there’s still a lot we don’t know about it. When Ford unveils it next year, we’ll have a rundown of all the details.
Source: Ford Authority


import com.sleepycat.db.*;public void commit() throws DbException;
The DbTxn.commit method ends the transaction specified by the tid argument.
If Db.DB_TXN_NOSYNC was not specified, a commit log record is written and flushed to disk, as are all previously written log records.
In the case of nested transactions, if the transaction is a parent transaction with unresolved (neither committed or aborted) child transactions, the child transactions are aborted and the commit of the parent will succeed.
In the case of nested transactions, if the transaction is a child transaction, its locks are not released, but are acquired by its parent. While the commit of the child transaction will succeed, the actual resolution of the child transaction is postponed until the parent transaction is committed or aborted, i.e., if its parent transaction commits, it will be committed, and if its parent transaction aborts, it will be aborted.
Any applications that require strict two-phase locking must not release any locks explicitly, leaving them all to be released by DbTxn.commit.
The DbTxn.commit method throws an exception that encapsulates an errno on failure.
The DbTxn.commit method may fail and throw an exception for any of the errors specified for the following Berkeley DB and C library functions: abort(3), fcntl(3), fflush(3), fprintf(3), free(3), getpid(3), DbLockTab.vec, DbLog.put, malloc(3), memcpy(3), memset(3), strerror(3), vfprintf(3), and vsnprintf(3).
In addition, the DbTxn.commit method may fail and throw an exception encapsulating errno for the following conditions:


{% extends "base_community.html" %} {% block header %}
Code of Conduct
All content on this page is licensed under a Creative Commons Attribution license.


Start scrolling and follow a guided tour
As an introduction to this awesome data visualization tool, we are going to explore a restricted dataset of news mentions. We chose to focus on the recent Gilet Jaune protests in France, in particular the related articles that span between Monday 10th and Tuesday 11th of December 2018, at the time when the French President Emmanuel Macron announced policy changes towards the end of Monday after hours of non-stopping leaks and rumors about what changes would be announced.
Let’s first explore this data through a graph of the 13 most prolific news outlets. By ‘prolific’ we mean the news outlets that have shared the biggest number of different events in the scope of our topic. This enables to focus on the biggest players and prevent a too noisy analysis since GDELT is not perfect and is subject to inconsistencies.
Each news outlets on the graph is connected (at least) to the 4 nodes with whom it shared the highest number of distinct events. This enables to visualize a robust summary of how news outlets can be associated. What we can see is that there are two clear clusters of news outlets: one composed only of French news outlets and one composed mostly of foreign news outlets; the French newspaper ‘La dépèche’ acts here as a bridge between the two clusters. The color of the edges characterizes the average tone distance of each article of the two news sources (nodes) that talk about common event. We see here that the tone inside the French cluster is highly similar while in the second cluster they seem to disagree on basically everything. Therefore, non-French news sources seem to be more partisan regarding what was going. You can also click on the nodes to get access to other metrics.
To dive in the second level of the graph, you should click on an edge. In this level, the central nodes represent all the events both of the news outlets have spoken about. The color applied on the edges tells if the tone of the articles mentioning that event is rather negative or positive. That information from each of the two news outlets is summarized on the ‘event’ node color: if they agreed on the tone then the node takes the matching color. If they disagreed, then the node takes a grey color. By clicking on an ‘event’ you will get more information about, including 1 corresponding news article from each source. Be aware that this view clearly outlines some inconsistencies on how GDELT may map articles to events.
Interested in how all this evolves over time? Check out the streamgraph view below! There you can see, for each source, with how many other sources it has shared a common event during a specific time interval. For example, look at ziarelive.ro (green color). At around 10am the first day, the green area becomes quite larger. What does this mean? It means that around that midday, a large number of sources shared some event that ziarelive.ro also shared - it also means that, at that point of the day, its position in the graph was particularly strong. How many sources? Move your mouse over that area and you will see a tooltip with the number.
What info can we get from that visualization? We can see, for instance, that the outlets are quite dormant during the night (12am to 6am), compared to during the day.
NB: be aware that the data is displayed according to your time zone.
This happens both days. However, each source peaks at different periods each day. See, for example, how ziarelive.ro is stronger around midday, while globo.com is stronger during the evening. This might hint at the time zone difference, since globo.com is in Brazil! Notice how these peaks are not the same for all sources we can see here. For example, when globo.com is peaking during the evening, it shares events with a lot of sources that do not appear here.
If you click on an outlet, you can see how many of these sources agreed with that source, and how many disagreed. Check out, for example, how many outlets seemed to agree with Huffington Post around 6pm. And, sometimes, outlets agree on an event and disagree on another - this is when the one view mirrors the other, like with elpais.com!


WORTH WINNING A film review by Kevin Romano Copyright 1989 Kevin Romano
* MINOR SPOILERS *
Judging from WORTH WINNING, America is in deep trouble! I knew that the film probably wouldn't be too good because it has Lesley Ann Warren in it, but I went to see it anyway. It is so deeply shallow that there's not a whole lot to be said about it.
Most of us have seen the television show MOONLIGHTING no doubt. Well if you've seen MOONLIGHTING, you've seen WORTH WINNING. WORTH WINNING, however, is much more predictable. Mark Harmon takes the place of Bruce Willis. He talks to the camera, explains his feelings, what's happening in the story, etc.
Admittedly, I missed the very beginning because the Boston Globe with its usual crummy quality control had the wrong start time printed. But it didn't matter. This TV program that thinks it's a movie is such a formula flick that you don't need to catch the opening to understand it.
Here's the plot. Two friends make a bet that one of them can/can't get three women to agree to marry one of them. He does, but falls for one. The women find out and turn the tables on him. He repents and wins back the lady. Pure hack!
This movie defines new lows in the consumer mentality that has overtaken America. It assumes that we are all part of a great era of dreck in which reality is defined not by any drive to make ourselves better as individuals, as a people, as a nation, but by our unblinking acceptance of the drivel of consumerism. We are no longer looked upon as thinking people, or even as film audiences. We are - media consumers! Boy, does this flick ever make you feel like an consumer!
Lesley Ann Warren is one reason I went. She is a wonderful, talented lady. It's a pity she seems to always appear in stuff that is way below her capabilities. I don't know if she herself has the bad taste, her agent, the casting directors, the producers? I just don't know. How awful to watch someone loaded with talent consistently exploited in demeaning roles. Of course, she has considerable physical charms, but, while undoubtedly a reliable aspect for manipulation of the audience, hormone production is best left where it belongs - with pharmaceutical companies; Lesley Ann is wasted in this outing. There are so few good screen parts written for women that taking someone as talented as Lesley and using her in a part like this should be made part of the felony statutes. Nevertheless, she does a good job in the second-rate role of a vapid, repressed housewife.
I can only hope that the producers and financiers of this piece of skit will get to read reviews like this and somehow get it through their witless skulls that vulgarities, jiggling tits, and a hack TV formula do not a movie make. They should stick to things they're best at, like manipulating the stock market, or certain of their anatomical appendages. This is not light comedy; it's a comedy for air heads, which is what the producers apparently think of their audience. Do yourself a favor. Miss this one even on cable.
--Kevin Romano
.
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
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


SBI steeply slashes deposit rates; lowers lending rates marginally
by PTIHighlights
- This is the seventh consecutive cut in lending rates by the bank this fiscal
- With this reduction, the one year MCLR, to which most of its loan prices are linked, will come down to 8 per cent, SBI said
MUMBAI: The country's largest lender State Bank of India (SBI) on Friday reduced its marginal cost of fund based lending rate (MCLR) by 5 basis points across all tenors, effective November 10, and sharply slashed the deposits pricing between 15 and 75 basis points.
This is the seventh consecutive cut in lending rates by the bank this fiscal.
With this reduction, the one year MCLR, to which most of its loan prices are linked, will come down to 8 per cent, the bank said in a statement.
The bank also revised its interest rates on term deposits on account of adequate liquidity in the system. The new deposit rates will also be effective from November 10.
It has reduced interest rate on retail term deposit by 15 basis points for one year to less than two years' tenor.
Bulk term deposit interest rates have been reduced by 30 to 75 bps across tenors, the bank said.


Records by Month
This section lists the best performances achieved during each of the twelve calendar
months. The standards are the same as for the national records section.
Road
5 kilometers
4 miles
8 kilometers
10 kilometers
12 kilometers
15 kilometers
10 miles
20 kilometers
Half Marathon
25 kilometers
30 kilometers
Marathon
Outdoor Track
3000 meters
2 miles
5000 meters
10,000 meters
Indoor Track
3000 meters
2 miles
5000 meters


Resume
Feel free to download my resume in pdf format. It was created using LaTeX which is a formatting language that can take anything and make it look fantastic.
ResumeEducation
-
Jackson Hole High School, Jackson Hole, WY
Graduation - June 2012 -
Texas A&M University, College Station, TX
Bachelors of Electrical Engineering
Minors: Mandarin, Math
Graduation - May 2017


WITNESS LIST Teacher Health Insurance, Select Committee February 5, 2001-2:00P Revenue Est./ State Budget On: Keel, John (Legislative Budget Board) LeBas, James (Comptroller's Office) Reissig, Mike (Comptroller's Office) Total Return Investment On: Ferris, Roger (State Auditor's Office) McCabe, Martha (State Auditor's Office) Smith, Carol (State Auditor's Office)


A Timezone resolver
is now part of the spincast-default
artifact. This resolver allows you to define
a default TimeZone to use, but also provides a Pebble filter:
"timeZoneCookie()
". This filter
gets the user TimeZone using javascript and stores it in a cookie so Spincast has access to it.
Another new plugin, Spincast Date Formatter,
allows you to format dates in various ways, both in Java code and in templates (using a provided
dateFormat()
Pebble function).


Hi, my name is Matthew Madden, and I am thrilled to have you here at my portfolio site. This site has two goals:
I enjoy writing front-end code with these technologies:
If I can be a resource for your next project, or if you just want to reach out, here are the best ways to get in touch:
Email<EMAIL_ADDRESS>LinkedIn: Me
My code: on GitHub
Twitter: @mattmaddenmusic


I have always been the kind of kid which always have hated alcohol, cigarettes, drugs and all that kind of 'shit', but lately, my opinion about these have radically changed. To this date, I've drunk alot of booze, I've tried some psychoactives (lsa containing seeds, hawaiian baby woodrose seeds to be correct) and had cigarettes on occasion.
I was curious about this 'snus' (I don't know what they are called in english, but that is what it's called in Swedish. Sweden is where I live), best way to explain it, it's tobacco salt and water in a mixture to be put beneath your upper lip. Maybe I'm all overdescribing, but I don't recall ever hearing anyone who's from england or so use the word 'snus'.
Anyway, to get to the point.  So I decided I'd try something new, I was careless of what I'd do, and I thought I'd give Snus a go. I've never used it before but I knew it contained tobacco, and I liked the kick from cigarettes so I thought I'd give it a go.
On my way home, I put one portion under my lip and that stuff really stings. Ow.  Very unpleasant. The next 10-20 minutes I was wondering if it would have any effect, and I felt robbed on that nicotine kick I get from cigarettes. Then I sat down on a bench outside my home and just wanted to chill, and see if there would be any effects.
Shortly, I began to feel lightheaded, dizzy and nausea. I am not sure if it was some kind of placebo or anything, but when I looked down on the grass, it felt as if the ground was slightly breathing, just as I had read about some psychoactives. I thought it was 'cool', but I didnt like the nervous feeling in my body so I threw it away. I thought it wasn't worth the while and put the package away.
Later on, when I was about to go to bed I thought I still wanted to give them another try, so I put two portions (double dose, if you like) under my lip and awaited the effects. After 4-6 minutes I began to feel nervous, dizzy and feeling sick. Rebelliant, I was, and I wanted to stick with it to see if I could get some kind of high. Shortly, a cola sign which I have hanging from the cieling was slightly morphing and the colors were glowing. Kind of a plamsa feeling but nothing 'visually cool'. I thought maybe I just made it up, but I could clearly see the sign skew and the image breathe.
Soon I got very sick, and about the same moment I had this sexual lust growing up on me, so I thought I'd go to the bathroom to spit the snus out, and masturbate some. It felt really good, but also very alien at the same time. I can't decide if it was an overall pleasent feeling but my motor skills began to drift off so I spit out the snus shortly after ejaculation.
I threw up a couple of times and I've made up my mind. I don't like tobacco, and I will not probably use it again. Maybe I would on some party, but definatley not on a regular basis. It was not in it for me.
The sum up of the effects that I noted positive were:
Mild relaxation.
Happy buzz feeling.
Morphing and breathing.
Shimmering colors.
Motor failure (it was kinda fun trying to walk straight).
The sum up of the effects that I noted negative were:
Moderate Nausea.
Nervousity.
Foul and sour taste.
Foul smell.
Motor failure (was only fun a few moments).
The effects came up on me about 10-20 minutes when taking one dose, lasting to about 1 minute after throwing it away. Using two, I started feeling the effects strong and fast, in about 5 minutes. I estimate I had still the feeling in me five minutes after I spit it out. I didn't keep it in me much longer than until I started feeling the effects.
I'd rather smoke than using tobacco this way. If anyone would ever be curious about the brand I used, it's Gustavus Original. Can be found in Sweden. I wouldn't personally recommend this to anyone, but it was still 'fun to have experienced it'
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


These are the world's 'most excellent' airlines for 2020
Rankings according to AirlineRatings.com
by Francesca Street, CNNAUCKLAND, New Zealand - It's a country characterized by sandy beaches, jaw-dropping glaciers and sweeping mountain ranges -- and an industry-leading airline.
Air New Zealand is Airline of the Year for 2020, according to AirlineRatings.com, the Australia-based aviation safety and product rating agency.
AirlineRatings.com says the Kiwi carrier's record-breaking performance and inflight innovations -- not to mention its safety record and staff motivation -- earned it the win.
Taking back the number one slot from last year's winner Singapore Airlines, this is Air New Zealand's sixth time winning the travel award.
The Airline Excellence Awards cover the best of the best in the aviation world, recognizing the swankiest airline lounges, finest first class cabins and most exciting in-flight entertainment.
"In our analysis Air New Zealand came out number one in most of our audit criteria, which is an outstanding performance when it is up against carriers with more resources and scale," says Geoffrey Thomas, editor-in-chief of AirlineRatings.com.
Innovation and sustainability
This past year has seen airlines striving towards ultra long-haul flights and -- conversely -- assessing aviation's carbon footprint.
Thomas tells CNN Travel it was Air New Zealand's fleet age that helped cement the airline's eco-conscious status.
"In the past 10 years the airline has reduced its fuel burn and thus carbon emissions by almost 22%, ahead of the industry average," he says
"The airline has been a pioneer in a number of important industry initiatives such as biofuels and more efficient flight paths as well as a host of on ground improvements such as electric vehicles."
AirlineRatings.com's awards are judged by seven experienced editors using international industry and government safety audits, alongside 12 key criteria including fleet age, passenger reviews, investment ratings, staff relations, product offerings and profitability.
Qantas, currently in the middle of a series of test flights for its 19-hour stretch from London to Sydney, came in at number four on the overall ranking, but also picked up gongs for Best Domestic Airline Service and Best Lounges.
The airline didn't win the Excellence in Long Haul travel award, though.
Instead, Delta Air Lines took the top spot for the Americas, Lufthansa grabbed the gong in Europe, Emirates won in the Middle-East/Africa and Cathay Pacific Airways cinched the title in Asia-Pacific.
Last year's Airline of the Year winner Singapore Airlines won Best First Class this year.
"The editors said that the competition for top spot was tight with Singapore Airlines, Qantas and All Nippon Airways just being pipped at the post," says Thomas.
As for the budget options, JetBlue won Best Low-Cost Airline in the Americas, Wizz won in Europe, Air Arabia in the Middle East and Africa and Air Asia/Air Asia X won for Asia-Pacific.
AirlineRatings.com's top 10 airlines for 2020
1. Air New Zealand
2. Singapore Airlines
3. All Nippon Airways
4. Qantas
5. Cathay Pacific
6. Emirates
7. Virgin Atlantic
8. EVA Air
9. Qatar Airways
10. Virgin Australia


crystal-wait-group
This is a Crystal implementation of golang's sync.WaitGroup
There's probably still some work that needs to be done here, but it seems to work pretty well!
Installation
- Add the dependency to your
shard.yml
:
`yaml
dependencies:
crystal-wait-group:
github: jasonrobot/crystal-wait-group
`
- Run
shards install
Usage
require "crystal-wait-group"
To use like Go's WaitGroup, there are the add
, done
, and wait
methods. They should work just as expected.
wg = WaitGroup.new
wg.add
spawn do
sleep 1
wg.done
end
wg.wait
As a fun crystal-style addition, there is also a spawn
method which takes a block and spawns it in a fiber that is waited for by the WaitGroup.
wg = WaitGroup.new
wg.spawn do
sleep 1
end
wg.wait
Development
All feedback is welcome! This is my first time playing with concurrency at this level, or doing low-level Crystal stuff, so there's gotta be room for improvment. The usage of Intrinsics.pause
is taken from Crystal::SpinLock
. Basically what I've gone for here is a version of SpinLock built around an atomic counter.
Contributing
- Fork it (<https://github.com/jasonrobot/crystal-wait-group/fork>)
- Create your feature branch (
git checkout -b my-new-feature
) - Commit your changes (
git commit -am 'Add some feature'
) - Push to the branch (
git push origin my-new-feature
) - Create a new Pull Request
Contributors
- Jason Howell - creator and maintainer


Reflections
November 15, 2014
I can't believe we're already finished with the first 3 weeks of the prep work. It seems it just went by really quickly. I felt I've learned a lot in these past 3 weeks. I've realized I've also learned a lot about myself. This program really makes us reflect a lot especially after each week. Not only does this reaffirm what I've learned through this process, but also learn about the way we feel and react to certain learning situations.
In the first week I took a quiz about my Gregorc Thinking style. I got a tie between Abstract Sequential and Concrete Random. This covers a lot of the spectrum and I think a little of both describes my thinking styles... read more
November 15, 2014
So what is an array or a hash? Sounds like a Star Trek weapon and some breakfast food. They are both objects in the programming world, specifically in the language Ruby. Both have their own uses. Let's say you're a planning a party and you wanted to keep track of guest list. How would you be able to do this in a program? It might be helpful to make a list. read more
November 9, 2014
In HTML / CSS there are elements can be tagged with a specific ID or Class name. IDs are unique and are only supposed to be declared on one element in a document. Classes are not unique. A specific class can be used on more than one element. Also each element can also have more than one class. Let's say you had a list of items each in a "li" tag (which lists them out in bulletpoint form) and you placed each one in a class... read more
November 1, 2014
I'm pretty excited to start DBC. I think that DBC is a great new way to prepare you for a career. I think that traditional colleges do a poor job doing this. DBC gives you real world problems and you're set in an environment similar to the work setting. I believe DBC teaches you the tools to learn a programming language in a short amount of time. Buts it's not just about learning the language, it's more everything else that goes into being a great developer including soft skills. I think that the fast paced environment, where all the students are just as enthusiastic as me about learning the material, will just push me even harder to excel. read more
October 31, 2014
I just started week 1 of Phase 0 with DevBootcamp. I've actually learned quite a lot. I used to be confused about how GitHub worked but now it's very clear to me. Here's what I've learned so far.
Version Control is a pretty much an essential tool to programmers. Version control is a way to keep track of changes you make as you write your program or edit your files. Let's say you've added some code to a program and when you try to run the program, it crashes. Good thing you've got Version Control. You can now go back to the previously saved version and undo your mistakes. You can think of it like a video game. You wouldn't want to play through the whole video game without making any game saves. Well I think I did have a friend play a Final Fantasy game without a memory card; he would leave his ps2 on all day and night so he wouldn't lose his place in the game... read more


Main Title Text Here
Hops Tasty & Sons new seasons pearl district fixed gear co-op indie rock gentrification Saturday Market it's raining again.
Hops Tasty & Sons new seasons pearl district fixed gear co-op indie rock gentrification Saturday Market it's raining again.
Portland pop-up iceland kale chips tumblr literally meditation banjo ironypin farm-to-table cold-pressed. Portland pop-up iceland kale chips tumblr literally meditation.
...could be right here in the audience watching this random unknown guy sing into the mic.


MARY SHELLEY'S FRANKENSTEIN A film review by James Berardinelli Copyright 1994 James Berardinelli
Rating (0 to 10): 7.4
Date Released: 11/4/94 Running Length: 2:04 Rated: R (Violence, gore)
Starring: Kenneth Branagh, Robert De Niro, Helena Bonham Carter, Ian Holm, Tom Hulce, Aidan Quinn, Richard Briers, Robert Hardy, John Cleese Director: Kenneth Branagh Producers: Francis Ford Coppola, James V. Hart, and John Veitch Screenplay: Steph Lady and Frank Darabont based on the novel by Mary Shelly Cinematography: Roger Pratt Music: Patrick Doyle Released by TriStar Pictures
"In the last 20, 30 years, [FRANKENSTEIN has] been claimed by a whole generation of academics and scholars as a seminal piece of literature of that time. [It's] something which now, post-Freud, they feel reveals so many observations about family life, and incest, father-and-son relationships, and husband and wife relationships. [FRANKENSTEIN] speaks loudly to people, partly because it's so elusive. There's no definitive interpretation of it--it's certainly more than just a monster story." - Kenneth Branagh, director of MARY SHELLY'S FRANKENSTEIN
During the course of more than thirty adaptations, sequels, spin- offs, rip-offs, and spoofs, the name of "Frankenstein" has become associated with one of the world's most recognizable movie monsters. The creature, as typified by Boris Karloff with outstretched arms, flat- topped head, and ubiquitous neck bolts, has met the likes of Dracula, the Wolfman, and even Abbott and Costello. It has been played by (among others) Charles Ogle, Karloff, Lon Chaney, Bela Lugosi, Glenn Strange, Christopher Lee, Fred Gwynne (as Herman Munster), and now, Robert De Niro. Rarely, however, has a cinematic interpretation of "the daemon" approached the level of three-dimensionality with which it is portrayed in the novel.
As conceived and written by Shelly, FRANKENSTEIN was more of a gothic melodrama than a horror story. Considered in its most basic terms, the tale is one of actions and their consequences, and of what happens when man, in his hubris, attempts to usurp the role of God. For the most part, however, motion pictures have chosen to ignore the weightier issues of the book to concentrate instead on the "monster movie" aspects. With this latest cinematic depiction, director (and uncredited co-writer) Kenneth Branagh has taken a less-traveled path. He has chosen to view FRANKENSTEIN as a tragedy of Greek (or, given his background, Shakespearean) proportions.
What Branagh should recognize better than anyone, though, is that tragedy is at its most effective when allowed to cook slowly, basting in its own juices. This version of FRANKENSTEIN moves so frantically that far too many subtleties get lost along the way. The result is a rousing, occasionally-chaotic (especially during the choppily-edited first half-hour) piece of work that, while undeniably entertaining, lacks a depth that might otherwise have been attained. Patrick Doyle's bombastic score helps only to underline the melodramatic elements of this production, rarely allowing a quiet or reflective moment.
As far as its faithfulness to the source material is concerned, MARY SHELLY'S FRANKENSTEIN frequently differs from the book on plot points, but the two are thematically in synch. Several movie characters bear little resemblance to their book counterparts beyond having the same name (Dr. Waldeman, Frankenstein's mentor, being a chief example), and there is a significant alteration in the last act. Surprisingly enough, although it reflects nothing written by Shelly, this scene is effective in underlining the weaknesses and strengths of both Victor Frankenstein and his creature.
Can a man create life, then abandon his creation because its appearance horrifies him? To whom are its actions then attributable: the creature or the being who brought about its existence? Shelly did not answer these questions, but she certainly posed them. Following her example, Branagh does the same.
The greatest strength of MARY SHELLY'S FRANKENSTEIN is that it illustrates both the good and evil qualities in each of its main characters. Of the two--Robert De Niro's creature and Kenneth Branagh's Frankenstein--the former is, perhaps surprisingly, the more sympathetic. In part because of the script and in part because of the acting (De Niro gives a stronger performance than his director/co-star), the creature seems almost the more "human" of the two. In its own words, it is capable of great love and great rage. Frankenstein, on the other hand, often comes across as petty, self-serving, and ambitious. Only towards the end, when he finally grasps the full consequences of his actions, does the scientist capture a measure of our understanding.
Despite the presence of John Cleese--who is excellent in a straight, if somewhat limited, role--there is no comic relief in MARY SHELLY'S FRANKENSTEIN (or at least none that is intentional--a few lines here and there are too-obviously overacted, which can lead to a chuckle or two). However, since the screenplay is not relentlessly downbeat, the bursts of action and horror are effective enough in lessening tension that breaks of levity are not needed. In fact, given the tone of this film, humor might easily have seemed an unwelcome intrusion.
Shelly was never concerned about the scientific realism of Frankenstein's actions. She describes neither his experiments nor the practical (as opposed to the philosophical) reasoning that leads to them. In this film, while Branagh doesn't attempt to fully remedy this lapse (something that obviously can't be done), he presents enough pseudo- scientific evidence to suggest how the creation of a life might plausibly be accomplished. Suspension of disbelief is, of course, requisite for the viewer at this point.
One area where this FRANKENSTEIN meets expectations is in its cast. The weakest link is Branagh (and that's not to suggest that he gives a bad performance, because he doesn't), whose Victor is more than occasionally overwrought. De Niro, although buried beneath hours' worth of makeup, is less monstrous here than in films like CAPE FEAR and THE UNTOUCHABLES. The sequence where the creature befriends a family, anonymously providing them food (instead of firewood, as in the book) while observing and learning from them through a chink in a wall, is marvelously moving, and possibly the best moment offered by the film.
Helena Bonham Carter gives a feisty and fiery interpretation of Elizabeth, who eventually becomes much more than merely Frankenstein's love interest. Richard Briers (as the blind patriarch of the creature's adopted "family"), Ian Holm (as Frankenstein's father), Tom Hulce (as Frankenstein's best friend and fellow student, Henry Clerval), Aidan Quinn (as the north-pole bound explorer Robert Walton), Robert Hardy (as the odious Professor Krempe), Trevyn McDowell (as Justine, the Frankensteins' housekeeper) and John Cleese (as Waldeman, Frankenstein's mentor) round out the supporting cast.
The film has a striking visual look, which owes as much to the set design and special effects as to the soaring cinematography of Roger Pratt. Although Branagh does not opt for straight horror, the gothic element of the tale is very much in evidence as a result of the carefully-crafted atmosphere of several key scenes. From the Arctic Ocean to the Swiss Alps and the plague-riddled streets of Ingolstadt, MARY SHELLY'S FRANKENSTEIN is a wonder to behold.
Comparison's with 1992's BRAM STOKER'S DRACULA are inevitable, especially since both came from Francis Ford Coppola's American Zoetrope production company. Considering the merits of both movies, however, there is little doubt which is more effective. Kenneth Branagh's film is stronger thematically and visually, possesses more solid characterization, and boasts Robert De Niro and Helena Bonham Carter rather than Keanu Reeves and Winona Ryder. MARY SHELLY'S FRANKENSTEIN may not be the definitive version of the 1817 novel, and the director likely attempted more than is practical for a two-hour film, but overambition is preferable to the alternative, especially if it results--as in this case--in something more substantial than Hollywood's typical, fitfully entertaining fluff.
- James Berardinelli<EMAIL_ADDRESS>.
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
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


--- layout: post title: 3G demand grows, says Voda date: 2006-01-24 00:00:00 categories: business mobile ---
3G demand grows, says Voda: "Publishing its latest trading update, Vodafone confirmed that it added a further 3.1m 3G punters in the last quarter, taking its total 3G user base to 8m."


The Moviemaking Magic of Star Wars: Creatures + Aliens
Bantha
Only one elephant was used, so shots with two banthas were composed using optical effects. The only scene in A New Hope with more than one bantha is the shot where Luke is watching them through his macrobinoculars.
Dewback
George Lucas hated the final model as he thought it was too static. Maybe that’s why it was left (along with the Krayt dragon skeleton) abandoned in the Tunisian desert after production ended.
Jawas
Jawas were originally going to have rodent-like features, but they were eventually pared back to just glowing eyes in a dark hood. Jawas are one of the most recognizable Star Wars creatures so I think it’s pretty clear this was a good decision.


@RunWith(Parameterized.class)
without
a data provider method annotated with @Parameterized.Parameters
or with a data provider method that has an incorrect signature.
A data provider method should be public
, static
and have a return type of Iterable
or
Object[]
.
Such test classes cannot be run.
For example:
@RunWith(Parameterized.class)
public class ImportantTest {
private int input;
private int expected;
ImportantTest(int input, int expected) {
this.input = input;
this.expected = expected;
}
// ... test cases
}
A quick fix is provided to create an empty parameter provider method (though you'll need to implement it manually):
@RunWith(Parameterized.class)
public class ImportantTest {
private int input;
private int expected;
ImportantTest(int input, int expected) {
this.input = input;
this.expected = expected;
}
@Parameters
public static Iterable<Object[]> parameters() {
return null;
}
// ... test cases
}


| 046:035 Khan | : |
Therefore be patient (O Muhammad SAW) as did the Messengers of strong will and be in no haste about them (disbelievers). On the Day when they will see that (torment) with which they are promised (i.e. threatened, it will be) as if they had not stayed more than an hour in a single day. (O mankind! This Qur'an is sufficient as) a clear Message (or proclamation to save yourself from destruction). But shall any be destroyed except the people who are Al-Fasiqun (the rebellious, disobedient to Allah). |
| 046:035 Maulana | : |
So have patience, as men of resolution, the messengers, had patience, and seek not to hasten on for them (their doom). On the day when they see that which they are promised, (it will be) as if they had not tarried save an hour of the day. (Thine is) to deliver. Shall then any be destroyed save the transgressing people? |
| 046:035 Pickthal | : |
Then have patience (O Muhammad) even as the stout of heart among the messengers (of old) had patience, and seek not to hasten on (the doom) for them. On the day when they see that which they are promised (it will seem to them) as though they had tarried but an hour of daylight. A clear message. Shall any be destroyed save evil-living folk? |
| 046:035 Rashad | : |
Therefore, be patient like the messengers before you who possessed strength and resorted to patience. Do not be in a hurry to see the retribution that will inevitably come to them. The day they see it, it will seem as if they lasted one hour of the day. This is a proclamation: Is it not the wicked who are consistently annihilated? |
| 046:035 Sarwar | : |
(Muhammad), exercise patience as did the steadfast Messengers. Do not try to make them suffer the torment immediately; on the day when they will see the torment with which they were threatened, they will think that they had lived no more than an hour. The message has been delivered. No one else will be destroyed except the evil doing people. |
| 046:035 Shakir | : |
Therefore bear up patiently as did the messengers endowed with constancy bear up with patience and do not seek to hasten for them (their doom). On the day that they shall see what they are promised they shall be as if they had not tarried save an hour of the day. A sufficient exposition! Shall then any be destroyed save the transgressing people? |
| 046:035 Sherali | : |
Have patience, then, as the Messengers, possessed of high resolve, had patience; and be in no haste concerning them. On the day when they see that which they are threatened, it will appear to them as though they had not tarried in this world save for an hour of a day. This warning has been conveyed; and none but the disobedient people shall be destroyed. |
| 046:035 Yusufali | : |
Therefore patiently persevere, as did (all) messengers of inflexible purpose; and be in no haste about the (Unbelievers). On the Day that they see the (Punishment) promised them, (it will be) as if they had not tarried more than an hour in a single day. (Thine but) to proclaim the Message: but shall any be destroyed except those who transgress? |
Concepts/Themes Covered: أركان الإسلام > التوحيد > الكافرون > صفات الكفار Pillars of Islam> Islamic> The Disbelievers> The Characteristics of the Disbelievers أركان الإسلام > (محمد (صلى الله عليه وسلم > تسليته وتثبيته Pillars of Islam> The Blessed Muhammad(PBUH)> Cheering and Consolidating Him أركان الإسلام > (محمد (صلى الله عليه وسلم > مخاطبة الله إياه Pillars of Islam> The Blessed Muhammad(PBUH)> Allah's Address to Him(PBUH) الإيمان > اليوم الآخر > إثباته Faith> The Hereafter> Its Proof (Evidence) الإنسان والعلاقات الأخلاقية > الأخلاق الحميدة > الصبر Man and The Moral Relations> Good Morals>Patience
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


{{Site Title}}
{{Events}}
{{What's going on}}
{{Ticket}}
{{What needs to be done}}
{{Wiki}}
{{What we know}}
{{Team}}
{{Who we are}}
{{Dev-Tool}}
{{Git, Cron, Monitor}}
{{Site Title}}
{{Events}}
{{Ticket}}
{{Wiki}}
{{Team}}
{{Dev-Tool}}
<%if(user()) {%>
<%=user('name')%>
<%=user('title')%>
{{Settings}}
{{Logout}}
<%}else{%>
{{Login}}
{{Register}}
<%}%>


Salamander Rescue is 3D immersive game for 6th graders to learn science. Salamander Rescue Website is the official Website for the the game.
The primary goal is to create Salamander Rescue Website to bring more attention to an immersive 3D learning game---Salamander Rescue. It serves to introduce the content, key design features, as well as the direction for Salamander Rescue users.
HTML5, CSS3, Gliffy, Axure, Adobe Photoshop, Adobe Premiere, Camtasia, FileZilla


But, will everyone without BBLOG be able to see the line break?The line break exist, i only make it visible... people that will use this will be able to see posts better. Everyone has the ability to make a line break, and they actually use it but it is then not visible...
Who said that? I missed sth? lolbrain wrote:Em, i don't know why you say it makes no sense?
Everyone uses break lines when they post... when you enable them, you have a much better understanding of what they say... this must be a battlelog bug, that's why i say FIX.brain wrote:The plugin just make the overview for the feeds better.
If anybody wants to use it, they can use it without restrictions for non plugin users.
The line breaks still exist in the battlelog feeds, but not shown.
The plugin only enable the line breaks for the user that uses this plugin.
Thats the main part of bblog, make things better and more usefull for the user :-)
So, i won't include it into BBLog but its a nice addition.
$(this).html($(this).html().replace(/\n/gi,'').replace('',''));
$(this).html($.trim($(this).html()).replace(/\n/gi,''));
Take a better look. What i do is that i change the first back to a space... when i do it this way an extra break line appear at the start so i have to change it back ;)...brain wrote:Looks as it should be.
But why you use this 2 replaces instead of one
$(this).html($(this).html().replace(/\n/gi,'').replace('',''));
this should also work
$(this).html($.trim($(this).html()).replace(/\n/gi,''));
I can't understand where the bug is... this is what this plug in does...xXJumpyXx wrote:Found a small little bug in the plugin. All messages left on someone's battle feed will be a little bit messed up. I'll write up a small example below :P
This also makes it so you can't mark the text if you want to copy it.
----Without the Plugin----
xXJumpyXx» DJ-Brainnrg: Great work on BBLog :)
----With the Plugin----
xXJumpyXx»
DJ-Brainnrg: Great work on BBLog :)
I'm using Firefox, I haven't tried this on Chrome.
GreatApo wrote:I can't understand where the bug is... this is what this plug in does...xXJumpyXx wrote:Found a small little bug in the plugin. All messages left on someone's battle feed will be a little bit messed up. I'll write up a small example below :P
This also makes it so you can't mark the text if you want to copy it.
----Without the Plugin----
xXJumpyXx» DJ-Brainnrg: Great work on BBLog :)
----With the Plugin----
xXJumpyXx»
DJ-Brainnrg: Great work on BBLog :)
I'm using Firefox, I haven't tried this on Chrome.
The reason I called it a bug was because it makes all messages left in battle feeds look broken.GreatApo wrote:I can't understand where the bug is... this is what this plug in does...
Yes, you are right but this is up to you how you will write it... when you write a big comment and you break lines to make paragrafs or just go to a new line, you have a far more better look...xXJumpyXx wrote:The reason I called it a bug was because it makes all messages left in battle feeds look broken.
It might not really be a bug but you have to agree, it looks better the normal way.
xXJumpyXx» DJ-Brainnrg: {message}
VS.
xXJumpyXx»
DJ-Brainnrg: {message}
I'm just trying to help.
EDIT: In case you misunderstood what I meant, do what wasakakero said :)
The thing is that the part that gets broken (the names) aren't written by the user. It's automatic. It doesn't matter if the message is 1 letter or 100 letters long.GreatApo wrote:Yes, you are right but this is up to you how you will write it... when you write a big comment and you break lines to make paragrafs or just go to a new line, you have a far more better look...
Yea, i just found out what you mean, i will try to fix such isues... thanks for informing me.xXJumpyXx wrote:The thing is that the part that gets broken (the names) aren't written by the user. It's automatic. It doesn't matter if the message is 1 letter or 100 letters long.


Install
$ sudo gem install twitter
note: the twitter gem now works with hpricot 0.5+
API Wrapping
I do my best to keep it easy to use. Below are some code samples showing a few of the methods.
twit = twit
twit.update('watching veronica mars')
puts "Public Timeline", "=" * 50
twit.timeline(:public).each do |s|
puts s.text, s.user.name
puts
end
puts '', "Friends Timeline", "=" * 50
twit.timeline(:friends).each do |s|
puts s.text, s.user.name
puts
end
puts '', "You and Your Friends Timeline", "=" * 50
twit.timeline(:user).each do |s|
puts s.text, s.user.name
puts
end
puts '', "Your Friends", "=" * 50
twit.friends.each do |u|
puts u.name, u.status.text
puts
end
puts '', "jnunemaker's Friends", "=" * 50
twit.friends_for('jnunemaker').each do |u|
puts u.name
puts
end
puts '', "Your Followers", "=" * 50
twit.followers.each do |u|
puts u.name
puts
end
Search API Examples
#searches all tweets for httparty
Twitter::Search.new('httparty').each { |r| puts r.inspect }
# searches all of jnunemaker's tweets for httparty
Twitter::Search.new('httparty').from('jnunemaker').each { |r| puts r.inspect }
# searches all tweets from jnunemaker to oaknd1
Twitter::Search.new.from('jnunemaker').to('oaknd1').each { |r| puts r.inspect }
# you can also use fetch to actually just get the parsed response
Twitter::Search.new.from('jnunemaker').to('oaknd1').fetch()
Command Line
Note: If you want to use twitter from the command line be sure that sqlite3 and the sqlite3-ruby gem are installed. I removed the sqlite3-ruby gem as a dependency because you shouldn't need that to just use the API wrapper. Eventually I'll move the CLI interface into another gem.
The first thing you'll want to do is install the database so your account(s) can be stored.
$ twitter install
You can always uninstall twitter like this:
$ twitter uninstall
Once the twitter database is installed and migrated, you can add accounts like this:
$ twitter add
Add New Account:
Username: jnunemaker
Password (won't be displayed):
Account added.
You can also list all the accounts you've added.
$ twitter list
Account List
* jnunemaker
snitch_test
The * means denotes the account that will be used when posting, befriending, defriending, following, leaving or viewing a timeline.
To post using the account marked with the *, simply type the following:
$ twitter post "releasing my new twitter gem"
That is about it. You can do pretty much anything that you can do with twitter from the command line interface.
$ twitter
Will give you a list of all the commands. You can get the help for each command by running twitter [command] -h.
Support
Conversations welcome in the google group and bugs/features over at lighthouse
Uses
- Snitch
- Growl + Twitter
- Twitter Woot Bot (more here)
- Tweet Quicksilver Action
- logging security events to twitter
- Shareomatic is using it for their twitter account
Using the twitter gem for something, let me know and I'll add you above.


3.4.5. Site Response Analysis¶
s3hark allows users to determine the event at the base of the building by performing an effective free-field site response analysis of a soil column. In this panel the user specifies a ground motion at the bottom of the soil column. After the soil layers have been properly defined, the motion at the ground surface are given at the end of the analysis and that motion can be used in the simulation of the building response.
The full user graphic interface looks like what is shown in Fig. 3.4.6
Clicking the arrow between the Soil Column Graphic and the FE Mesh Graphic will hide the FE Mesh Graphic, which makes the UI look like what is shown in Fig. 3.4.7.
The UI of s3hark consists of the following components:
<IP_ADDRESS>. Soil Column Graphic¶
The first graphic on the left of the panel shows a visualization of the soil column created. Each layer has a different randomly generated color. When the user add or delete a soil layer, this graphic will refresh.
<IP_ADDRESS>. FE Mesh Graphic¶
The second graphic on the left shows the finite element mesh and profile plots. Upon the finish of the analysis, selecting any of the tabs on the right inside this graphic (i.e., PGA, \(\gamma max\), maxDisp, maxRu, maxRuPWP) will show various results from the simulation at the mesh points.
<IP_ADDRESS>. Operations Area¶
The right side of this area shows some information of the created soil column, such as the total height and number of soil layers. The user also finds the Ground Water Table (GWT) input field, plus and minus buttons in this area. If the user pressed the plus button, a layer will be added below a currently selected layer. If the minus button is pressed the currently selected layer will be removed. The GWT input field allows the user to specify the level of the ground water table.
Note
Variables are assumed to have m, kPa, and kN units in s3hark.
<IP_ADDRESS>. Soil Layer Table¶
This table is where the user provides the characteristics of soil layers, such as layer thickness, density, Vs30, material type, and element size in the finite element mesh.
Single click at a cell will make a soil layer selected, which will highlight the layer using green color in the table.
Also the layer will be highlighted by red box in the Soil Column Graphic.
Meanwhile the Layer Properties Tab will be activated.
Double click a cell to edit it in the table.
If you change the Material
cell of a layer, the Layer Properties Tab will change correspondingly.
<IP_ADDRESS>. Tabbed Area¶
This area contains the three tabbed widgets described below.
Configure Tab
“““““““““““““““““““
This tab allows the user to specify the paths to the OpenSees executable and a ground motion file that represent the ground shaking at the
bedrock. The rock motion file must follow the SimCenter event format.
Examples of SimCenter event files are available in the motion demos
.
s3hark will determine to use 2D column or 3D column based on the ground motion file provided.
When a ground motion file is selected from the local computer, or the path of the ground motion file is typed in,
s3hark will figure out if it’s a 1D or 2D shaking file. If it’s 1D shaking, all elements will be 2D. If it’s 2D shaking,
all elements will be 3D.
The definition of 2D and 3D slope are different. See Fig. 3.4.13 and Fig. 3.4.15.
More details about this tab can be found in Configure.
Layer Properties Tab ““““““““““““““““““““““ This tab allows the user to enter additional material properties for the selected soil layer Fig. 3.4.8.
Response Tab “““““““““““““ Once the site response analysis has been performed, this tab provides information about element and nodal time varying response quantities. See Fig. 3.4.9.
<IP_ADDRESS>. Analyze Button¶
This Analyze button is located at the top-right corner of the UI and shall be used to run the simulation locally on your computer. A progress bar will show up at the bottom of the application indicating the status of the analysis. Upon the finish of the simulation, a message will be displayed (Fig. 3.4.10).
<IP_ADDRESS>. View Results¶
Click the button to dismiss the message window, the response tab will be activated.
The user can click on any element in the mesh graphic, the selected element will be highlighted in red and the selected nodes will be pointed out by blue arrows.
The time history of selected element / node will be shown in the Response Tab.
This allows the user to review the ground motion predicted at selected nodes Fig. 3.4.11.
Note
If the Analyze button is not pressed, no simulation will be performed, therefore no simulation is performed and there will be no ground motions provided to the building, if your are using s3hark inside other SimCenter applications.
<IP_ADDRESS>. Configure¶
In the configure tab, two paths need to be specified.
You can either type them or click the ‘+’ button to select them from your computer.
If you don’t have OpenSees installed, the instruction can be found here.
If you don’t have a ground motion file, demos can be downloaded here
.
Note
Variables are assumed to have m, kPa, and kN units in s3hark.
The first demo is SRT-GM-Input-Style3.json, which contains the shaking motion in one direction (1D shaking). If you select this files as the input motion, your tab will look like the one shown in Fig. 3.4.12. You can edit the slope degree \(\alpha\). For flat ground the value should be set as 0. If 1D shaking motion provided, s3hark automatically treat the problem as a 2D plane strain problem. 2D elements will be used. The slope diagram is plotted in Fig. 3.4.13.
The second demo is SRT-GM-Input-Style3-2D.json, which contains the shaking motion in two directions (2D shaking). If you select this file as the input motion, your tab will look like the one shown in Fig. 3.4.14.
You can see s3hark detected the file you provided is a 2D shaking, s3hark automatically treat the problem as a 3D problem. 3D elements will be used. The slope diagram is plotted in Fig. 3.4.15:
For flat ground \(\alpha\) and \(\beta\) should be set as 0.


| Class | Log | I'm a log file. You can write to me and close me. Me and my brothers
|
| Class | ErrorLog | Error log for collecting information about problems which occur
while
|
| Function | log | Write arguments to sys.stderr, which has been overridden by an
ErrorLog
|


[gecode-users] last question
Guido Tack
tack at ps.uni-sb.de
Tue Aug 22 18:05:53 CEST 2006
Hi Kilian.
> this is surely my last question for today:
Don't worry - this list is not exactly flooded with traffic ;-)
> There is something I dont understand about using the minimodel -- I
> can see that it provides a more functional approach, creating
> variables on the fly in nested expressions.
>
> But it does not seem to be necessary to attach those variables to
> the Store... Dont they need to be copied?
Variables are always copied automatically by the propagators that use
them. However, if a propagator "loses interest" in a variable, it can
drop its subscription and not copy it. That is why you have to copy
all those variables manually that you want to access in your solution.
For temporary variables, not copying them explicitly does exactly the
right thing: they are copied as long as any propagator depends on
them, and after that they are discarded.
Cheers,
Guido
--
Guido Tack
Programming Systems Lab, Saarland University, Germany
http://www.ps.uni-sb.de/~tack
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We don’t often think of parrots as successful invasive species. The monk parakeet, Myiopsitta monachus, is a widespread invader in the Northern hemisphere. Monk parakeets are native to temperate South America, and have been dispersed to other countries by means of the global pet trade. Monks survive winters in Chicago, Brooklyn and Washington State. Recently, SEO/BirdLife volunteers estimated around 20,000 monk parakeets in Spanish cities .
I’ve been working on maps of monk parakeet sightings using Global Biodiversity Information Facility (GBIF) data. Introduced populations are nearly always found in cities or suburbs. I’ve included some code below to explore how monk parakeets are distributed across different land class categories in Uruguay, a country thought to be the origin for introduced populations. Keep in mind that GBIF sightings will be biased by human reporting.
The map I will make here is heavily based off of Oscar Perpiñán Lamigueiro’s code to create lattice maps using raster layers: see link for Oscar’s original code.
r
knitr::opts_chunk$set(fig.path='/images/uruguay-mymon-map-')
r
# make sure to install packages
library(maps)
library(mapdata)
library(ggmap)
library(ggplot2)
library(maptools) #for shapefiles
library(scales) #for transparency
library(RColorBrewer)
library(rgeos)
library(rgdal)
library(sp)
library(rgbif)
library(raster)
library(rasterVis)
library(colorspace)
library(lattice)
library(latticeExtra)
library(grid)
library(gridExtra)
library(grDevices)
Read in GBIF monk parakeet (Myiopsitta monachus) sightings and Uruguay administrative bouandaries
```r mymon <- read.csv(“mymon.csv”, header = TRUE)
URY_adm0 <- readShapePoly(“URY_adm0.shp”, proj4string=CRS(“+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0”)) # country border
URY_adm0_df <- fortify(URY_adm0) ```
Retain only GBIF observations contained within the country level polygon, using sp::over(). I did this because GBIF observations do not always contain accurate stateProvince information. Also, reading in Uruguay roads as shapefiles.
```r # create SpatialPoints object of monk parakeet observations lon <- mymon$decimalLongitude lat <- mymon$decimalLatitude mat <- as.matrix(cbind(lon, lat)) p <- SpatialPoints(mat, proj4string = CRS(“+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0”))
URY <- !is.na(over(p, as(URY_adm0, “SpatialPolygons”)))
lon.URY.in <- lon[which(URY == TRUE)] lat.URY.in <- lat[which(URY == TRUE)]
# same coordinate system as gadm data mat2 <- as.matrix(cbind(lon.URY.in, lat.URY.in)) p2 <- SpatialPoints(mat2, proj4string = CRS(“+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0”))
conv.lon <- p2@coords[, 1] conv.lat <- p2@coords[, 2] points <- data.frame(lon = conv.lon, lat = conv.lat)
# from Natural Earth http://www.naturalearthdata.com/downloads/10m-cultural-vectors/ URYroadsOGR <- readOGR(“URY_roads.shp”, “URY_roads”) str(URYroadsOGR) URYroads <- spTransform(URYroadsOGR, CRS(“+proj=longlat +datum=WGS84”)) URYroads_df <- fortify(URYroads) str(URYroads_df) ```
Read in and crop global population raster
```r # download global population and land cover MODIS data as GEOTiff # http://neo.sci.gsfc.nasa.gov
b <- extent(-59, -53, -35.5, -29.5)
pop <- raster(“SEDAC_POP_2000-01-01_rgb_3600x1800.FLOAT-2.TIFF”) pop <- crop(pop, b) pop[pop == 99999] <- NA
# for a less pixelated map, this doesn’t work well for the land cover raster pop2 <- disaggregate(pop, fact = 10, method = “bilinear”) ```
Read in and crop global land cover raster layers
```r # I’m only using a handful of land cover categories for Uruguay # Check out all categories: # http://eoimages.gsfc.nasa.gov/images/news/NasaNews/ReleaseImages/LCC/Images/lcc_key.jpg
landClass <- raster(“LandClass_RenderData”) landClass <- crop(landClass, b) landClass[landClass %in% c(0, 254)] <- NA
landClass <- cut(landClass, c(8, 10, 11, 12, 13))
landClass <- ratify(landClass)
# 1) create a RAT data.frame using the levels method # 2) set the values for each class (to be used by levelplot) # 3) assign this RAT to the raster rat <- levels(landClass)[[1]]
rat$classes <- c(“GRASSLANDS”, “WETLANDS”, “CROPLANDS”, “URBAN”) levels(landClass) <- rat
# lowering max limit of population scale, since Uruguay is not densely populated # at <- pTotal$legend$bottom$args$key$at # from original code at <- seq(pop2@data@min, pop2@data@max, pop2@data@max/16)
nClasses <- nrow(rat) ```
Creating a lattice map object, with land cover layer now scaled by population numbers
```r # initialize pList, a list of levelplots pList <- NULL
ev <- c(seq(2, nClasses, 2)) od <- c(seq(1, nClasses, 2))
pList <- lapply(1:nClasses, function(i){
landSub <- landClass
# assign NAs to all land classes that are not pulled out by the current iteration of i landSub[!(landClass == rat$ID[i])] <- NA
popSub <- mask(pop2, landSub) # mask population by land classes
# color land class categories step <- 180/nClasses if(grepl(“URB”, rat$classes[i])){ # making urban category stand out pal <- rev(heat_hcl(28, h = 0, c. = c(80,30), l = c(30,90), power = c(1/5,1.5)))[-c(1:10)] }else if(i %in% ev){ pal <- rev(terrain_hcl(28, h = (30 + step(i-1))%%360, c. = c(65,0), l = c(45,95), power = c(1/3, 1.5)))[-c(1:10)] }else if(i %in% od){ pal <- rev(heat_hcl(28, h = (90 + step(i-1))%%360, c. = c(80,30), l = c(30,90), power = c(1/5,1.5)))[-c(1:10)] }
# creating levelplot for the current land class pClass <- levelplot(popSub, at=at, col.regions=pal, margin=FALSE, labels = list(labels = c(ceiling(at)), cex = 3), xlab = list(label = “Longitude”, cex = 3), ylab = list(label= “Latitude”, cex = 3), scales = list(cex = 2)) })
p <- Reduce(‘+’, pList) # only one legend appears
cols <- 1 rows <- 2
addTitle <- function(legend, title){
# the urban legend ends up on the right hand side, # and the text gets skewed, so I’m treating this label differently if(grepl(“URB”, title)){ titleGrob <- textGrob(title, gp=gpar(fontsize=25), rot = 270, x = 0.1, y = 0.9, just = “left”) } else{ titleGrob <- textGrob(title, gp=gpar(fontsize=25), rot = 270, y = 0.9, just = “left”) }
legendGrob <- eval(as.call(c(as.symbol(legend$fun), legend$args)))
# specifying one column and two rows for the legend and title below ly <- grid.layout(ncol=cols, nrow=rows, heights=unit(c(0.8,0.2), rep(‘npc’, cols)), widths=unit(rep(0.1,rows), rep(‘npc’, rows)))
# packing legends with titles into a frame Grob fg <- frameGrob(ly, name=paste(‘legendTitle’, title, sep=’_’)) pg <- packGrob(fg, legendGrob, col=1, row=1) pg <- packGrob(pg, titleGrob, col=1, row=2)
}
for (i in 1:nClasses){ lg <- pList[[i]]$legend$right lg$labels <- ceiling(at) lg$args$key$labels$cex = ifelse(i==nClasses, 2, 0) # only the last legend needs labels pList[[i]]$legend$right <- list(fun=’addTitle’, args=list(legend=lg, title=rat$classes[i])) }
legendList <- lapply(pList, function(x){ lg <- x$legend$right clKey <- eval(as.call(c(as.symbol(lg$fun), lg$args))) clKey })
# adapted from latticeExtra::: mergedTrellisLegendGrob packLegend <- function(legendList){ N <- length(legendList) ly <- grid.layout(nrow = 1, ncol = N) g <- frameGrob(layout = ly, name = “mergedLegend”) for (i in 1:N) g <- packGrob(g, legendList[[i]], col = i) g }
p$legend$right <- list(fun = ‘packLegend’, args = list(legendList = legendList))
dev.off() ```
Adding other layers to the trellis object p: country border, roads and GBIF sightings
```r # creating another legend for these additional layers lGrob <- legendGrob(labels = c(“URY border”, “URY roads”, expression(italic(M.monachus )~sightings)), nrow = 1, ncol = 3, default.units = “lines”, pch = 21, gp = gpar(fill = c(diverge_hcl(12, h = 246,40, c=96)[1], diverge_hcl(12, h = 246,40, c=96)[6], heat.colors(12, alpha = 0.6)[9]), col = c(“black”, “black”, heat.colors(12)[3]), cex = 2))
bGrob <- rectGrob(gp = gpar(col = “white”))
mainGrob <- p + latticeExtra::layer(sp.polygons(URY_adm0, lwd = 4, col = diverge_hcl(12, h = 246,40, c=96)[1])) + latticeExtra::layer(sp.lines(URYroadsOGR, lwd = 2, col = diverge_hcl(12, h = 246,40, c=96)[6])) + latticeExtra::layer(panel.points(points, pch = 21, cex = 2.5, fill = heat.colors(12, alpha = 0.6)[9], col = heat.colors(12)[3]))
labGrob <- textGrob(expression(“Population density” (persons/km^{2})), default.units = “lines”, rot = 270, gp = gpar(fontsize = 27))
h <- 40 w <- 40
trellis.device(‘png’, file = “Mymon_Uruguay_landcover.png”, units = “cm”, height = h, width = w, res = 600) grid.arrange(arrangeGrob(lGrob, bGrob, mainGrob, nrow = 3, heights = unit(c((h/h)2, h/(h10), h - h/h - h/h*2), units = ‘cm’)), labGrob, ncol = 2, widths = unit(c(35, 2), units = ‘cm’)) ```