17 GEE, Count Outcome: Epilepsy
17.1 Packages
17.1.1 CRAN
library(tidyverse) # all things tidy
library(pander) # nice looking genderal tabulations
library(furniture) # nice table1() descriptives
library(texreg) # Convert Regression Output to LaTeX or HTML Tables
library(psych) # contains some useful functions, like headTail
library(lme4) # Linear, generalized linear, & nonlinear mixed models
library(corrplot) # Vizualize correlation matrix
library(gee) # Genderalized Estimation Equation Solver
library(geepack) # Genderalized Estimation Equation Package
library(MuMIn) # Multi-Model Inference (caluclate QIC)
library(HSAUR) # package with the dataset
17.2 Background
This dataset was used as an example in Chapter 11 of “A Handbook of Statistical Analysis using R” by Brian S. Everitt and Torsten Hothorn. The authors include this data set in their HSAUR package on
CRAN
.
The Background
In this clinical trial, 59 patients suffering from epilepsy were randomized to groups receiving either the anti-epileptic drug “Progabide”” or a placebo in addition to standard chemotherapy. The numbers of seizures suffered in each of four, two-week periods were recorded for each patient along with a baseline seizure count for the 8 weeks prior to being randomized to treatment and age.
The Research Question
The main question of interest is whether taking progabide reduced the number of epileptic seizures compared with placebo.
The Data
Indicators
subject
the patient ID, a factor with levels 1 to 59
period
treatment period, an ordered factor with levels 1 to 4
Outcome or dependent variable
+
seizure.rate
the number of seizures (2-weeks)Main predictor or independent variable of interest
treatment
the treatment group, a factor with levels placebo and Progabide
Time-invariant Covariates
age
the age of the patient
base
the number of seizures before the trial (8 weeks)
17.2.1 Read in the data
data("epilepsy", package = "HSAUR")
Problem: The outcome (seizure.rate
) were counts over a TWO-week period and we would like to interpret the results in terms of effects on the WEEKLY rate.
- If we divide the values by TWO to get weekly rates, the outcome might be a decimal number
- The Poisson distribution may only be used for whole numbers (not deciamls)
Solution: We need to include an offset
term in the model that indicates the LOG DURATION of each period.
- Every observation period is exactly 2 weeks in this experiment
- Create a variable in the original dataset that is equal to the LOG DURATION (
per = log(2)
) - To the formula for the
glm()
orgee()
, add:+ offset(per)
17.2.2 Long Format
<- epilepsy %>%
data_long ::select(subject, age, treatment, base,
dplyr%>%
period, seizure.rate) ::mutate(per = log(2)) %>% # new variable to use with the offset
dplyr::mutate(base_wk = base/8)
dplyr
str(data_long)
'data.frame': 236 obs. of 8 variables:
$ subject : Factor w/ 59 levels "1","2","3","4",..: 1 1 1 1 2 2 2 2 3 3 ...
$ age : int 31 31 31 31 30 30 30 30 25 25 ...
$ treatment : Factor w/ 2 levels "placebo","Progabide": 1 1 1 1 1 1 1 1 1 1 ...
$ base : int 11 11 11 11 11 11 11 11 6 6 ...
$ period : Ord.factor w/ 4 levels "1"<"2"<"3"<"4": 1 2 3 4 1 2 3 4 1 2 ...
$ seizure.rate: int 5 3 3 3 3 5 3 3 2 4 ...
$ per : num 0.693 0.693 0.693 0.693 0.693 ...
$ base_wk : num 1.38 1.38 1.38 1.38 1.38 ...
::headTail(data_long, top = 10, bottom = 6) psych
subject age treatment base period seizure.rate per base_wk
1 1 31 placebo 11 1 5 0.69 1.38
110 1 31 placebo 11 2 3 0.69 1.38
112 1 31 placebo 11 3 3 0.69 1.38
114 1 31 placebo 11 4 3 0.69 1.38
2 2 30 placebo 11 1 3 0.69 1.38
210 2 30 placebo 11 2 5 0.69 1.38
212 2 30 placebo 11 3 3 0.69 1.38
214 2 30 placebo 11 4 3 0.69 1.38
3 3 25 placebo 6 1 2 0.69 0.75
310 3 25 placebo 6 2 4 0.69 0.75
... <NA> ... <NA> ... <NA> ... ... ...
582 58 36 Progabide 13 3 0 0.69 1.62
583 58 36 Progabide 13 4 0 0.69 1.62
59 59 37 Progabide 12 1 1 0.69 1.5
591 59 37 Progabide 12 2 4 0.69 1.5
592 59 37 Progabide 12 3 3 0.69 1.5
593 59 37 Progabide 12 4 2 0.69 1.5
17.2.3 Wide Format
<- data_long %>%
data_wide ::spread(key = period,
tidyrvalue = seizure.rate,
sep = "_") %>%
::arrange(subject)
dplyr
str(data_wide)
'data.frame': 59 obs. of 10 variables:
$ subject : Factor w/ 59 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
$ age : int 31 30 25 36 22 29 31 42 37 28 ...
$ treatment: Factor w/ 2 levels "placebo","Progabide": 1 1 1 1 1 1 1 1 1 1 ...
$ base : int 11 11 6 8 66 27 12 52 23 10 ...
$ per : num 0.693 0.693 0.693 0.693 0.693 ...
$ base_wk : num 1.38 1.38 0.75 1 8.25 ...
$ period_1 : int 5 3 2 4 7 5 6 40 5 14 ...
$ period_2 : int 3 5 4 4 18 2 4 20 6 13 ...
$ period_3 : int 3 3 0 1 9 8 0 23 6 6 ...
$ period_4 : int 3 3 5 4 21 7 2 12 5 0 ...
::headTail(data_wide) psych
subject age treatment base per base_wk period_1 period_2 period_3 period_4
1 1 31 placebo 11 0.69 1.38 5 3 3 3
2 2 30 placebo 11 0.69 1.38 3 5 3 3
3 3 25 placebo 6 0.69 0.75 2 4 0 5
4 4 36 placebo 8 0.69 1 4 4 1 4
... <NA> ... <NA> ... ... ... ... ... ... ...
56 56 26 Progabide 22 0.69 2.75 1 23 19 8
57 57 21 Progabide 25 0.69 3.12 2 3 0 1
58 58 36 Progabide 13 0.69 1.62 0 0 0 0
59 59 37 Progabide 12 0.69 1.5 1 4 3 2
17.3 Exploratory Data Analysis
17.3.1 Summarize
<IP_ADDRESS> Demographics and Baseline
%>%
data_wide ::group_by(treatment) %>%
dplyr::table1(age, base, base_wk,
furnituretotal = TRUE,
test = TRUE,
digits = 2,
type = "full",
output = "markdown")
| Total | placebo | Progabide | Test | P-Value | |
|---|---|---|---|---|---|
| n = 59 | n = 28 | n = 31 | |||
| age | T-Test: 0.76 | 0.449 | |||
| 28.34 (6.30) | 29.00 (6.00) | 27.74 (6.60) | |||
| base | T-Test: -0.12 | 0.907 | |||
| 31.22 (26.88) | 30.79 (26.10) | 31.61 (27.98) | |||
| base_wk | T-Test: -0.12 | 0.907 | |||
| 3.90 (3.36) | 3.85 (3.26) | 3.95 (3.50) |
<IP_ADDRESS> Outcome Across Time
Note: The Poisson distribution specifies that the MEAN = VARIANCE
In this dataset, the variance is much larger than the mean, at all time points for both groups. This is evidence of overdispersion and suggest the scale parameter should be greater than one.
%>%
data_long ::group_by(treatment, period) %>%
dplyr::summarise(N = n(),
dplyrM = mean(seizure.rate),
VAR = var(seizure.rate),
SD = sd(seizure.rate)) %>%
::pander() pander
summarise()
has grouped output by ‘treatment’. You can override using the .groups
argument.
| treatment | period | N | M | VAR | SD |
|---|---|---|---|---|---|
| placebo | 1 | 28 | 9.4 | 103 | 10.1 |
| placebo | 2 | 28 | 8.3 | 67 | 8.2 |
| placebo | 3 | 28 | 8.8 | 215 | 14.7 |
| placebo | 4 | 28 | 8.0 | 58 | 7.6 |
| Progabide | 1 | 31 | 8.6 | 333 | 18.2 |
| Progabide | 2 | 31 | 8.4 | 141 | 11.9 |
| Progabide | 3 | 31 | 8.1 | 193 | 13.9 |
| Progabide | 4 | 31 | 6.7 | 127 | 11.3 |
<IP_ADDRESS> Correlation Across Time
Raw Scale
%>%
data_long ::select(subject, period, seizure.rate ) %>%
dplyr::spread(key = period,
tidyrvalue = seizure.rate ) %>%
::select(-subject) %>%
dplyrcor() %>%
::corrplot.mixed() corrplot
Log Scale
%>%
data_long ::mutate(rate_wk = log(seizure.rate + 1)) %>%
dplyr::select(subject, period, rate_wk) %>%
dplyr::spread(key = period,
tidyrvalue = rate_wk) %>%
::select(-subject) %>%
dplyrcor() %>%
::corrplot.mixed() corrplot
17.3.2 Visualize
<IP_ADDRESS> Oucome on the Raw Scale
There appear to be quite a few extreme values or outliers, particularly for the Progabide group during period one.
Since the outcome is truely a COUNT, we will model it with a Poisson distribution combined with a LOG link.
%>%
data_long ggplot(aes(x = period,
y = seizure.rate)) +
geom_boxplot() +
theme_bw() +
facet_grid(.~ treatment)
To investigate possible outliers, we should transform the outcome with the log
function first.
Note: Since some participants reported no seizures during a two week period and the
log(0)
is unndefinded, we must add some amount to the values before transforming. Here we have chosen to add the value of \(1\).
%>%
data_long ggplot(aes(x = period,
y = log(seizure.rate + 1))) +
geom_boxplot() +
theme_bw() +
facet_grid(.~ treatment)
%>%
data_long ggplot(aes(x = period,
y = log(seizure.rate + 1))) +
geom_line(aes(group = subject)) +
theme_bw() +
facet_grid(.~ treatment)
%>%
data_long ggplot(aes(x = period,
y = log(seizure.rate + 1))) +
geom_smooth(aes(group = subject),
method = "lm",
se = FALSE) +
geom_smooth(aes(group = 1),
color = "red",
size = 1.5,
method = "lm",
se = FALSE) +
theme_bw() +
facet_grid(.~ treatment)
17.4 Poisson Regression (GLM)
Note: THIS IS NEVER APPROPRIATE TO CONDUCT A GLM ON REPEATED MEASURES. THIS IS DONE FOR ILLUSTRATION PURPOSES ONLY!
17.4.1 Fit the model
<- glm(seizure.rate ~ base + age + treatment + offset(per),
fit_glm data = data_long,
family = poisson(link = "log"))
summary(fit_glm)
Call:
glm(formula = seizure.rate ~ base + age + treatment + offset(per),
family = poisson(link = "log"), data = data_long)
Deviance Residuals:
Min 1Q Median 3Q Max
-4.4360 -1.4034 -0.5029 0.4842 12.3223
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.1306156 0.1356191 -0.963 0.3355
base 0.0226517 0.0005093 44.476 < 2e-16 ***
age 0.0227401 0.0040240 5.651 1.59e-08 ***
treatmentProgabide -0.1527009 0.0478051 -3.194 0.0014 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 2521.75 on 235 degrees of freedom
Residual deviance: 958.46 on 232 degrees of freedom
AIC: 1732.5
Number of Fisher Scoring iterations: 5
17.4.2 Tabulate the Model Parameters
::knitreg(list(fit_glm,
texreg::extract_glm_exp(fit_glm,
texreghelprinclude.any = FALSE)),
custom.model.names = c("b (SE)", "IRR [95 CI]"),
caption = "Poisson Generalized Linear Regression (GLM)",
single.row = TRUE,
digits = 3,
ci.test = 1)
| b (SE) | IRR [95 CI] | |
|---|---|---|
| (Intercept) | -0.131 (0.136) | 0.878 [0.672; 1.144] |
| base | 0.023 (0.001)*** | 1.023 [1.022; 1.024]* |
| age | 0.023 (0.004)*** | 1.023 [1.015; 1.031]* |
| treatmentProgabide | -0.153 (0.048)** | 0.858 [0.782; 0.943]* |
| AIC | 1732.459 | |
| BIC | 1746.314 | |
| Log Likelihood | -862.229 | |
| Deviance | 958.464 | |
| Num. obs. | 236 | |
| ***p < 0.001; **p < 0.01; *p < 0.05 (or Null hypothesis value outside the confidence interval). |
17.5 Generalized Estimating Equations (GEE)
17.5.1 Match Poisson Regresssion (GLM)
- correlation structure:
independence
- scale parameter = \(1\)
<- gee::gee(seizure.rate ~ base + age + treatment + offset(per),
fit_gee_ind_s1 data = data_long,
family = poisson(link = "log"),
id = subject,
corstr = "independence",
scale.fix = TRUE,
scale.value = 1)
(Intercept) base age treatmentProgabide
-0.13061561 0.02265174 0.02274013 -0.15270095
summary(fit_gee_ind_s1)
GEE: GENERALIZED LINEAR MODELS FOR DEPENDENT DATA
gee S-function, version 4.13 modified 98/01/27 (1998)
Model:
Link: Logarithm
Variance to Mean Relation: Poisson
Correlation Structure: Independent
Call:
gee::gee(formula = seizure.rate ~ base + age + treatment + offset(per),
id = subject, data = data_long, family = poisson(link = "log"),
corstr = "independence", scale.fix = TRUE, scale.value = 1)
Summary of Residuals:
Min 1Q Median 3Q Max
-4.9195387 0.1808059 1.7073405 4.8850644 69.9658560
Coefficients:
Estimate Naive S.E. Naive z Robust S.E. Robust z
(Intercept) -0.13061561 0.1356191185 -0.9631062 0.365148155 -0.3577058
base 0.02265174 0.0005093011 44.4761250 0.001235664 18.3316325
age 0.02274013 0.0040239970 5.6511312 0.011580405 1.9636736
treatmentProgabide -0.15270095 0.0478051054 -3.1942393 0.171108915 -0.8924196
Estimated Scale Parameter: 1
Number of Iterations: 1
Working Correlation
[,1] [,2] [,3] [,4]
[1,] 1 0 0 0
[2,] 0 1 0 0
[3,] 0 0 1 0
[4,] 0 0 0 1
The estimates and the naive standard errors match the GLM exactly.
The naive SE’s are much smaller (half) than the robust (sandwich) SE’s, suggesting a poor fit.
17.5.2 Change Correlation Sturucture
- correlation structure:
exchangeable
- scale parameter = \(1\)
<- gee::gee(seizure.rate ~ base + age + treatment + offset(per),
fit_gee_exc_s1 data = data_long,
family = poisson(link = "log"),
id = subject,
corstr = "exchangeable",
scale.fix = TRUE,
scale.value = 1)
(Intercept) base age treatmentProgabide
-0.13061561 0.02265174 0.02274013 -0.15270095
summary(fit_gee_exc_s1)
GEE: GENERALIZED LINEAR MODELS FOR DEPENDENT DATA
gee S-function, version 4.13 modified 98/01/27 (1998)
Model:
Link: Logarithm
Variance to Mean Relation: Poisson
Correlation Structure: Exchangeable
Call:
gee::gee(formula = seizure.rate ~ base + age + treatment + offset(per),
id = subject, data = data_long, family = poisson(link = "log"),
corstr = "exchangeable", scale.fix = TRUE, scale.value = 1)
Summary of Residuals:
Min 1Q Median 3Q Max
-4.9195387 0.1808059 1.7073405 4.8850644 69.9658560
Coefficients:
Estimate Naive S.E. Naive z Robust S.E. Robust z
(Intercept) -0.13061561 0.2004416507 -0.6516391 0.365148155 -0.3577058
base 0.02265174 0.0007527342 30.0926122 0.001235664 18.3316325
age 0.02274013 0.0059473665 3.8235638 0.011580405 1.9636736
treatmentProgabide -0.15270095 0.0706547450 -2.1612270 0.171108915 -0.8924196
Estimated Scale Parameter: 1
Number of Iterations: 1
Working Correlation
[,1] [,2] [,3] [,4]
[1,] 1.0000000 0.3948033 0.3948033 0.3948033
[2,] 0.3948033 1.0000000 0.3948033 0.3948033
[3,] 0.3948033 0.3948033 1.0000000 0.3948033
[4,] 0.3948033 0.3948033 0.3948033 1.0000000
- Although the estimated beta parameters are not much different, the naive SE’s are some closer to the robust SE’s.
<IP_ADDRESS> Interpretation
For determining significance, no p-values are given, however the p-value will be < .05 when the z-score is > 1.96.
“For this example, the estimates of standard errors under the independence are about half of the corresponding robust estimates, and the the situation improves only a little when an exchangeable structure is fitted. Using naive standard errors leads, in particular, to a highly significant treatment effect which disappears when the robust estimates are used.”
17.5.3 Estimate the Additional Scale Parameter
“The problem with the GEE approach here, using either the independence or exchangeable correlation structure lies in constraining the scale parameter to be one. For these data there is overdispersion (variance is larger than the mean value) which has to be accommodated by allowing this parameter to be freely estimated.”
- correlation structure:
exchangeable
- scale parameter = freely estimated
<- gee::gee(seizure.rate ~ base + age + treatment + offset(per),
fit_gee_exc_sf data = data_long,
family = poisson(link = "log"),
id = subject,
corstr = "exchangeable",
scale.fix = FALSE)
(Intercept) base age treatmentProgabide
-0.13061561 0.02265174 0.02274013 -0.15270095
summary(fit_gee_exc_sf)
GEE: GENERALIZED LINEAR MODELS FOR DEPENDENT DATA
gee S-function, version 4.13 modified 98/01/27 (1998)
Model:
Link: Logarithm
Variance to Mean Relation: Poisson
Correlation Structure: Exchangeable
Call:
gee::gee(formula = seizure.rate ~ base + age + treatment + offset(per),
id = subject, data = data_long, family = poisson(link = "log"),
corstr = "exchangeable", scale.fix = FALSE)
Summary of Residuals:
Min 1Q Median 3Q Max
-4.9195387 0.1808059 1.7073405 4.8850644 69.9658560
Coefficients:
Estimate Naive S.E. Naive z Robust S.E. Robust z
(Intercept) -0.13061561 0.45219954 -0.2888451 0.365148155 -0.3577058
base 0.02265174 0.00169818 13.3388301 0.001235664 18.3316325
age 0.02274013 0.01341735 1.6948302 0.011580405 1.9636736
treatmentProgabide -0.15270095 0.15939823 -0.9579840 0.171108915 -0.8924196
Estimated Scale Parameter: 5.089608
Number of Iterations: 1
Working Correlation
[,1] [,2] [,3] [,4]
[1,] 1.0000000 0.3948033 0.3948033 0.3948033
[2,] 0.3948033 1.0000000 0.3948033 0.3948033
[3,] 0.3948033 0.3948033 1.0000000 0.3948033
[4,] 0.3948033 0.3948033 0.3948033 1.0000000
The naive SE’s are much closer inline with the robust SE’s.
The scale parameter is estimated to be much larger than \(1\).
“When this is done (scale parameter is freely estimated) it gives the last set of results shown above. THe estimate of \(\phi\) is 5.09 and the naive and robust estimates of the standard errors are now very similar.”
17.5.4 Compare Models
<IP_ADDRESS> Raw Estimates (logit scale)
::knitreg(list(fit_glm,
texreg
fit_gee_ind_s1,
fit_gee_exc_s1,
fit_gee_exc_sf),custom.model.names = c("GLM",
"GEE-Indep(1)",
"GEE-Exchg(1)",
"GEE-Exchg(free)"),
caption = "Estimates on Logit Scale",
digits = 3)
| GLM | GEE-Indep(1) | GEE-Exchg(1) | GEE-Exchg(free) | |
|---|---|---|---|---|
| (Intercept) | -0.131 | -0.131 | -0.131 | -0.131 |
| (0.136) | (0.365) | (0.365) | (0.365) | |
| base | 0.023*** | 0.023*** | 0.023*** | 0.023*** |
| (0.001) | (0.001) | (0.001) | (0.001) | |
| age | 0.023*** | 0.023* | 0.023* | 0.023* |
| (0.004) | (0.012) | (0.012) | (0.012) | |
| treatmentProgabide | -0.153** | -0.153 | -0.153 | -0.153 |
| (0.048) | (0.171) | (0.171) | (0.171) | |
| AIC | 1732.459 | |||
| BIC | 1746.314 | |||
| Log Likelihood | -862.229 | |||
| Deviance | 958.464 | |||
| Num. obs. | 236 | 236 | 236 | 236 |
| Scale | 1.000 | 1.000 | 5.090 | |
| ***p < 0.001; **p < 0.01; *p < 0.05 |
<IP_ADDRESS> Exponentiate the Estimates (odds ratio scale)
::knitreg(list(extract_glm_exp(fit_glm),
texregextract_gee_exp(fit_gee_ind_s1),
extract_gee_exp(fit_gee_exc_s1),
extract_gee_exp(fit_gee_exc_sf)),
custom.model.names = c("GLM",
"GEE-Indep(1)",
"GEE-Exchg(1)",
"GEE-Exchg(free)"),
digits = 3,
caption = "Estimates on Odds-Ratio Scale",
caption.above = TRUE,
ci.test = 1)
| GLM | GEE-Indep(1) | GEE-Exchg(1) | GEE-Exchg(free) | |
|---|---|---|---|---|
| (Intercept) | 0.878 | 0.878 | 0.878 | 0.878 |
| [0.672; 1.144] | [0.429; 1.795] | [0.429; 1.795] | [0.429; 1.795] | |
| base | 1.023* | 1.023* | 1.023* | 1.023* |
| [1.022; 1.024] | [1.020; 1.025] | [1.020; 1.025] | [1.020; 1.025] | |
| age | 1.023* | 1.023* | 1.023* | 1.023* |
| [1.015; 1.031] | [1.000; 1.046] | [1.000; 1.046] | [1.000; 1.046] | |
| treatmentProgabide | 0.858* | 0.858 | 0.858 | 0.858 |
| [0.782; 0.943] | [0.614; 1.200] | [0.614; 1.200] | [0.614; 1.200] | |
| Dispersion | 1.000 | 1.000 | 5.090 | |
| * Null hypothesis value outside the confidence interval. |


--- layout: post title: Good news, everyone! ---
Okay, but this is actually good news. I feel overwhelmingly blessed and grateful to be able to say that I'll be starting as a cohort[5] student @ Ada Developers Academy in August! Here's a rundown of my journey (warning: this goes way back) to get to this point.
I've always been fascinated by tech, but played a little dancing game on how I would break into the field.
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With marketing crossed off my list, I knew I didn't want to go to business school. Going into the University of Washington, I thought I was going to major in Psychology. It was intriguing and I liked the research elements, but the end point of being a psychologist didn't appeal to me. I switched gears to Communication since I adored rhetoric (or any type of wordplay, really), and my fascination with political rhetoric drove me to add Political Science as my second major. The manifestation of my interests could be characterized through my curiosity around the SOPA/PIPA debate - the perfect combo of tech, politics, and rhetoric. At this point, I still didn't have a career in mind. I actually wandered a bit and became interested in screenwriting, but that settled into a hobby despite looking into that career path. I graduated without a plan, which was terrifying.
I applied to so many positions. I still have the folder with all the different cover letters I wrote. Luckily, I had landed a communications internship at the City of Kirkland just prior to graduating. During that internship, I was given some creative freedom in what stories I wanted to cover. I chose TEALS, an awesome program where software engineers volunteer to teach computer science at high schools very early in the AM, then go to their regular jobs for the rest of the day. I was so psyched that this program was at the high school I went to (and secretly very jealous, they didn't have it when I was there). In reaching out to them for the story, I was put in touch with a Microsoft PR contact. I noticed she worked for Waggener Edstrom Communications (now WE Communications) and thought "her job seems cool..." In the many, many applications that I filled out post-graduation, Waggener Edstrom Communications was one of the only employers that I got to interview with. I got into their internship program and am so thankful that they gave me my big tech break.
The internship program at WE Communications is crazy good. I got to do team projects with the other interns and also rotate on a number of teams. This position was immensely helpful in building up my skills in teamwork, strategy, and overall professionalism. At the end of the internship I joined the Reactive Issues team (I was very torn between this team & Dev Comms). This is where I was introduced to the world of cybersecurity and I was hooked. I built up very, very rudimentary learnings about this world and wanted more. This is where the frustration set in, I would watch infosec lectures and nothing would stick. It felt like to know security, I would first need to know programming, and to know programming...well, I didn't even know where to start. When you're not in a school setting, the plethora of resources is overwhelming. I couldn't even wrap my head around what programming language to start with. I started taking online lecture-style courses but I still felt lost. Eventually, I decided to try out a more proactive PR role at Edelman. Spoiler alert: my interest in learning programming never went away and was like this nonstop nagging in the back of my brain.
Eventually I discovered more hands-on learning websites like Codecademy, Treehouse, The Odin Project, and Free Code Camp. This is where I actually felt like things were sticking - they allowed me the venue to try things for myself instead of just sitting back and watching a lecture. This is also where I had trouble controlling my hunger for learning. Eventually I succombed - that is, to trying to control my hunger. I quit my job and dedicated myself to online learning. I relentlessly researched my options - boot camps, post-bacc programs, online certificates, etc. I had known about Ada Developers Academy for a while (I almost applied to Cohort 5!), and after looking into all my options I knew ADA was what I wanted. I'll do a whole post on my research into ADA and the application process, because that itself was a doozy!
In putting all these thoughts down, I realized that I've always characterized my success as "luck" and happenstance. While that's a nice notion, it's really about planning and persistence. Know what you want, why you want it, and how you're going to get it. I finally feel like I'm on-track towards what I've wanted and it's because I put the effort into it. I feel excited, nervous, and blessed to be starting at Ada Developers Academy in August - but I'm cognizant of what it took to get here, both from me and the amazing organization that's provided me this opportunity. Don't take anyone (yourself/others) or anything for granted.


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--- layout: page redirect_from: - /poetry.php/ - /textbook.php/ ---
I'm Chucky Ellison. I'm a backend software engineer. I like playing with data, designing and building fast and scalable systems, and optimizing code. I'm a former academic, responsible for the first complete formal semantics of C.
I'm also currently looking for a job! Please take a look at my CV if you're hiring.


|
PX4 Firmware
PX4 Autopilot Software http://px4.io
|
#include <uORB/uORB.h>
Go to the source code of this file.
Classes | |
| struct | vehicle_status_s |
Functions | |
| ORB_DECLARE (vehicle_status) | |
| #define VEHICLE_STATUS_ARMING_STATE_ARMED 2 |
Definition at line 46 of file vehicle_status.h.
Referenced by gpio_led_cycle().
| #define VEHICLE_STATUS_ARMING_STATE_IN_AIR_RESTORE 5 |
Definition at line 49 of file vehicle_status.h.
| #define VEHICLE_STATUS_ARMING_STATE_INIT 0 |
Definition at line 44 of file vehicle_status.h.
| #define VEHICLE_STATUS_ARMING_STATE_MAX 6 |
Definition at line 50 of file vehicle_status.h.
| #define VEHICLE_STATUS_ARMING_STATE_REBOOT 4 |
Definition at line 48 of file vehicle_status.h.
| #define VEHICLE_STATUS_ARMING_STATE_STANDBY 1 |
Definition at line 45 of file vehicle_status.h.
Referenced by gpio_led_cycle().
| #define VEHICLE_STATUS_ARMING_STATE_STANDBY_ERROR 3 |
Definition at line 47 of file vehicle_status.h.
Referenced by gpio_led_cycle().
| #define VEHICLE_STATUS_HIL_STATE_OFF 0 |
Definition at line 51 of file vehicle_status.h.
| #define VEHICLE_STATUS_HIL_STATE_ON 1 |
Definition at line 52 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_ACRO 10 |
Definition at line 63 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_ALTCTL 1 |
Definition at line 54 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_FOLLOW_TARGET 19 |
Definition at line 72 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_LAND 18 |
Definition at line 71 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_LANDENGFAIL 8 |
Definition at line 61 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_LANDGPSFAIL 9 |
Definition at line 62 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_LOITER 4 |
Definition at line 57 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_MISSION 3 |
Definition at line 56 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_PRECLAND 20 |
Definition at line 73 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_RCRECOVER 6 |
Definition at line 59 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_RTGS 7 |
Definition at line 60 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_RTL 5 |
Definition at line 58 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_AUTO_TAKEOFF 17 |
Definition at line 70 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_DESCEND 12 |
Definition at line 65 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_MANUAL 0 |
Definition at line 53 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_MAX 21 |
Definition at line 74 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_OFFBOARD 14 |
Definition at line 67 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_POSCTL 2 |
Definition at line 55 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_RATTITUDE 16 |
Definition at line 69 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_STAB 15 |
Definition at line 68 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_TERMINATION 13 |
Definition at line 66 of file vehicle_status.h.
| #define VEHICLE_STATUS_NAVIGATION_STATE_UNUSED 11 |
Definition at line 64 of file vehicle_status.h.
| #define VEHICLE_STATUS_RC_IN_MODE_DEFAULT 0 |
Definition at line 75 of file vehicle_status.h.
| #define VEHICLE_STATUS_RC_IN_MODE_GENERATED 2 |
Definition at line 77 of file vehicle_status.h.
| #define VEHICLE_STATUS_RC_IN_MODE_OFF 1 |
Definition at line 76 of file vehicle_status.h.
| ORB_DECLARE | ( | vehicle_status | ) |


class ChangeUserActivity : AppCompatActivity
A screen changing user information |
|
class LoginActivity : AppCompatActivity
A login screen that offers login via email/password. |
|
class RegistrationActivity : AppCompatActivity
A screen registration |
|
class UserSettingsActivity : AppCompatActivity, OnNavigationItemSelectedListener
A screen user settings |
|
class UserViewActivity : AppCompatActivity
A screen information about user |


College of Natural Resources (CNR)
-
Advising Office: 260 Mulford Hall
-
Website:
cnr.berkeley.edu
-
Unit minimum per semester (w/case-by-case exceptions): 13 units
-
All major requirements must be taken for a letter grade
-
Semester Limit, No Unit Limit
-
Started Cal as a Freshmen = 8 semesters
-
Started Cal as a Transfer = 4 semesters
-
AP and IB high school exams can complete requirements
-
No Foreign Language or Quantitative Reasoning requirement, except Environmental Economics and Policy majors
College of Environmental Design (CED)
-
Advising Office: 250 Wurster Hall
-
Website:
http://ced.berkeley.edu/ced/students/undergraduate-advising/
-
Unit minimum per semester (w/case-by-case exceptions): 12 units
-
Semester Limit, No Unit Limit
-
Started Cal as a Freshmen = 8 semesters
-
Started Cal as a Transfer = 4 semesters
-
Exception may be requested with revised graduation plan
-
Graduation plan for each major can be found in Major Handbook online:
-
ced.berkeley.edu/advising/forms
-
Curriculum is fairly fixed, especially junior and senior year
-
Best to take Environmental Design 1 (ED 1) first semester.
-
New major in Sustainable Environmental Design is impacted. No guarantee of changing in after admission to UCB. Talk with SED major advisor.
-
AP, IB, GCE and A-Level high school exams can complete requirements
-
Most required courses must be taken for letter grade. See advisor if considering P/NP
-
Only one breadth course may be taken P/NP
-
No College-level language or quantitative breadth requirement. However, Arch, SED, and US majors do require calculus and/or stat (check major handbooks)
College of Chemistry (COC)
-
Advising Office: 121 Gilman Hall
-
Website:
chemistry.berkeley.edu
-
Unit minimum per semester (w/case-by-case exceptions): 13 units
-
Each semester: 12 units must satisfy major requirements - math, science, breadth electives (including R&C + AC)
-
All technical courses must be taken for letter grade (chemistry, math, physics courses)
-
AP, IB, and A-Level exams can complete requirements
College of Engineering (COE)
-
Advising Office: 230 Bechtel Hall
-
Center for Access to Engineering Excellence: 227 Bechtel Hall
-
Tutoring for most lower division courses
-
Website:
coe.berkeley.edu/ess
-
Students make appointments on this site
-
Unit minimum per semester (w/case-by-case exceptions): 12 units
-
Each semester: at least two technical courses required of the major
-
All technical courses must be taken for letter grade
-
Technical = math, science, engineering courses
-
Semester-by-semester plan for each major: coe.berkeley.edu/guide
-
Change of college information: coe.berkeley.edu/coc
-
Engineering 92, 1 unit P/NP, no work involved other than attendance
-
Course is open to anyone and helps explore engineering fields
College of Letters and Science (L&S)
-
Advising Office: 206 Evans Hall
-
Website:
ls-advise.berkeley.edu
-
Unit minimum per semester (w/case-by-case exceptions): 13 units
-
Up to 1/3 of UC Berkeley units can be taken P/NP


text shadows are cool
I'm so
COOL!
These text fields look like buttons, right?
We are not buttons :)
We are not buttons :)


John Pilling
, Volume 18, Number 4, November 2011, p. 881 (Article)
Published by The Johns Hopkins University Press
DOI: 10.1353/mod.2011.0113
For additional information about this article
http://muse.jhu.edu/journals/mod/summary/v018/18.4.pilling01.html
Access Provided by The University Of Texas at Austin, General Libraries at 07/05/12 8:00PM GMT
In November 1930, shortly after Beckett returned from two years as exchange lecteur at the ENS in Paris to take up a teaching post at his alma mater Trinity College, Dublin, he gave an address in French to the Modern Languages Society in the form of a spoof lecture, which seems to have much amused the academic community.1 Much of the material, though, especially those portions of it which obliquely show Beckett struggling with his own demons, must have passed over most of their heads.
These translated extracts were published by the Menard Press as MenCards no. 93 and no. 118, in 1986 and 1990 respectively. They were undertaken on behalf of Antony Rudolf, who wished to mark, in the case of the first, the eightieth birthday of Samuel Beckett, whom he greatly admired, and, in the case of the second, to mark the twenty-first birthday of Antony’s Menard Press, which is still going strong, and is now twice as old as it was in 1990. Thanks are due to Antony for permission to reprint these, to Edward Beckett, Rosica Colin Ltd., and Faber and Faber for waiving fees for them, and to Dr. Peter Fifield for thinking them worth giving a more general airing. A portion of one of them is quoted in James Knowlson’s Damned to Fame: the life of Samuel Beckett (Bloomsbury, 1996). There is as yet no complete translation of the lecture published with the agreement of the Estate of Samuel Beckett, which holds all the appropriate copyrights.
1. See Beckett’s letter to Thomas McGreevy of 14 November, 1930. Samuel Beckett, The Letters of Samuel Beckett, vol. 1, 1929–1940, ed. Martha Fehsenfeld and Lois More Overbeck (New York: Cambridge University Press, 2009), 55 (hereafter cited in text as L, 1).
modernism / modernity volume eighteen, number four, pp 881. © 2012
the johns hopkins university press


WITNESS LIST State, Federal & International Relations Committee April 17, 2001-8:00A HCR 241 Registering, but not testifying: For: Gutierrez, Jr., Hector (City of El Paso) Kastrin, Deborah (County of El Paso) SB 911 For: Davis, Ed (City of San Antonio) SB 1140 On: James, Daniel (Adjutant General's Department) SB 1165 On: James, Daniel (Adjutant General's Department)


COurse RegIstry stAtistics aNd aDditional matERial
Explore the courses by keywords, countries and years. Below the plot a list with courses matching the current selection is displayed. By clicking on one of that courses further information and additional literature from a Zotero bibliography and Wikidata is displayed. Click on Keywords for a visualisation of relationships. To know more go to GitHub for the full README.
Selected year:


{% extends 'base.html' %} {% block title %} Home Page {% endblock title %} {% block homeactive %} active {% endblock homeactive %} {% block body %}
This is a simple hero unit, a simple jumbotron-style component for calling extra attention to featured content or information.
It uses utility classes for typography and spacing to space content out within the larger container.
This is a wider card with supporting text below as a natural lead-in to additional content.


| Name | Description |
|---|---|
| Bike.Number == ( other ) |
Determines if this number is equal to the specified number.
Parameters other Type: Bike.Number The number to be compared. Return Value Type: Bike.Boolean True if this number is equal to the supplied number. |
| Bike.Number.hash_code() |
Gets the hash code of this number.
Return Value Type: Bike.Number The hash code of this number. |
| Bike.Number.to_string() |
Gets the string representation of this number.
Return Value Type: Bike.String The string representation of this number. |
| Bike.Number.compare_to( other ) |
Compares this number with the provided number.
Parameters other Type: Bike.Number The number to compare to. Return Value Type: Bike.Number 1 if this number comes before other; 0 if this number is equal to other; -1 if this number comes after other. |
| Bike.Number.times( fn ) |
Executes a function for a number of times specified by this number.
Parameters fn Type: Bike.Function The function to be executed. This function could accept a number denoting the current execution time, starting from 0. |
| Bike.Number.upto( to, fn ) |
Executes a function for as many times as this number proceeds to to, exclusively.
Parameters to Type: Bike.Number Determines how many times the function is executed. fn Type: Bike.Function The function to be executed. This function could accept a number denoting the current execution time, starting with this number up to to-1. |
| Bike.Number.downto( to, fn ) |
Executes a function for as many times as this number descends to to, exclusively.
Parameters to Type: Bike.Number Determines how many times the function is executed. fn Type: Bike.Function The function to be executed. This function could accept a number denoting the current execution time, starting with this number down to to-1. |
| Bike.Number.ceil() |
Returns the ceiling of this number.
Return Value Type: Bike.Number The ceiling of this number. |
| Bike.Number.floor() |
Returns the floor of this number.
Return Value Type: Bike.Number The floor of this number. |
| Bike.Number.round( places ) |
Returns the round of this number.
Parameters places Type: Bike.Number The number of decimal places to reserve. If not specified, no decimal place is reserved. Return Value Type: Bike.Number The round of this number. |
| Bike.Number.whole() |
Determines if this number is a whole number.
Return Value Type: Bike.Boolean True if this number is a whole number. |
| Bike.Number.truncate() |
Returns the whole part of this number.
Return Value Type: Bike.Number The whole part of this number. |
| Bike.Number.odd() |
Determines if this number is an odd number.
Return Value Type: Bike.Boolean True if this number is an odd number. |
| Bike.Number.even() |
Determines if this number is an even number.
Return Value Type: Bike.Boolean True if this number is an even number. |


Details
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ace.com
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Username
alexdoe
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Netherlands, Amsterdam
Age
38
Joined
2010/06/20
Last Online
3 hours ago
About Me
Bio
Send a message to Alex
Email me a copy
Submit


---
layout: default
disqus: false
archive: false
post_class: post-template
---
{% include app_banner.html title="I'm Building Taskito" description="Taskito offers simple and intuitive tools to organize your daily tasks. It combines features of project management software with productivity and time management tools. Try it out now!" url="https://play.google.com/store/apps/details?id=com.fenchtose.reflog&utm_source=personal_website_post&pcampaignid=MKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1" image_small="/assets/images/taskito_website_logo.png" %}
{{content}}
{%- assign next_post = false %}
{%- for post in site.posts reversed %}
{%- if next_post and post.category == "Series" and post.category != "Project" and post.category != "privacy-policy" %}
{% include read_next_card.html post=post %}
{%- assign next_post = false %}
{%- break %}
{%- endif %}
{%- if post.url == page.url %}
{%- assign next_post = true %}
{%- endif %}
{%- endfor %}


German exports to US jump in Q3 despite trade tensions - Reuters
by Dhwani MehtaThe latest data compiled for Reuters from the Federal Statistics Office showed on Thursday, the German exports to the US jumped in the third quarter of 2019, which partly helped the Euro area’s economic powerhouse to avoid a recession.
Key Details:
“German exports to the U.S. jumped by 7.6% year-on-year from July through September after a 5.3% increase in the previous three months.
The detailed trade figures underline that U.S. demand for German goods remain strong, undaunted by President Donald Trump's 'America First' campaign and his threats to increase import tariffs on European cars.
Exports to France rose by 3.1% year-on-year in the third quarter while sales to China nearly stagnated.”
Meanwhile, EUR/USD is seen holding the renewed upside near 1.1085 amid broad-based US dollar weakness and mixed US-China headlines. Focus now remains on the ECB minutes due later today at 1230 GMT.


时钟
| Student ID | Name | Sex | Selected Subjects |
|---|---|---|---|
| {{ acl.id }} | {{ acl.name }} | Male Female | {{ acl.select }} |
{
{
}
}
to quote variables，`me` means
me and `you` means you | Variables | Meanings |
|---|---|
| Sex | Sex：0 means male，1 means female |
| Name | Student's Name |
| Class | Class |
| Select | Selected Subjects |
| Id | Student ID |


| I l@ve RuBoard |
3.3 The Queue ModuleThe Queue module provides a thread-safe queue implementation, shown in Example 3-2. It provides a convenient way of moving Python objects between different threads. Example 3-2. Using the Queue ModuleFile: queue-example-1.py import threading import Queue import time, random WORKERS = 2 class Worker(threading.Thread): def _ _init_ _(self, queue): self._ _queue = queue threading.Thread._ _init_ _(self) def run(self): while 1: item = self._ _queue.get() if item is None: break # reached end of queue # pretend we're doing something that takes 10—100 ms time.sleep(random.randint(10, 100) / 1000.0) print "task", item, "finished" # # try it queue = Queue.Queue(0) for i in range(WORKERS): Worker(queue).start() # start a worker for i in range(10): queue.put(i) for i in range(WORKERS): queue.put(None) # add end-of-queue markers task 1 finished task 0 finished task 3 finished task 2 finished task 4 finished task 5 finished task 7 finished task 6 finished task 9 finished task 8 finished Example 3-3 shows how you can limit the size of the queue. If the producer threads fill the queue, they will block until items are popped off the queue. Example 3-3. Using the Queue Module with a Maximum SizeFile: queue-example-2.py import threading import Queue import time, random WORKERS = 2 class Worker(threading.Thread): def _ _init_ _(self, queue): self._ _queue = queue threading.Thread._ _init_ _(self) def run(self): while 1: item = self._ _queue.get() if item is None: break # reached end of queue # pretend we're doing something that takes 10—100 ms time.sleep(random.randint(10, 100) / 1000.0) print "task", item, "finished" # # run with limited queue queue = Queue.Queue(3) for i in range(WORKERS): Worker(queue).start() # start a worker for item in range(10): print "push", item queue.put(item) for i in range(WORKERS): queue.put(None) # add end-of-queue markers push 0 push 1 push 2 push 3 push 4 push 5 task 0 finished push 6 task 1 finished push 7 task 2 finished push 8 task 3 finished push 9 task 4 finished task 6 finished task 5 finished task 7 finished task 9 finished task 8 finished You can modify the behavior through subclassing. The class in Example 3-4 provides a simple priority queue. It expects all items added to the queue to be tuples, where the first member contains the priority (lower value means higher priority). Example 3-4. Using the Queue Module to Implement a Priority QueueFile: queue-example-3.py import Queue import bisect Empty = Queue.Empty class PriorityQueue(Queue.Queue): "Thread-safe priority queue" def _put(self, item): # insert in order bisect.insort(self.queue, item) # # try it queue = PriorityQueue(0) # add items out of order queue.put((20, "second")) queue.put((10, "first")) queue.put((30, "third")) # print queue contents try: while 1: print queue.get_nowait() except Empty: pass third second first Example 3-5 shows a simple stack implementation (last-in, first-out, instead of first-in, first-out). Example 3-5. Using the Queue Module to Implement a StackFile: queue-example-4.py import Queue Empty = Queue.Empty class Stack(Queue.Queue): "Thread-safe stack" def _put(self, item): # insert at the beginning of queue, not at the end self.queue.insert(0, item) # method aliases push = Queue.Queue.put pop = Queue.Queue.get pop_nowait = Queue.Queue.get_nowait # # try it stack = Stack(0) # push items on stack stack.push("first") stack.push("second") stack.push("third") # print stack contents try: while 1: print stack.pop_nowait() except Empty: pass third second first |
| I l@ve RuBoard |


Chuta Kaimu:
My hero, my master!
Should my spirit ever return here, gather my shattered body and sing to me the warrior song of old.
As the letters on the Pillar of Wisdom are reorganized, you hear a stirring, almost sad melody.


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Guidance
Types of apprenticeships that you can apply for in the combined manufacturing processes sector.
This apprenticeship deals with a major section of the UK paper making industry, which is among one of the most forward-thinking industries in the areas of recycling, energy conservation and the environment.
As an intermediate level apprentice you could be working in a paper mill or a recovery plant making paper or corrugated board and tissue from wood pulp and recycled materials. On this apprenticeship you’ll learn:
The advanced apprenticeship has 2 routes of specialisation:
You might also learn some engineering skills and carry out maintenance on machines, or learn how to effectively respond to any problems that may come up - and keep production processes going.
There are 2 types of combined manufacturing processes apprenticeships.
You could train in roles like:
You could train in roles like:
You can become an apprentice in England if you’re:
Published: 12 April 2012


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very low
low
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First ACM/USENIX Conference on Virtual Execution Environments (VEE'05)
Chicago, Illinois June 11-12, 2005,
Sponsored by ACM SIGPLAN and USENIX, in cooperation with ACM SIGOPS, held in conjunction with PLDI 2005
Supporting Organizations:
www.veeconference.org
Slides from the invited talks are available.
program


--- status: "ready" title: "Promo - bleed image text right" text: "Promotion of featured content - suitable for use with banner type images" ---
A relaxed lifestyle. Friendly people. Spectacular scenery. Find out what makes Australia one of the best places in the world to live and study.


Name: Timothy Munene
Below is a list of the projects I have completed:
A website about my favorite pet.
This webpage is written in HTML exclusively.
Link: click here👊
This page is for a travel agency, Happy Trails Travel Agency.
Languages used:
You can find the source code of this web page on this link.
Some of my educational qualifications:
I decided to take programming classes because I developed interest in coding but wasn't motivated then as I am now! Programming is a beautiful skill to have
I am learning a lot already and I am grateful for the opportunity.
My current interests include:


Hello, my name is Jaime Coan. I’m a 21 year old graphic design student living in Vancouver. I am currently in my third year of Graphic Design for Marketing. My passion is all about creating awesome illustrations and packaging design. Always keeping it fresh and clean. If you would like to connect with me then be sure to find me on Facebook, Instagram and Behance.
Challenge: Create a brand name, design a brand mark, and design comprehensive mock-ups for a line of consumer products.Approach: ost Bear is a camping supply company based out of Vancouver that provides snacks and camping supplies, which can be sold as individual items as well as kits. The primary target audience for these items are both men and women ages 18-60 who live in Vancouver and are active and/ or outdoor enthusiasts. The main objective is to create awareness and interest in Lost Bear by setting it apart from the competition and become the number one choice for camping supplies.
Challenge: Create a brand name, design a brand mark, and present comprehensive mock-ups of sample packaging designs for a range of retail products as well as considering point-of-purchase displays. Approach: Draw or Die is a new stationery company that provides various back to school basics like notebooks, pencil cases, pencil holders, rulers, pencils and erasers. Draw or Die is selling supplies in stores such as Wal-Mart, Staples, Michaels, Skate shops and online. The primary target audience is boys and girls ages 12+ who live in Vancouver. The main objective is to create awareness and interest about Draw or Die by setting it apart from the competition and make it the number one choice for school supplies.
EMAIL<EMAIL_ADDRESS>PHONE:<PHONE_NUMBER>


Thanks for coming to Family Friday lunch!
May 26, 2017 at 12:00 PM
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Hi Jill! As an important part of the engineering team, we want to make sure our lunches are meeting your expectations. Help us choose better restaurants by giving us some feedback! Let us know how many stars you'd rate your last lunch. Feel free to review Pizza R Us on their Yelp page Best, The Lunch Crew
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As I wrote some time ago, I started my own python cookbook for Chef because I didn't like the direction the "default" one was going.
I recently added a new feature that I wanted to talk about. I called it smart_install
in the cookbook, but it's actually a "dry-run" mode for pip install
Motivation
When installing a Pip package using Chef, I have the "install" command, which is something like pip install PACKAGENAME
. After I do so, I consider the resource "updated" (as in, its state has changed), which means it'll notify any resoures subscribed to it (e.g. restarting a service after a package is upgraded).
I have 3 constraints:
- The
install
action of the Pip resource should look like it ranpip install
every time. In other words, ifpip install
would do something, it should run. - The
install
action shouldn't notify other resources that subscribed to it ifpip install
would have done nothing (e.g. if package is installed at the right version). - The
install
action should notify other resources that subscribed to it ifpip install
would have done something (e.g. installed a package if it's missing).
I saw 2 options to solve my constraints:
- Run
pip install
every time, and parse its output to determine whether it did something or not. - Mark the resource as updated whenever I run
pip install
, and use something beforehand to determine whether runningpip install
is even needed (as in, would it do something).
Option 1 seemed too unreliable for me as it involved parsing a pretty verbose output that could change greatly between Pip versions, and might also include custom output (from installed packages' code), so I had to go for option 2.
Initial implementation
The first implementation, which currently stays as a fallback to "smart install", is taken primarily from the original Python cookbook.
It involves running pip list
and parsing its output to see which version is installed now, if any:
# https://github.com/BackSlasher/chef-backslasher-python/blob/5de6e03/providers/pip.rb#L51
my_line = pip_command('list').stdout.lines.map{|line| pattern.match(line)}.compact.first
This information is joined with what little info we have about the package we're about to install (e.g. do we have a manually set version) and our intended action (install/upgrade) to decide whether to run pip install
.
My primary issue with it is that it didn't work when installing from a URL / complex requirement line (e.g. requests>=2
), and enriching it to work with these meant a lot of complexity (like downloading the package at the provided URL, extracting it and parsing its version) that I wasn't going to implement.
Smart install
To handle more complicated cases, I've decided to create a Python script that uses Pip's libraries to decide whether pip install
would do something.
At first, I copied a lot of logic from pip.commands.install
and pip.req
to fill a to_install
array (the name given in the Pip code to a collection of "requirements" to be installed), and then check whether this array has anything in it.
Problem was, some method headers differ between my tested Pip versions, so I decided to avoid using that script because it might break pretty easily, in addition to it being pretty bulky.
 I decided to patch the "install" method on the RequirementSet
object (used to represent a collection of needed packages) to add them all to my own array. I'm then checking whether this array is empty or not, and printing the result.
The script looks like this:
# https://github.com/BackSlasher/chef-backslasher-python/blob/90631c3/files/default/smart_install.py
from pip.req import RequirementSet
to_install=[]
def my_install(self, install_options, global_options=(), *args, **kwargs):
global to_install
to_install.extend([r for r in self.requirements.values() if not r.satisfied_by])
RequirementSet.install = my_install
import pip
import sys
args = sys.argv[1:]
if '-q' not in args: args.append('-q') # keep it quiet
pip.main(args)
#print 'to_install is',[r.name for r in to_install]
print any(to_install)
Interesting points:
- The script is invoked just like Pip would, i.e.
python /tmp/smart_install.py install requests>=2
- I'm forcing
-q
or "quiet" mode to avoid littering STDOUT with Pip's usual chatter. - A non-0 exit code means failure to run. Whether anything is to be installed is determined by the script returning
True
/False
.
Conclusion
I'm not sure the script is fit for every use-case, so it's disabled by default. I'm especially afraid of it actually doing something (and not tellng Chef that it did).
I would like to integrate it into Pip some day as --dry-run
(thinking big). I still haven't decided how it will behave in the way of output - I'm not big on changing the exit code on one hand, and afraid of my meaningful output drowning in Pip's output.
As usual, any comments are welcome!


|
Class Summary |
| DateParser |
Deprecated. Use DateUtil |
| DateUtil |
A utility class for parsing and formatting HTTP dates as used in cookies and
other headers. |
| EncodingUtil |
The home for utility methods that handle various encoding tasks. |
| ExceptionUtil |
The home for utility methods that handle various exception-related tasks. |
| HttpURLConnection |
Provides a HttpURLConnection wrapper around HttpClient's
HttpMethod . |
| IdleConnectionHandler |
A helper class for connection managers to track idle connections. |
| IdleConnectionTimeoutThread |
A utility class for periodically closing idle connections. |
| LangUtils |
A set of utility methods to help produce consistent Object#equals(Object) and
Object#hashCode methods. |
| ParameterFormatter |
This formatter produces a textual representation of attribute/value pairs. |
| ParameterParser |
A simple parser intended to parse sequences of name/value pairs. |
| TimeoutController |
Executes a task with a specified timeout. |
| URIUtil |
The URI escape and character encoding and decoding utility. |
| URIUtil.Coder |
Deprecated. use org.apache.commons.codec.net.URLCodec |
Provides some utility classes for use by HttpClient.


Compare the elements in a tournament fashion by splitting the elements in pairs and comparing each pair and then proceeding to compare the winners. In this way, the problem is reduced to size and only one element is left in the end.
There will be n-1 matches and one winner will be selected and second smallest element is one of the lgn elements and this element is lost to the smallest such that it is smaller than the ones it has been compared to. Thus, – 1 comparisons can be used to find the smallest element.
The total number of comparisons are .
Optimal number of comparisons required to find the maximum and minimum of n numbers in the worst-case scenario:
Step 1: Set initial values for the minimum and maximum.
i. If n is odd, minimum and maximum are set to the value of the first element.
ii. If n is even, compare the first 2 elements and assign the smaller element to minimum and larger element to maximum.
Step 2: Process elements in pairs.
i. Compare pairs of elements from the input with each other.
ii. Compare the smaller to the current minimum.
iii. Compare the larger to the current maximum.
The processing of elements is done in pairs. Therefore , pairs are processed.
To process each pair of elements, 3 comparisons are required as described in step 2.
Hence, comparisons are required.
If n is odd, comparisons are performed.
If n is even, one initial comparison is done to set initial value for maximum and minimum and comparison are performed for the remaining pairs.
Thus, the total number of comparisons performed when n is even can be known by adding 1 to as shown below:
Hence, number of comparisons when n is odd is and number of comparisons when n is even is.
In the worst case scenario, consider the upper bound to calculate the total number of comparisons.
Hence, comparisons are necessary to find both the minimum and the maximum of n numbers.


RT @beanieboi: super awesome #lightningtalk on how to draw sketch notes by @malweene #baruco
9/12/2014, 8:13:32 AM
Favs: 0
Retweets: 0
link--- layout: tweet ---
RT @beanieboi: super awesome #lightningtalk on how to draw sketch notes by @malweene #baruco
9/12/2014, 8:13:32 AM
Favs: 0
Retweets: 0
link


The idea of creating a brand for a wedding was exciting and challenging — I wanted to be able to create enough pieces to create not only a consistent theme around botanicals, but a coherent style that was specific and recognizable throughout the mailer, website, and any other material. I incorportated various botanical watercolour graphics in different ways with each piece in an effort to avoid repetition and keep the theme feeling fresh and new with each piece of work. Included in this mock up is a logo design for the couple, a save the date card and envelope, accommodation information, RSVP information, and a menu. However this design could reach to other elements such as table cards and thank you notes.
The website acts as a landing spot for easy access to any information for a guest if they don't have their wedding mailer readily available. The website also has an online RSVP option for those who choose to opt out of a physical invitation for whatever reason. Additionally, there is a link to the wedding registry, information about the where and when of the wedding, the day's itinerary, and information about the couple available as well.


About me
I graduated from psychology and social work at Masaryk University. During my studies I absolved internship
in
England, where I improved my english language. And polish :)
I worked in language school as an english and spanish lecturer.Than I worked in kindergarden as an english
teacher.Currently I´m on maternity leave.
During the last year (2019) I got the information about Czechitas and I participated at some workshops.I was
so
excited about Czechitas curriculum, whole atmosphere and whole concept that I thought that even I can study
IT.
I like not only the content of the IT job, the fact that I can use english, creativity, and logical thinking
but also the time and financial freedom.
I love children, foreign languages, traveling, spending time with friends, meeting new people and exploring
new
posibilities.
Work experience
1/2017 - 4/2018 English lecturer in kindergarden
Pedagogical and educational activities with children (3 - 6 years old)in English.
Children school Safirka Pavlovská 576/16, Brno;
4/2015 - 11/2015 English and spanish lecturer
Teaching of English and Spanish language.
Language school, Perfect world Pilsen, Vondrouskova 1;
1/2015 - 3/2015 Teacher - assistant
Pedagogical and educational activities with children (3 - 6 years old).
60th children school Manetinska Pilsen, Manetinska 1617;
9/2012 - 6/2014 Personal assistant: live - in
Assistance for spinal cord injury clients, occasional assignments
Active Assistance Sevenoaks, 1 Suffolk Way;
Education
9/2010 - 1/2015 Masaryk University - Faculty of social studies
Psychology and social work
final state: bachelor degree
Masarykova univerzita, Fakulta sociálních studií, Joštova 10, 602 00 Brno;
9/2002 - 6/2010 High school
general studies
final state: graduation degree
Gymnázium, Studentská 11/1198, 73601 Havířov;


DatePicker Dropdown
January
February
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April
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Test IE6 iframe shim


Explosion at Italian fireworks factory kills 5
by The Associated PressROME — Italian rescue services say a blast at a fireworks factory in Sicily has killed five people and seriously injured two others.
Italian firefighters and Carabinieri police said that the 71-year-old wife of the owner of the family-run factory in the Sicilian town of Barcellona Pozzo di Gotto was among the victims. The owner’s son was hospitalized in serious condition.
Police say workers at the depot may have accidentally set off the explosion with welding equipment.
Safety at fireworks depots has been long debated in Italy, where the production of fireworks is often a family-run business.
Consumers association Codacons says 68 people have been killed in explosions at fireworks firms since 2000.
The Associated Press


All Things in Murderation is a detailed Murder mystery game where your choices affect the story and give the story the ability to "branch" off to get different outcomes. Choose wisely, your choices may get someone killed!
As a bright young detective, in the midst of a snow storm you somehow stumble upon a chalet. You embark on an adventure of mystery, lies, and of course murder...
A dazzling young magician who regrets her life choices, most of all her career choices.
The Chalet's resident chef. Mostly keeps to herself and is generally quiet. Is currently trying a new recipe for chocolate...
Owner of the mighty succesful Herrington Chocolate Company, Reid can be quite abnoxious at times.
An excentric old billionare who happens to own the chalet!
A bounty hunter and debt collector...you dont want to mess with her...
A professor and scientist who currently has tenure at Yale.
The esteemed daughter of Willem Van Der Berg... She happens to be married to Brennan O'Shea...
Being a small town hick but yet a millionare Buck Denim is not the brightest apple in the bunch...but he is rich.
Of Irish decent, the husband of Margaret Van Der Berg... he also happens owns a pub...and a dinking problem (who woulda thought?)
A very mysterious looking man...nothing is really known of this person...


| First name |
[[${employee.firstName}]]
|
| Last name |
[[${employee.lastName}]]
|
| E-mail |
[[${employee.email}]]
|
| Phone number |
[[${employee.phoneNumber}]]
|
| Hire date |
[[${#dates.format(employee.hireDate, 'yyyy-MM-dd')}]]
|
| salary |
[[${employee.salary}]]
|
| Commission % |
[[${employee.commissionPct}]]
|
| Manager id |
[[${employee.manager?.id}]]
|
| Manager first name |
[[${employee.manager?.firstName}]] |
| Manager last name |
[[${employee.manager?.lastName}]] |
| Manager email |
[[${employee.manager?.email}]] |
| Manager phone number |
[[${employee.manager?.phoneNumber}]] |
| Department id |
[[${employee.department?.id}]]
|
| Department name |
[[${employee.department?.departmentName}]] |


\thanks{text}
The \thanks command produces a footnote to the title.
It is typically used as part of the argument of a \title or \author command.
For example
\title{Work in Progress \thanks{Contribution No. 1 from our lab}} \author{A. Author\thanks{Supported by a grant}}
See also Page Styles,
\maketitle.
Go to LaTeX Table of Contents


Rules of P.Pig.Dice
- Write your names on the input form then touch start button
- Both participants can roll the dice 6times
- When you roll the dice and it falls on one then you lose and no points will be counted
- When you roll the dice the points will count on the count box when you press End button to switch to your partner
Rolled Dice
possible points *
0


--- layout: home --- {% assign total_talks = 0 %} {% for conference in site.data.conferences %} {% assign total_talks = total_talks | plus: site.data[conference.id].size %} {% endfor %}
Stats
Conferences quick links


MFM shocks Rangers, Lobi pips Pillars - The Nation Newspaper
Taofeek Babalola
MOUNTAIN of Fire and Miracle Ministries (MFM) FC of Lagos recorded its second away win yesterday following a 1-0 win over Rangers International FC in the match day three of the Nigeria Professional Football League (NPFL) at the Nnamdi Azikwe Stadium, Enugu.
Chuks Kenedinum 45th minute goal was all the Olukoya Boys needed to secure three points against the former league champions. MFM got its first away win in the league opener against Heartland FC in Owerri.
It was the same scenario at the Sani Abacha Stadium in Kano as the visiting Lobi Stars FC of Makurdi defeated Kano Pillars 1-0. The Pride of Benue scored the only goal through Douglas Achiv’s 62th minute goal.
Also, Enyimba FC defeated Akwa United 3-1 at the Aba International Stadium. All the four goals were scored in the first half of the encounter. Austin Oladapo shot the home side into the lead in the 13th minute from the spot before Stanley Dimgba and Samson Obi scored in the 30th and 33rd minute respectively.


Reconnecting..
AssetRails Routes
temp/AssetRailsLog.txt
UnityEditor.log
cannot run jenkins job
import
no report.
prefabricate
no report.
bundlize
no report.
versioning
no report.
logs


Server information
URL:
Versions
Client Version:
Loading...
Server Version:
Loading...
EO Data Discovery
Number of supported collections:
Loading...
Process Discovery
Number of supported processes:
Loading...


{% extends "base.html" %} {% block content %}
Enter a blockchain node URL and click on "View Votes" button to check all votes


Detail the Process for measuring Speaker Demographics.
Provide the link for the page related to Speaker Demographics if available.
Criteria:
Measuring demographics - The Event has a process for measuring speaker demographics.
Displaying demographics - The Event displays speaker demographics.
Detail the process for measuring Attendee Demographics.
Provide the link for the page related to Attendee Demographics if available.
Criteria:
Measuring Demographics - The Event has a process for measuring Attendee demographics.
Displaying demographics - The Event displays attendee demographics.
Attendee Inclusivity - The Event requests feedback from attendees regarding Diversity & Inclusion.
Is the code of conduct posted at Event venue?
Provide the link for the Event Code of Conduct.
Criteria:
Findability - It is possible to find the Code of Conduct on the Event website.
Clarity - Event Code of Conduct provides a definition of expected behaviour.
Reporting venue - The event has a venue for reporting violations of the CoC at the event website.
Support at Event - The Event Code of Conduct provided information about possible methods to provide support to victims of inappropriate behavior.
Enforcement - The participants in the Event are required to accept the Code of Conduct.
How many different types of diversity access tickets are available for the event?
What are the criteria for qualifying for a diversity access ticket?
Provide a link to the page containing information about Diversity Access Tickets.
Criteria:
Availability - The event provides one or more Diversity Access Tickets.
Ticket allocation - The Event has a process for allocating diversity access tickets.
Findability - The information about Diversity Access Tickets is public.
Does the Event provide childcare facilities for its attendees and speakers?
What are the other ways that a family-friendly environment is being created in the Event?
Provide relevant links related to family friendliness at the Event.
Criteria:
Availability - The Event provides one or more services/facilities for families.
Findability - The information about the family friendly services provided at the Event is easy to find on the website.
Once you click "submit", you must use your GitHub account to finalize the issue on their Website by clicking "Create New Issue".
Detail the Process for measuring Speaker Demographics.
Provide the link for the page related to Speaker Demographics if available.
Criteria:
Measuring demographics - The Event has a process for measuring speaker demographics.
Displaying demographics - The Event displays speaker demographics.
Detail the process for measuring Attendee Demographics.
Provide the link for the page related to Attendee Demographics if available.
Criteria:
Measuring Demographics - The Event has a process for measuring Attendee demographics.
Displaying demographics - The Event displays attendee demographics.
Attendee Inclusivity - The Event requests feedback from attendees regarding Diversity & Inclusion.
Is the code of conduct posted at Event venue?
Provide the link for the Event Code of Conduct.
Criteria:
Findability - It is possible to find the Code of Conduct on the Event website.
Clarity - Event Code of Conduct provides a definition of expected behaviour.
Reporting venue - The event has a venue for reporting violations of the CoC at the event website.
Support at Event - The Event Code of Conduct provided information about possible methods to provide support to victims of inappropriate behavior.
Enforcement - The participants in the Event are required to accept the Code of Conduct.
How many different types of diversity access tickets are available for the event?
What are the criteria for qualifying for a diversity access ticket?
Provide a link to the page containing information about Diversity Access Tickets.
Criteria:
Availability - The event provides one or more Diversity Access Tickets.
Ticket allocation - The Event has a process for allocating diversity access tickets.
Findability - The information about Diversity Access Tickets is public.
Once you click "submit", you must use your GitHub account to finalize the issue on their Website by clicking "Create New Issue".


Shillien Knights
are the faithful pick of the Dark Elves.
Description of the Shillien Knight
Change occupations to a Shillien Knight.
Return


Home
Credits
About
S2Scart
Home Page
~ Welcome to demo of Easy Counter ~
Visitor Count : {{ request.visitors }}


Academic Programs
The Black in AI Academic program is committed to serving as a resource and supporting Black junior researchers as they apply to graduate programs, navigate graduate school, and enter the postgraduate job market. To that end, we conduct online information sessions, provide scholarships to cover costs related to applications, assign participants to peer and senior mentors, and share crowdsourced documents that demystify application processes.
In addition to these efforts, we conduct research studies to explore and expose the barriers that affect Black junior researchers, and advocate for structural changes to remove these barriers and foster equitable research environments.
Our program is presently designed to cover three areas of graduate education:
- Graduate application mentoring program: to support Black students seeking admission into masters and Ph.D. programs around the world. This program currently serves over 200 Black applicants in this application cycle.
- Graduate school mentoring: to offer guidance, mentorship, and resources for current graduate students.
- Postgraduate application network: to empower soon-to-be or recent Black Ph.D. students seeking postdoctoral, faculty, and research scientist positions. This program is currently serving over 100 Black applicants during this application cycle.
Since 2017, the graduate application mentoring program has served over 400 students overall, with the support of nearly 100 mentors.
Participants in this program have enrolled at universities including the Australian National University, University of California - Berkeley, University of British Columbia, University of Capetown, Carnegie Mellon University - Africa, University College Dublin, Cornell University, Georgia Institute of Technology, Howard University, University of Oxford, Stanford University, University of the Witwatersrand, and many others.
Starting 2020, this program expanded into the Black in AI Academic Positions program, now serving current graduate students and over 100 Black junior scholars applying to postgraduate positions during the 2020/21 application cycle. Members of this program are interested in research careers in academia, industry, and policy, and previous participants have already had a significant impact in the field of AI.
On this page we will answer frequently asked questions and provide opportunities to advertise graduate, fellowship, postdoctoral, faculty, and research scientist positions. (See below.)
If you are interested in supporting us by volunteering your time as a mentor, donating to the program, or supporting us with our advocacy, please reach out to the organizers
Contact:
<EMAIL_ADDRESS>Organizers:
- Rediet Abebe, Ph.D., Harvard University
- Moses Namara, Clemson University
- Daniel Nkemelu, Georgia Institute of Technology
- Ezinne Nwankwo, Duke University
Faculty Advisors:
- Rediet Abebe, Ph.D., Harvard University
- Sanmi Koyejo, Ph.D., University of Illinois, Urbana Champaign
- Dina Machuve, Ph.D., Nelson Mandela African Institute of Science and Technology
- Brandeis Marshall, Ph.D.
Supported By:
Black in AI
FAQs:
- How can I take part in this program?
- How can I support this program as an academic?
- How can my organization support the program?
- How can I advertise graduate student, postdoctoral fellowship, faculty, or research scientist positions at my institutions?
- To advertise graduate programs (masters, professional, and doctorate degrees), please fill out this form.
- To advertise fellowships or scholarships, please fill out this form.
- To advertise postdoctoral, faculty, or research scientist positions, please fill out this form.
If you self-identify as Black and are applying to graduate or postgraduate positions or are currently in graduate school, please sign up to join the Black in AI google group here and follow instructions sent out over our email list.
You can sign up to mentor by first joining the Black in AI group here, then reaching out to us at<EMAIL_ADDRESS>For partnership and sponsorship, please email us at<EMAIL_ADDRESS>Resources:
- Help us identify graduate programs with lower financial barriers by filling out the respective forms below:


{% extends "kdl_wagtail/section.html" %} {% load wagtailcore_tags kdl_wagtail staticfiles %} {% block section-content %} {% block section-items_before %} {% for item in value.items %} {% if item.type == 'testimonials' %}
At the heart of Archetype is a philosophy that digital tools should enable scholars to do what they know best. It doesn’t aim to replace your workflow, but augment it with tools that adapt to your needs. The strength of Archetype is that your annotations are stored in a structured database, allowing you to explore your research data using powerful, built-in search facilities. Archetype may be used by individual scholars, or as the hub of a collaborative project, or to enable the sharing of data with other scholars anywhere.
Winner of the first annual Medieval Academy Digital Humanities Prize, Archetype (in the form of DigiPal) was commended for its “innovative framework, collaborative origins, open access, quality design, and skillfully curated pilot collection” and judged to be “an excellent model for the practice of digital humanities scholarship in the field of medieval studies.


Gaston
Gouron
About
Contact
Links
Diary
Road covers
2010
Animated music covers in relation to the road
soundtrack Kraftwerk > Autobahn
Animation
1:13'
Index
> Next project
< Previous project


Welcome To YAM
See more
Contact with me
What deserves your ears
And More
Your thoughts
Citizen — Yellow Love
Citizen — Yellow Love
Low Roar- Don't Be So Serious
Mo - Mercy


Title: {{ selectedMovie.title }}
0" class="reviewscore">User Review Score: {{ reviewScore.toFixed(1) }}
Year: {{ selectedMovie.releaseDate | date: 'yyyy' }}
Release Date: {{ selectedMovie.releaseDate }}
Runtime: {{ selectedMovie.runtimeMinutes }} minutes
Genre: {{ selectedMovie.movieGenres }}
Director(s): {{ selectedMovie.movieDirectors }}
Actors: {{ selectedMovie.movieActors }}
Plot Summary: {{ selectedMovie.plot }}


{% extends "base-full.html" %} {% block content %}
Almost there! Enter and confirm your new password and you'll be ready to go.


Compiling data from ACORD XML with SAX No validation of data is
performed by this class.
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Store accident or violation data |
source code
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setDriver(self,
data=None)
Store driver data |
source code
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setEffectiveDate(self,
data=None)
Store the effective date |
source code
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setLocation(self,
data=None)
Store location data |
source code
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setNameInfo(self,
data=None)
Store name and SSN data. |
source code
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setPaymentOption(self,
data=None)
Store payment option data |
source code
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setResidenceOwnedRented(self,
data=None)
Store residence ownership data |
source code
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setStreetAddr(self,
data=None)
Store street address data |
source code
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setVehicle(self,
data=None)
Store vehicle data |
source code
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updatePath(self,
name=None)
Update the current address in the XML stream |
source code
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Inherited from xml.sax.handler.ContentHandler :
endDocument ,
endElementNS ,
endPrefixMapping ,
ignorableWhitespace ,
processingInstruction ,
setDocumentLocator ,
skippedEntity ,
startDocument ,
startElementNS ,
startPrefixMapping
|


Clip
Users of popular grid-based DAWs like Ableton or Bitwig may be familiar with clips. Clips are simply a small set of MIDI notes that can repeat in a loop. A Song is what happens when you arrange multiple clips by Scene and Track in a grid.
To make for easy changes across an entire song, Patterns, transforms, and scales referenced in clips are symbolic links -
which may make sense if you have a programming background. What this means is that if one has a pattern named "groove1" and later
reconfigures what notes and chords are in groove1, Warp will change in all clips that use that pattern. This makes it easy to try out both small and large scale variations in a song without tedious reprogramming.
The same being true for scales means you could have a scale named "intro", and could later decide your introduction really should be played in a different key - and all parts of your song that reference "intro"
would change accordingly.
Basic Features
- A clip belongs to a Scene (horizontally) and a Track (Vertically) in the Song grid.
- A clip contains a list of one or more Patterns that play in order, resulting in notes.
- Playing a clip will stop any other clips that are playing in the same Track as the clip.
- A clip may have one or more Scales. These scales are used for each playing Pattern and are rotated in a loop as each pattern advances or the clip repeats.
- If a clip does not have a Scale assigned, the Scale can come from the Scene, and if not set set there either, then from the Song.
- A clip may also define a tempo multiplier rate such as 0.5 (half speed) or 2 (double speed) - and this can be any positive decimal value.
- A clip may have one or more Transforms, which are powerful tools that modify the currently playing Pattern. These are used in rotation just as the Scales are.
- A clip may have a list of tempo_shifts, which are added or subtracted to the tempo of each playing Pattern to construct tempo builds or endings. These rotate similarly as scales or transforms.
- A clip may be set to repeat indefinitely (it will end if the scene ends), a finite number of times, or just play once.
- A clip may be set to advance the Scene when the clip completes.
- A clip may trigger another specific clip when it completes. This does not occur if the clip is set to advance a Scene.


Remove superfluous (..)
around condition to avoid subshell overhead.
if ([ "$x" -gt 0 ])
then true; fi
if [ "$x" -gt 0 ]
then true; fi
The shell syntax is if cmd
, elif cmd
, while cmd
and until cmd
without any parentheses. Instead, parentheses are an independent construct used to create subshells.
ShellCheck has noticed that you're wrapping (..)
around one or more test commands. This is unnecessary, and the resulting fork adds quite a lot of overhead:
$ i=0; time while ( [ "$i" -lt 10000 ] ); do i=$((i+1)); done
real 0m6.998s
user 0m3.453s
sys 0m3.464s
$ i=0; time while [ "$i" -lt 10000 ]; do i=$((i+1)); done
real 0m0.055s
user 0m0.054s
sys 0m0.001s
Just delete the surrounding (..)
since they serve no purpose and only slows the script down.
This issue only affects performance, not correctness, so it can be safely [[ignore]]d.
If you are considering doing it to stylistically match C-like languages, please note that this is not conventional and that you'd probably recommend someone use if (1 == 2)
over if (system("[ 1 = 2 ]"))
in C no matter which language they're used to.