ETS models¶
The ETS models are a family of time series models with an underlying state space model consisting of a level component, a trend component (T), a seasonal component (S), and an error term (E).
This notebook shows how they can be used with statsmodels
. For a more thorough treatment we refer to [1], chapter 8 (free online resource), on which the implementation in statsmodels and the examples used in this notebook are based.
statsmodels
implements all combinations of: - additive and multiplicative error model - additive and multiplicative trend, possibly dampened - additive and multiplicative seasonality
However, not all of these methods are stable. Refer to [1] and references therein for more info about model stability.
[1] Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice, 3rd edition, OTexts, 2019. https://www.otexts.org/fpp3/7
[1]:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline
from statsmodels.tsa.exponential_smoothing.ets import ETSModel
[2]:
plt.rcParams['figure.figsize'] = (12, 8)
Simple exponential smoothing¶
The simplest of the ETS models is also known as simple exponential smoothing. In ETS terms, it corresponds to the (A, N, N) model, that is, a model with additive errors, no trend, and no seasonality. The state space formulation of Holt’s method is:
This state space formulation can be turned into a different formulation, a forecast and a smoothing equation (as can be done with all ETS models):
Here, \(\hat{y}_{t|t-1}\) is the forecast/expectation of \(y_t\) given the information of the previous step. In the simple exponential smoothing model, the forecast corresponds to the previous level. The second equation (smoothing equation) calculates the next level as weighted average of the previous level and the previous observation.
[3]:
oildata = [
111.0091, 130.8284, 141.2871, 154.2278,
162.7409, 192.1665, 240.7997, 304.2174,
384.0046, 429.6622, 359.3169, 437.2519,
468.4008, 424.4353, 487.9794, 509.8284,
506.3473, 340.1842, 240.2589, 219.0328,
172.0747, 252.5901, 221.0711, 276.5188,
271.1480, 342.6186, 428.3558, 442.3946,
432.7851, 437.2497, 437.2092, 445.3641,
453.1950, 454.4096, 422.3789, 456.0371,
440.3866, 425.1944, 486.2052, 500.4291,
521.2759, 508.9476, 488.8889, 509.8706,
456.7229, 473.8166, 525.9509, 549.8338,
542.3405
]
oil = pd.Series(oildata, index=pd.date_range('1965', '2013', freq='AS'))
oil.plot()
plt.ylabel("Annual oil production in Saudi Arabia (Mt)");
[3]:
Text(0, 0.5, 'Annual oil production in Saudi Arabia (Mt)')
The plot above shows annual oil production in Saudi Arabia in million tonnes. The data are taken from the R package fpp2
(companion package to prior version [1]). Below you can see how to fit a simple exponential smoothing model using statsmodels’s ETS implementation to this data. Additionally, the fit using forecast
in R is shown as comparison.
[4]:
model = ETSModel(oil, error='add', trend='add', damped_trend=True)
fit = model.fit(maxiter=10000)
oil.plot(label='data')
fit.fittedvalues.plot(label='statsmodels fit')
plt.ylabel("Annual oil production in Saudi Arabia (Mt)");
# obtained from R
params_R = [0.99989969, 0.11888177503085334, 0.80000197, 36.46466837, 34.72584983]
yhat = model.smooth(params_R).fittedvalues
yhat.plot(label='R fit', linestyle='--')
plt.legend();
[4]:
<matplotlib.legend.Legend at 0x7ff29caa8310>
By default the initial states are considered to be fitting parameters and are estimated by maximizing log-likelihood. Additionally it is possible to only use a heuristic for the initial values. In this case this leads to better agreement with the R implementation.
[5]:
model_heuristic = ETSModel(oil, error='add', trend='add', damped_trend=True,
initialization_method='heuristic')
fit_heuristic = model_heuristic.fit()
oil.plot(label='data')
fit.fittedvalues.plot(label='estimated')
fit_heuristic.fittedvalues.plot(label='heuristic', linestyle='--')
plt.ylabel("Annual oil production in Saudi Arabia (Mt)");
# obtained from R
params = [0.99989969, 0.11888177503085334, 0.80000197, 36.46466837, 34.72584983]
yhat = model.smooth(params).fittedvalues
yhat.plot(label='with R params', linestyle=':')
plt.legend();
[5]:
<matplotlib.legend.Legend at 0x7ff29ca19c90>
The fitted parameters and some other measures are shown using fit.summary()
. Here we can see that the log-likelihood of the model using fitted initial states is a bit lower than the one using a heuristic for the initial states. Additionally, we see that \(\beta\) (smoothing_trend
) is at the boundary of the default parameter bounds, and therefore it’s not possible to estimate confidence intervals for \(\beta\).
[6]:
print(fit.summary())
ETS Results
==============================================================================
Dep. Variable: y No. Observations: 49
Model: ETS(AAdN) Log Likelihood -258.108
Date: Tue, 02 Feb 2021 AIC 528.216
Time: 07:02:07 BIC 539.567
Sample: 01-01-1965 HQIC 532.523
- 01-01-2013 Scale 2202.048
Covariance Type: approx
===================================================================================
coef std err z P>|z| [0.025 0.975]
-----------------------------------------------------------------------------------
smoothing_level 0.9999 0.136 7.326 0.000 0.732 1.267
smoothing_trend 9.999e-05 nan nan nan nan nan
damping_trend 0.8798 0.059 14.901 0.000 0.764 0.996
initial_level 54.2331 55.750 0.973 0.331 -55.034 163.500
initial_trend 52.9975 34.392 1.541 0.123 -14.409 120.404
===================================================================================
Ljung-Box (Q): 1.42 Jarque-Bera (JB): 20.73
Prob(Q): 0.49 Prob(JB): 0.00
Heteroskedasticity (H): 0.52 Skew: -1.02
Prob(H) (two-sided): 0.20 Kurtosis: 5.45
===================================================================================
Warnings:
[1] Covariance matrix calculated using numerical (complex-step) differentiation.
[7]:
print(fit_heuristic.summary())
ETS Results
==============================================================================
Dep. Variable: y No. Observations: 49
Model: ETS(AAdN) Log Likelihood -258.881
Date: Tue, 02 Feb 2021 AIC 525.761
Time: 07:02:08 BIC 533.328
Sample: 01-01-1965 HQIC 528.632
- 01-01-2013 Scale 2272.587
Covariance Type: approx
===================================================================================
coef std err z P>|z| [0.025 0.975]
-----------------------------------------------------------------------------------
smoothing_level 0.9999 0.097 10.289 0.000 0.809 1.190
smoothing_trend 0.1183 nan nan nan nan nan
damping_trend 0.8000 nan nan nan nan nan
==============================================
initialization method: heuristic
----------------------------------------------
initial_level 33.6309
initial_trend 34.8115
===================================================================================
Ljung-Box (Q): 0.27 Jarque-Bera (JB): 19.93
Prob(Q): 0.88 Prob(JB): 0.00
Heteroskedasticity (H): 0.50 Skew: -0.95
Prob(H) (two-sided): 0.18 Kurtosis: 5.48
===================================================================================
Warnings:
[1] Covariance matrix calculated using numerical (complex-step) differentiation.
Holt-Winters’ seasonal method¶
The exponential smoothing method can be modified to incorporate a trend and a seasonal component. In the additive Holt-Winters’ method, the seasonal component is added to the rest. This model corresponds to the ETS(A, A, A) model, and has the following state space formulation:
[8]:
austourists_data = [
30.05251300, 19.14849600, 25.31769200, 27.59143700,
32.07645600, 23.48796100, 28.47594000, 35.12375300,
36.83848500, 25.00701700, 30.72223000, 28.69375900,
36.64098600, 23.82460900, 29.31168300, 31.77030900,
35.17787700, 19.77524400, 29.60175000, 34.53884200,
41.27359900, 26.65586200, 28.27985900, 35.19115300,
42.20566386, 24.64917133, 32.66733514, 37.25735401,
45.24246027, 29.35048127, 36.34420728, 41.78208136,
49.27659843, 31.27540139, 37.85062549, 38.83704413,
51.23690034, 31.83855162, 41.32342126, 42.79900337,
55.70835836, 33.40714492, 42.31663797, 45.15712257,
59.57607996, 34.83733016, 44.84168072, 46.97124960,
60.01903094, 38.37117851, 46.97586413, 50.73379646,
61.64687319, 39.29956937, 52.67120908, 54.33231689,
66.83435838, 40.87118847, 51.82853579, 57.49190993,
65.25146985, 43.06120822, 54.76075713, 59.83447494,
73.25702747, 47.69662373, 61.09776802, 66.05576122,
]
index = pd.date_range("1999-03-01", "2015-12-01", freq="3MS")
austourists = pd.Series(austourists_data, index=index)
austourists.plot()
plt.ylabel('Australian Tourists');
[8]:
Text(0, 0.5, 'Australian Tourists')
[9]:
# fit in statsmodels
model = ETSModel(austourists, error="add", trend="add", seasonal="add",
damped_trend=True, seasonal_periods=4)
fit = model.fit()
# fit with R params
params_R = [
0.35445427, 0.03200749, 0.39993387, 0.97999997, 24.01278357,
0.97770147, 1.76951063, -0.50735902, -6.61171798, 5.34956637
]
fit_R = model.smooth(params_R)
austourists.plot(label='data')
plt.ylabel('Australian Tourists')
fit.fittedvalues.plot(label='statsmodels fit')
fit_R.fittedvalues.plot(label='R fit', linestyle='--')
plt.legend();
[9]:
<matplotlib.legend.Legend at 0x7ff29abc2bd0>
[10]:
print(fit.summary())
ETS Results
==============================================================================
Dep. Variable: y No. Observations: 68
Model: ETS(AAdA) Log Likelihood -152.627
Date: Tue, 02 Feb 2021 AIC 327.254
Time: 07:02:10 BIC 351.668
Sample: 03-01-1999 HQIC 336.928
- 12-01-2015 Scale 5.213
Covariance Type: approx
======================================================================================
coef std err z P>|z| [0.025 0.975]
--------------------------------------------------------------------------------------
smoothing_level 0.3398 0.111 3.070 0.002 0.123 0.557
smoothing_trend 0.0259 0.008 3.158 0.002 0.010 0.042
smoothing_seasonal 0.4010 0.080 5.041 0.000 0.245 0.557
damping_trend 0.9800 nan nan nan nan nan
initial_level 29.4475 2.92e+04 0.001 0.999 -5.72e+04 5.72e+04
initial_trend 0.6147 0.392 1.567 0.117 -0.154 1.383
initial_seasonal.0 -3.4379 2.92e+04 -0.000 1.000 -5.72e+04 5.72e+04
initial_seasonal.1 -5.9571 2.92e+04 -0.000 1.000 -5.72e+04 5.72e+04
initial_seasonal.2 -11.4881 2.92e+04 -0.000 1.000 -5.72e+04 5.72e+04
initial_seasonal.3 0 2.92e+04 0 1.000 -5.72e+04 5.72e+04
===================================================================================
Ljung-Box (Q): 5.76 Jarque-Bera (JB): 7.69
Prob(Q): 0.67 Prob(JB): 0.02
Heteroskedasticity (H): 0.46 Skew: -0.63
Prob(H) (two-sided): 0.07 Kurtosis: 4.05
===================================================================================
Warnings:
[1] Covariance matrix calculated using numerical (complex-step) differentiation.
Predictions¶
The ETS model can also be used for predicting. There are several different methods available: - forecast
: makes out of sample predictions - predict
: in sample and out of sample predictions - simulate
: runs simulations of the statespace model - get_prediction
: in sample and out of sample predictions, as well as prediction intervals
We can use them on our previously fitted model to predict from 2014 to 2020.
[11]:
pred = fit.get_prediction(start='2014', end='2020')
[12]:
df = pred.summary_frame(alpha=0.05)
df
[12]:
| mean | pi_lower | pi_upper | |
|---|---|---|---|
| 2014-03-01 | 67.611048 | 63.136076 | 72.086020 |
| 2014-06-01 | 42.814811 | 38.339839 | 47.289783 |
| 2014-09-01 | 54.106462 | 49.631490 | 58.581434 |
| 2014-12-01 | 57.928276 | 53.453304 | 62.403248 |
| 2015-03-01 | 68.422079 | 63.947107 | 72.897051 |
| 2015-06-01 | 47.277849 | 42.802877 | 51.752821 |
| 2015-09-01 | 58.954740 | 54.479768 | 63.429712 |
| 2015-12-01 | 63.982155 | 59.507183 | 68.457127 |
| 2016-03-01 | 75.905268 | 71.430295 | 80.380240 |
| 2016-06-01 | 51.418122 | 46.654016 | 56.182228 |
| 2016-09-01 | 63.703292 | 58.629393 | 68.777191 |
| 2016-12-01 | 67.978107 | 62.575778 | 73.380436 |
| 2017-03-01 | 78.315764 | 71.735800 | 84.895727 |
| 2017-06-01 | 53.780408 | 46.883520 | 60.677296 |
| 2017-09-01 | 66.018333 | 58.788303 | 73.248362 |
| 2017-12-01 | 70.246847 | 62.668821 | 77.824872 |
| 2018-03-01 | 80.539128 | 71.892785 | 89.185471 |
| 2018-06-01 | 55.959305 | 46.968347 | 64.950264 |
| 2018-09-01 | 68.153652 | 58.805308 | 77.501996 |
| 2018-12-01 | 72.339460 | 62.621963 | 82.056957 |
| 2019-03-01 | 82.589889 | 71.864783 | 93.314995 |
| 2019-06-01 | 57.969051 | 46.876058 | 69.062044 |
| 2019-09-01 | 70.123203 | 58.652201 | 81.594204 |
| 2019-12-01 | 74.269620 | 62.411255 | 86.127984 |
| 2020-03-01 | 84.481446 | 71.656450 | 97.306441 |
In this case the prediction intervals were calculated using an analytical formula. This is not available for all models. For these other models, prediction intervals are calculated by performing multiple simulations (1000 by default) and using the percentiles of the simulation results. This is done internally by the get_prediction
method.
We can also manually run simulations, e.g. to plot them. Since the data ranges until end of 2015, we have to simulate from the first quarter of 2016 to the first quarter of 2020, which means 17 steps.
[13]:
simulated = fit.simulate(anchor="end", nsimulations=17, repetitions=100)
[14]:
for i in range(simulated.shape[1]):
simulated.iloc[:,i].plot(label='_', color='gray', alpha=0.1)
df["mean"].plot(label='mean prediction')
df["pi_lower"].plot(linestyle='--', color='tab:blue', label='95% interval')
df["pi_upper"].plot(linestyle='--', color='tab:blue', label='_')
pred.endog.plot(label='data')
plt.legend()
[14]:
<matplotlib.legend.Legend at 0x7ff29c8541d0>
In this case, we chose “end” as simulation anchor, which means that the first simulated value will be the first out of sample value. It is also possible to choose other anchor inside the sample.
[ ]:


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Update 24-06-15
Thanks to this page, I fixed my script. It no longer requires root privillages. I also muted informational messages because they were not very informational.
The Story
Today I had a list of files (nagios check scripts), and I wanted to check for every file if there's a package containing it (I'm a big fan of getting files from the repo rather than downloading manually). Although YUM provides a way to search for packages containing a file pattern, like this:
yum provides '*/check_mailq'
The output is quite complicated to parse:
Loaded plugins: fastestmirror, presto
Loading mirror speeds from cached hostfile
* base: mirrors.seas.harvard.edu
* epel: mirror.symnds.com
* extras: mirror.ash.fastserv.com
* updates: mirror.cogentco.com
private-chef-1.4.15-1.el6.x86_64 : The full stack of private-chef
Repo : chef-stable
Matched from:
Filename : /opt/opscode/embedded/nagios/libexec/check_mailq
private-chef-1.4.14-1.el6.x86_64 : The full stack of private-chef
Repo : chef-stable
Matched from:
Filename : /opt/opscode/embedded/nagios/libexec/check_mailq
nagios-plugins-mailq-1.4.16-10.el6.x86_64 : Nagios Plugin - check_mailq
Repo : epel
Matched from:
Filename : /usr/lib64/nagios/plugins/check_mailq
The first part is irrelevant (info messages that should IMO go to stderr
), and every entry in the actual result contains multiple lines... bah.
Luckily, YUM is completely written in python so we can copy its behaviour with a custom script.
The Solution
I used this post to help me with basic discovery. The rest is my work.
This script requires root (or sudo
). I didn't bother finding out how to run it otherwise.
import logging
import yum
yb=yum.YumBase()
yb.setCacheDir()
logging.disable(logging.WARNING) # Mute loggers
files=['YOUR','file','name','go','here']
res={}
for f in files:
r=yb.searchPackageProvides(['*/'+f]) # ,('*/'+f+'.*')
res[f]=map(lambda x: x.name, r)
The following part varies by your objective. I wanted to list the packages required for each file, and also a sorted list of all relevant packages:
print '**No matches:'
for p in filter(lambda x: len(res[x])==0, res): print p
print
print '**Matches:'
for p in filter(lambda x: len(res[x])>0, res): print p,res[p]
print
print '**Duplicates:'
for p in filter(lambda x: len(res[x])>1, res): print p,res[p]
print
print '**Packages to be installed:'
pkgs=map(lambda x: res[x],filter(lambda x: len(res[x])>0, res))
print sorted(list(set([item for sublist in pkgs for item in sublist])))
The result is quite nice:
**No matches:
check_sockets.sh
check_threads.sh
check_exit_code.pl
check_duplicate_process
**Matches:
check_nagios ['nagios-plugins-nagios']
check_breeze ['nagios-plugins-breeze']
check_mrtgtraf ['nagios-plugins-mrtgtraf']
check_ldap ['check-mk', 'check-mk-docs', 'nagios-plugins-ldap']
check_ircd ['nagios-plugins-ircd']
**Duplicates:
check_ldap ['check-mk', 'check-mk-docs', 'nagios-plugins-ldap']
check_dns ['nagios-plugins-dns', 'check-mk', 'check-mk-docs']
check_smtp ['check-mk', 'nagios-plugins-smtp', 'check-mk-docs']
**Packages to be installed:
['check-mk', 'check-mk-docs', 'nagios-plugins-breeze', 'nagios-plugins-dns', 'nagios-plugins-ircd', 'nagios-plugins-ldap', 'nagios-plugins-mrtgtraf', 'nagios-plugins-nagios', 'nagios-plugins-smtp']
Looks good.


Before Change
A index for data shuffling due to sparse format change. Return None
if shuffle is not required.
raise Exception("immutable graph doesn\"t support incidence_matrix for now.")
def to_networkx(self):
Convert to networkx graph.
After Change
A index for data shuffling due to sparse format change. Return None
if shuffle is not required.
raise NotImplementedError("immutable graph doesn\"t implement incidence_matrix for now.")
def to_networkx(self):
Convert to networkx graph.


DAMES AT TEA
TEA WITH MUSSOLINI Directed by Franco Zeffirelli Screenplay by Zeffirelli and John Mortimer With Maggie Smith, Judi Dench De Vargas PG 117 min.
Franco Zeffirelli's reminiscence of his formative years in Mussolini's fascist Italy is pretty irresistible, in spite of a persistent shallowness of story and a touch of weakness for self- glorification. What it has going for it is Zeffirelli's reliable bonfire of surface vanities, including a nice evocation of period and glorious camerawork by David Watkin ("Out of Africa"); and best of all, a cast of actresses as delicious as the ice cream sundae disparaged by one of their number as an American vulgarism.
Dame Maggie Smith is Lady Hester, widow of the former British Ambassador and the doyenne of a clutch of pixillated British lady expats in Florence known as the Scorpioni. Lady Hester is a full-bore snob, and when she snorts "Americans!", of course we love it. Among her circle are Arabella, a dotty romantic artist played by Dame Judi Dench, whose career was crowned with a Tony this week, and Mary (Dame Joan Plowright), secretary to a philandering Italian businessman. Mary finds herself with the care and feeding of young Luca (Charlie Lucas), the motherless and unwanted illegitimate son of her boss. Luca, the end titles tell us, "grew up to be an artist and helped with the making of this picture." A degree in rocket science will help you understand that Luca is Zeffirelli himself.
Rounding out this bevy of talent is that American vulgarism herself, Elsa (Cher), a former showgirl who marries rich old men and gives them a bang for their buck before they go on to their next reward ("He's an angel," she confides of the latest, "or soon will be....")
The Scorpioni are at tea in an elegant hotel dining room when their protected world is rudely interrupted by shouting blackshirted hooligans smashing the stained glass windows and letting in an unpleasant whiff of the real world outside. Troubled, the ambassador's widow travels to Rome to see Mussolini, who smarmily reassures her over tea that she has nothing to fear.
But of course she does, they all do, though when war breaks out they stubbornly refuse to leave the country that is, after all, their home. They're rounded up as enemy aliens and incarcerated, though they are soon moved to hotel quarters in San Gemignano -- courtesy, Lady Hester is sure, of her friend and protector Il Duce. At this point the teenage Luca (Baird Wallace) returns from school in Austria, where his father had sent him to learn to be a good Nazi. Instead, he devotes himself to the ladies and to the Resistance, and eventually the war turns out well.
Smith and Dench reprise their characters from "A Room with a View", but these ladies are so good that you gladly accept the type-casting. Best of all is Joan Plowright, who plays a lovely scene with young Luca and a puppet stage that anticipates his future calling. Cher in her best scenes reminds us what a wonderful and charming actress she is, and dazzles us with what can be truly called a sculpted beauty. Lily Tomlin is good in a smaller role.
It's an up-and-down ride, but it would be a shame to miss a movie that offers such pleasures just because of a few shortcomings. Take "Tea" and see.
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


Inspire future generations by providing the most exciting and diverse speakers for your conference.
View the Project on GitHub KirstieJane/STEMMRoleModels
Logo image credit: Charis Tsevis
This is the page at which you would enter your search terms
We'd start with some instructions [that haven't been written yet!]
There would be certain terms related to the potential speaker:
And then certain filters based on how each member of the database has identified as a role model:
Would you like to help us develop this page?
Help with layout, content (text, images) and spelling mistakes all welcome!
Please
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Love your Friends
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Friendship... is not something you learn in school. But if you haven't learned the meaning of friendship, you really haven't learned anything.
Friendship Goals
When the great end of the day comes, the greatest joy of all will be the joy of knowing you have tried to make somebody else's life happy
He's what we really need. If your friend is sick and dying, the most important thing he wants is not an explanation but for you to sit with him. He's terrified of being alone more than anything else. So God has not left us alone
Mara text by Space Ipsum. Photographs by Mary Rose Asirot.


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When I switched from Visual Studio to using Vim I often experienced Vim freezes. This was really annoying. At the beginning I was thinking that maybe I installed too many plugins (using Vundle) or that Vim is not as good as they say.
After a few weeks an
idea come to my mind, I noticed that I have a subconscious habit of
pressing Ctrl+S
when editing a file. But hey Ctrl+S
has
special meaning for Linux terminal, it’s a terminal scroll lock -
basically it freezes program that wants to write to standard output/error.
To unfreeze program you must press Ctrl+Q
.
You can use this Bash one-liner to check how it works:
It still happens from time to time that I press Ctrl+S
while using
Vim (old habits die hard), but now I just press Ctrl+Q
and continue
my work. So far I have never experienced a real Vim freeze again.
Note for Windows users
Terminal scroll lock also works in Windows but there you use
Ctrl+S
both to freeze and to unfreeze a program.


Hello!
I'm using the EmonTX with DS18B20 sensors and the emontx_temperature_power script. Everything is working fine, but I have problems with negative temperatures.
How do I convert the input to a correct value, the standard calculation generates a value of 651°C for example, that should be about -10,8°C. Positive temperature values work without problems.
Re: Temperature sensors - negative values
Try searching the forums - IIRC I've seen this question before, I think it's a matter of signed/unsigned integers.
http://openenergymonitor.org/emon/node/1074
Re: Temperature sensors - negative values
Ok I've found a solution that is working for me.
First EmonTX has to check if the value is positive or negative. The maximum positive value is 125°C, the maximum negative value is -55°C.
If the value is negative the reading from the sensor will be higher than 500.00, that means an integer value of 50000. If this occurs I subtract the value from 65535. This is now the negative temperature but I can't add a minus to the integer. So the next step is to move the 0°C line up to +55°C, so th e value is subtracted from 5500. This value can now be transmitted to the receiver. To combine these steps simply subtract 60035 from the reading value and transmit it.
If the value is positiv then you have to add 5500 to the measurement (because 0 now means -55°C).
Code for EmonTX (inserted after reading of the temperature sensors):
if (emontx.T1 > 50000) emontx.T1=emontx.T1-60035;
else emontx.T1=emontx.T1+5500;
In EmonCms you simply subtract 5500 by adding -5500 to the received value and multiply it with 0.01 to get the real value because EmonCms can work with negative values.
Re: Temperature sensors - negative values
With my fusion sketch, I read the results of the sensing into a float variable first. Just before I want to transmit them I multiply them by 100 (so as to maintain two decimal places) and then cast them as integers just before the payload transmission.
On the receiver (either the GLCD or emonCMS or, in my case both) upon receipt of the payload I divide the received numbers by 100 and can then work with them.
This works fine on emoncms but the GLCD struggles to print negative numbers so I need to do a check and if the value is less than zero I need to print a negative sign in front of the value on the display. Cms will give fractional readings but GLCD seems happier just printing integers.
Re: Temperature sensors - negative values
After solving the biggest problem (no negative values possible) I want to find a solution for the problem when a sensor is disconnected. Then I get a value of 52836, I allready tried the following but something doesn't work.
if (emontx.T1>60035) emontx.T1=emontx.T1-60035; // negative value
else emontx.T1=emontx.T1+5500; // positive value
if (emontx.T1>18000) emontx.T1=5500; // Error: value should be 0°C
I want to send 0°C that would mean a value of 5500 when a sensor fails. On a graph It could be seen easily when the value drops to 0 (ok when the temperature is around 0 it can't be seen but normally temperatures move up and down permanently so if the value doesn't change for some time there should be an error.
Does anybody find an error in the short script?
Re: Temperature sensors - negative values
You don't need to do anything to the emonTx code, it behaves correctly and uses signed integers. If there is no sensor present it shows a value of -127 which is 52836 in unsigned form.
The latest version of emonCMS also handles signed integers correctly. The most likely cause of your problems is that you are running an old version of emonCMS. Have you checked?
Re: Temperature sensors - negative values
Ok it seems the version of EmonCMS on my Raspberry wasn't the latest one. I did a complete new installation of EmonCMS (copy old database and directory done) and installed the standard temperature sensor example with the correct sensor adresses of cause.
Now I also get negative values, but is it possible to tell EmonCMS to convert a value of -127 to 0 because I don't want these "spikes" to -127 when a sensor failes. This completely destroys the readability of a temperature graph.
Any solution to get EmonCMS to convert -127 to a definded value (for example 0)?
Re: Temperature sensors - negative values
It would probably be better to just ignore that value, trash it, as if there had been no transmission at all.
Re: Temperature sensors - negative values
Hello Jerome!
For me it's clear that -127 is a failure, but how to tell emoncms?
I think there should be a possibility in the input configuration to drop values if they have a certain value. (if value > x or if value < x then drop, else continue with the input processes) This would also reduce the space needed for the database if no false values are stored.
Re: Temperature sensors - negative values
Hi.
> For me it's clear that -127 is a failure, but how to tell emoncms?
I don't know, I haven't looked into the code of emoncms (yet). I was replying to this specific sentence :
> Now I also get negative values, but is it possible to tell EmonCMS to convert a value of -127 to 0
If -127 values can be detected, I'd rather have them removed than converted to 0.
Re: Temperature sensors - negative values
Removing would also be ok for me if possible.
It would be perfect if I can define in the inout configuration that if a value higher or lower than x is discarded and the handling of the input value is done with this step. Then it could be applied to all kind of inputs (power, temperature,...)


My name is Jonathan, and I'm from Honolulu, Hawaii. In my free time, I like like listening and trying to make music, longboarding, cooking/baking and making cool stuff. A lot of it starts with the question "Hey, you know what would be cool?" and this website and many of the projects on it are a testament to that.
I currently attend the Olin College of Engineering, a small, project based engineering school just outside of Boston. At Olin, I'm heavily involved in the Formula SAE team where I was the mechanical design lead for three semesters, from June 2018 to December 2019. Each year, we design, build, and race an open wheeled racecar.
As an engineer, I'm particularly interested in applying modeling and simulation to solve complex engineering problems.


This page is for configuring networking options for the SSH server. Some
of the less obvious options are :
- Idle timeout
- If this is set and there has been nothing sent by the client or server
during the period set, the client will be disconnected.
- Disconnect if client has crashed?
- If set to Yes, the SSH server will periodically check to see if the
client is still alive. If not (because of a network error or client machine
crash) it will be disconnected.
- Allow TCP forwarding?
- If this option is set, users can tunnel TCP connections from client
machines to machines on the server's network, and also allow connections
back from the server to machines on the client network.


It incorporates a 6.2-inch, 16:9 aspect ratio LCD touch screen, as well as traditional button controls and two analog sticks.
The GamePad also includes motion control, a front-facing camera, a microphone, stereo speakers, rumble features, a sensor bar, a stylus, and support for Near Field Communication (NFC). It is powered by a rechargeable lithium-ion battery and weighs approximately 1.1 pounds.
 Each time you turn on your Wii U console, you'll be greeted by Mii characters from around the world, and the Wii U community's most talked about games in the WaraWara Plaza.
Play Exlusive games
Check out the new generation of exclusive Nintendo games in gorgeous high-definition on the Wii U console - an amazing value the whole family can enjoy..
Play Nintendo
Young gamers and their parents have a new home on the web with Play Nintendo. Head to Play Nintendo to learn about your favorite characters, try out some fun activities, challenge yourself with a quiz or two, and much more. We'll add fresh content each week, so you'll always find something new to try.
Wii Remote Plus
The Wii Remote Plus is a unique controller for the Wii and Wii U systems that has the increased sensitivity of Wii MotionPlus built-in.
The button pressing of typical controllers is replaced by the natural, fluid motion of your hand. The Wii Remote Plus senses your every action and makes you feel less like a player and more like you're part of the game.


Welcome to my personal portfolio ...
Software Engineer in Toronto
Loves gaming
Loves food
Placeholder


Other Support for Dynamic Meta-objects¶
PyQt5 creates a QMetaObject
instance for any Python
sub-class of QObject
without the need for the
equivalent of Qt’s Q_OBJECT
macro. Most of a
QMetaObject
is populated automatically by defining
signals, slots and properties as described in previous sections. In this
section we cover the ways in which the remaining parts of a
QMetaObject
are populated.
Q_ENUMS()
and Q_FLAGS()
¶
New in version 5.2.
The Q_ENUMS()
and Q_FLAGS()
functions
declare enumerated types and flag types respectively that are published in the
QMetaObject
. The typical use in PyQt5 is to declare
symbolic constants that can be used by QML, and as type of properties that can
be set in Qt Designer.
Each function takes a number of Python type objects that implement the enumerated or flag type. For example:
from PyQt5.QtCore import Q_ENUMS, Q_FLAGS, QObject
class Instruction(QObject):
class Direction:
Up, Down, Left, Right = range(4)
Q_ENUMS(Direction)
class Status:
Null = 0x00
Urgent = 0x01
Acknowledged = 0x02
Completed = 0x04
Q_FLAGS(Status)
Q_CLASSINFO()
¶
The Q_CLASSINFO()
function is used in the same way as Qt’s
macro of the same name, i.e. it is called from a class’s definition in order to
specify a name/value pair that is placed in the class’s
QMetaObject
.
For example it is used by QML to define the default property of a class:
from PyQt5.QtCore import Q_CLASSINFO, QObject
class BirthdayParty(QObject):
Q_CLASSINFO('DefaultProperty', 'guests')


{% extends 'base.html' %} {% block content %}
This page allows you to change your password.
{% if form.errors %}Please re-enter your passwords. You either entered the wrong current password, or your new passwords did not match.
{% endif %} {% endblock %}


Takes a dataset of occurence or count observations and runs a pair-wise information network over all combinations of variables.
calc_entropy_net( pairs, id_col, target_col, count_col, info_func = associationsubgraphs::calc_mutual_info, possible_targets, parallel = TRUE, subset_pairs = FALSE, verbose = FALSE )
| pairs | Dataframe with at least two columns: |
|---|---|
| id_col | Name of column containing variable id (I.e. nodes of the association network). |
| target_col | Name of the column containing the target for occurance (I.e. the data used to infer association between nodes). |
| count_col | Name of column containing count values as integers. If this
is not set and no column with title |
| info_func | What information function should be used? Like all of the
|
| possible_targets | If there are some |
| parallel | Should the processing be run in parallel? Three options. A
logical |
| subset_pairs | Should the algorithm be run on a random subset of
possible combinations? Useful for making sure everything is good before
running larger jobs. Set to the number of pairs you want to calculate
strength for. If reproducability is desired use |
| verbose | Information about steps is written to console. |
# Run association net on the virus-host dataset calc_entropy_net( pairs = virus_host, id_col = virus_id, target_col = host_id, parallel = FALSE, subset_pairs = 100 )#> # A tibble: 100 x 3 #> a b strength #> <chr> <chr> <dbl> #> 1 Human papillomavirus 60 Manzanilla virus 0.00000254 #> 2 Caprine arthritis encephalitis virus Manzanilla virus 0.00000509 #> 3 Bovine ephemeral fever virus Wesselsbron virus 0.00313 #> 4 Human papillomavirus 53 Swinepox virus 0.00000254 #> 5 Lake Victoria marburgvirus Murine adenovirus A 0.0000179 #> 6 Australian bat lyssavirus Cercopithecine herpesvirus 16 0.000116 #> 7 Hippotragine herpesvirus 1 Rubella virus 0.00000254 #> 8 California encephalitis virus Human parainfluenza virus 1 0.00421 #> 9 Tamana bat virus Equine adenovirus A 0.0000333 #> 10 Japanese encephalitis virus Moloney murine sarcoma virus 0.0000672 #> # … with 90 more rows# Run count-based association for vir-clasp rna-seq dataset calc_entropy_net( pairs = virclasp_chikv, id_col = id, target_col = condition, count_col = count, parallel = FALSE, subset_pairs = 100 )#> # A tibble: 100 x 3 #> a b strength #> <chr> <chr> <dbl> #> 1 RFT1_HUMAN MBB1A_HUMAN 1.94 #> 2 SAHH2_HUMAN SAE2_HUMAN 0.969 #> 3 PSB5_HUMAN TGM3_HUMAN 0.0766 #> 4 OST48_HUMAN OTUD4_HUMAN 0.503 #> 5 GLYG_HUMAN KPRP_HUMAN 1.15 #> 6 NUP93_HUMAN APBB2_HUMAN 0.0786 #> 7 ARHGB_HUMAN AUTS2_HUMAN 0.0839 #> 8 LTN1_HUMAN CMTR1_HUMAN 2.74 #> 9 SYMC_HUMAN PLPL6_HUMAN 1.70 #> 10 ABCB7_HUMAN PSMF1_HUMAN 0.595 #> # … with 90 more rows


THE CELEBRATION
Reviewed by Harvey Karten, Ph.D. October Films Director: Thomas Vinterberg Writer: Thomas Vinterberg, Morens Rubkov Cast: John Boas, Klaus Bondam, Lars Brygmann, Gbatokai Dakinah, Helle Dolleris, Trine Dyrholm, Therese Glahn, Gjarne Henriksen, Thomas Bo Larsen, Linda Laursen, Lasse Lunderskov, Henning Moritzen, Birthe Neumann, Lene Laub Oksen, Birgitte Simonsen, Paprika Steen, Ulrich Thomsen
During the last world war, when their country was occupied by the Nazis, the Danes did a dauntless job of saving their country's Jews from deportation to the death camps, putting them in the front ranks on the Continent for such empathy, compassion adn good will. There's nothing like a Dane. Unfortunately, however, within the four walls of family life, they're no different from the rest of us, or at least that's so in the mind of writer-director Thomas Vinterberg whose "The Celebration" is produced by Lars von Trier ("The Kingdom," parts 1 & 2). With pederastry the trendy subject tackled this year by the film industry--"Lolita" is hitting the screens on Sept. 25 and "Happiness" following soon thereafter--this Danish study of family dysfunction pushes the envelope further. Involuntary incest, not mere pedophilia, is the theme-- not a new one if you've read or seen "Oedipus"--but in the hands of von Trier and Vinterberg the subjects gets a darkly comic touch. Most of the action takes place within the home of a wealthy man celebrating his sixtieth birthday, so that the story does bear the imprint of the stage and, in fact, some of the leading performers are quite renowned players in the Danish theater scene.
A powerful drama of guilt, revelation and cleansing which in Danish is called "Festen," this production exhibits the perverse manners of the birthday party from hell. Its celebrants including a large contingent of racists, a child molester, a wife abuser, a couple of psychotics and an assemblage of neurotics and, as has been fashionable in stories about incest since the time of Sophocles, a juicy suicide.
In one of the few outdoor scenes, a caravan of cars make their way across the Danish countryside to the chateau which is the country home of the fabulously wealthy patriarch, Helge (Henning Moritzen). At least two of the guests are off-the-wall from the very beginning. Michael (Thomas Bo Larsen), the eldest son, is so volatile he has to crash the banquet as his dad refused to invite him. He shrieks and is shrieked at by his wife, Mette (Helle Dolleris), throws her out of the car to allow his brother Christian (Ulrich Thomsen) to join him, slaps her around, and even engages in a bout of malevolent sex, graphically shown, as the guests are in their rooms awaiting the call to dinner. We learn that their sister, Linda (Lene Laub Oksen, who shows up in a flashback) had committed suicide by drowning herself in the bathtub a short while back, and soon enough find out the motive behind the tragedy.
As the dinner progresses with the toastmaster (Klaus Bondam) emceeing the banal speeches of the guests, Christian shocks the company by announcing "Dad raped us," adding as if to mollify the poor man that Helge had always been a clean person, addicted to baths in all seasons. He is later to present another toast to his old man, one even more shocking, but even then, the guests are prepared not to believe him until further evidence is brought forth.
Between these bouts of speechmaking, Vinterberg treats us to some comic business and hanky panky, particularly involving Christian's relationship to one of the house maids, Pia (Trine Dyrholm), a woman to whom he had not been able to commit presumably because of his childhood violations. In one scene Vinterberg indicts virtually the entire society of wealthy and successful guests as racists. When Helene (Paprika Steen) shows up with a black boyfriend, (Gbatokai Dakinah), the assemblage all burst forth in a racist song about "black Sambos" and "red Indians." In the movie's most comic moment, Michael, spotting Gbatokai in the parking and assuming that he is a musician rather than an invited guest, assures him that no trumpeter would be needed for this party.
Thomas Bo Larsen gets the opportunity to turn on the emotions with an array of wildly melodramatic acting. The real talents of the picture, though, are Ulrich Thomsen, who must portray an obsessed son who seems at first like the most stable man of the group but turns into the catalyst for disastrous revelation; and renowed stage actor Henning Moritzen, who, like Oedipus, reflects a disbelief in the disclosures at first but turns into a sunken shell when the final bombshell is delivered.
Like producer Lars von Trier, director Vinterberg shows a preference for the hand-held camera as though to portray the party from the point of view of a guest who is snapping photos of the macabre celebration. The shaky hand may be troubling at first, but effectively conveys the chaos and clutter of the moment.
Some theorists believe that dramatic conflict works best when the skirmishing people are essentially locked together in a closed space and cannot leave until they work out their tensions. What gives the picture this touch of theatricality is that much of the action would not have taken place had the company of guests been able to escape to their cars. Since the wait staff hid the keys to enjoy the fun, we are reminded of Luis Bunuel's 1962 masterpie;ce, "The Exterminating Angel," in which guests at an elegant dinner party cannot bring themselves to leave and begin to starve and die after several days. Vinterberg's characters do eventually get to retreat, sadder and wiser for the experience. For some the ritual has been a cleansing experience bringing about the closure that will allow them to go on with their lives in a healthier manner. We, too, feel a sense of relief when Vinterberg brings closure to the picture, a work which quite effectually takes us behind closely guarded walls to explore the nature of the rich and successful.
Rated R. Running time: 105 minutes. (C) Harvey Karten 1998
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


This would be Netscape's last participation in RSS development for eight years. As RSS was being embraced by web publishers who wanted their feeds to be used on My.Netscape.Com and other early RSS portals, Netscape dropped RSS support from My.Netscape.Com in April 2001 during new owner AOL's restructuring of the company, also removing documentation and tools that supported the format.[8]
Two entities emerged to fill the void, with neither Netscape's help nor approval: The RSS-DEV Working Group and Dave Winer, whose UserLand Software had published some of the first publishing tools outside of Netscape that could read and write RSS.
In December 2000, Winer released RSS 0.92[12] a minor set of changes aside from the introduction of the enclosure element, which permitted audio files to be carried in RSS feeds and helped spark podcasting. He also released drafts of RSS 0.93 and RSS 0.94 that were subsequently withdrawn.[13]
In September 2002, Winer released a major new version of the format, RSS 2.0, that redubbed its initials Really Simple Syndication. RSS 2.0 removed the type attribute added in the RSS 0.94 draft and added support for namespaces. To preserve backward compatibility with RSS 0.92, namespace support applies only to other content included within an RSS 2.0 feed, not the RSS 2.0 elements themselves.[14] (Although other standards such as Atom attempt to correct this limitation, RSS feeds are not aggregated with other content often enough to shift the popularity from RSS to other formats having full namespace support.)
Because neither Winer nor the RSS-DEV Working Group had Netscape's involvement, they could not make an official claim on the RSS name or format. This has fueled ongoing controversy in the syndication development community as to which entity was the proper publisher of RSS.
One product of that contentious debate was the creation of an alternative syndication format, Atom, that began in June 2003.[15] The Atom syndication format, whose creation was in part motivated by a desire to get a clean start free of the issues surrounding RSS, has been adopted as IETF Proposed Standard RFC 4287.
In July 2003, Winer and UserLand Software assigned the copyright of the RSS 2.0 specification to Harvard's Berkman Center for Internet & Society, where he had just begun a term as a visiting fellow.[16] At the same time, Winer launched the RSS Advisory Board with Brent Simmons and Jon Udell, a group whose purpose was to maintain and publish the specification and answer questions about the format.[17]
In September 2004, Stephen Horlander created the now ubiquitous RSS icon (Feed-icon.svg) for use in the Mozilla Firefox browser.[18]
In December 2005, the Microsoft Internet Explorer team[19] and Microsoft Outlook team[20] announced on their blogs that they were adopting Firefox's RSS icon. In February 2006, Opera Software followed suit.[21] This effectively made the orange square with white radio waves the industry standard for RSS and Atom feeds, replacing the large variety of icons and text that had been used previously to identify syndication data.
In January 2006, Rogers Cadenhead relaunched the RSS Advisory Board without Dave Winer's participation, with a stated desire to continue the development of the RSS format and resolve ambiguities. In June 2007, the board revised their version of the specification to confirm that namespaces may extend core elements with namespace attributes, as Microsoft has done in Internet Explorer 7. According to their view, a difference of interpretation left publishers unsure of whether this was permitted or forbidden.


rather than so that white space is preserved on copy #} {{ record.details.comments }} {% if record.details.reason %} Reason: {{ record.details.reason }} {% endif %} {% endif %}
{{ record.details.comments }}
Reason: {{ record.details.reason }}


GO BACK TO PREVIOUS PAGE
we will se how youtube video is included
now we will see differnt types of list
- orderd list
- ol and li tags
- unorderd list
- ul and li
- discription list
- dl then dt then dd
- this is ul
- it is going to contain ul and li tags
- we even use a tag to make it a hyper link and any element can be made as a hyperlink
-
discription term
- this is to describe the term
- dd
- this is the actual description of the term that is to be defined


| Category | Position | Company | Location | Type | |
|---|---|---|---|---|---|
| Hospitality |
Waiter |
Jamie's Burger | Canada | Internship | |
| Law | Clerk |
Duan Law Firm | Detroit | Volunteer | |
| Health | Nurse Assistance |
Bobby's Memorial Hospital | New York | Volunteer | |
| Technology | Assistant Technician |
Amazon | Chicago | Part-Time | |
| Labor | NEW Environmental Custodian |
Evan and Victor Community Center | California | Full-Time |


Before Change
def make_input(self, batch_dict):
x = batch_dict["x"]
xch = batch_dict.get("xch")
y = batch_dict.get("y")
lengths = batch_dict.get("lengths")
if self.gpu:
x = x.cuda()
if xch is not None:
xch = xch.cuda()
if y is not None:
y = y.cuda()
return x, xch, lengths, y
After Change
example_dict[key] = example_dict[key].cuda()
// Allow us to track a length, which is needed for BLSTMs
if self.lengths_key is not None:
example_dict["lengths"] = torch.from_numpy(batch_dict[self.lengths_key])
if self.gpu:
example_dict["lengths"] = example_dict["lengths"].cuda()
y = batch_dict.get("y")
if y is not None:
y = torch.from_numpy(y)
if self.gpu is not None:


Inventory Management Specialist
NIKE-Memphis,TN
August 2016 to Present
Position of Hire: PMV Operator, 8/3/2016
PMV Opertor, 8/2016 to 8/2017
Promoted
Operation Specialist, 8/2017 to 12/2018
Promoted
Inventory Management Specialist, 1/2019 to Present
Broad Technical and process knowlege of Distrubution Center including material handling equipment.
Warehouse management systems such as XpDS,IBM,Access,Movers and additional physical DC processes.
Project Leadership coordition, data analysis, staffing, training, and security.
Emphasis on growing leadership skill through rotational leading, reviewing performances, and evaluting the development of the team.
Cross-departmental communication skills
Volunteer Roles
Safety Team member
Lead Trainer
First Responder
CERT(Community Emergency Response Team)
CPR and AED Certified
Turret Truck
Order Picker
Dock Stocker
Straddle


:a
1
:b
2
:c
3
:d
4
This module bootstraps the ground environment with basic language facilities.
(ignore? val)
applicative? combiner?
returns true if the value is _ ("ignore")
_ is a special value used to ignore a value when binding symbols.
(let [(fst & _) [1 2]] fst)
1
(sink? val)
applicative? combiner?
returns true if the value is a sink
A sink is a type that you can send values to using (emit).
(source? val)
applicative? combiner?
returns true if the value is a source
A source is a type that you can read values from using (next).
(list? val)
applicative? combiner?
returns true if the value is a linked list
A linked list is a pair whose second value is another list or empty.
(object? val)
applicative? combiner?
returns true if the value is an object
An object is a mapping from keywords to values.
(keyword? val)
applicative? combiner?
returns true if the value is a keyword
A keyword is a constant value representing a single word with hyphens (-) translated to underscores (_).
(applicative? val)
applicative? combiner?
returns true if the value is an applicative
An applicative is a combiner that wraps another combiner.
When an applicative is called, it evaluates its operands in the caller's evironment and passes them to the underlying combiner.
(operative? val)
applicative? combiner?
returns true if the value is an operative
An operative is a combiner that is given the caller's environment.
An operative may decide whether and how to evaluate its arguments. They are typically used to define new syntactic constructs.
(combiner? val)
applicative? combiner?
returns true if the value is a combiner
A combiner takes sequence of values as arguments and returns another value.
(path? val)
applicative? combiner?
returns true if the value is a path
A path is a reference to a file, directory, or command.
(empty? val)
applicative? combiner?
returns true if the value is an empty list, a zero-length string, an empty object, or null
ground
env?
ground environment please ignore
This value is only here to aid in developing prior to first release.
Fetching this binding voids your warranty.
<env>
(log val)
applicative? combiner?
writes a string message or other arbitrary value to stderr
Returns the given value.
(time form)
operative? combiner?
evaluates the form and prints the time it took
Returns the value returned by the form.
(wrap comb)
applicative? combiner?
construct an applicative from a combiner (typically an operative)
(bind env formals val)
applicative? combiner?
attempts to bind values in the env
Returns true if the binding succeeded, otherwise false.
(doc & symbols)
operative? combiner?
print docs for symbols
Prints the documentation for the given symbols resolved from the current environment.
With no arguments, prints the commentary for the current environment.
(comment form annotated)
operative? combiner?
record a comment
Splices one annotated value with another, recording commentary in the current environment.
Typically used by operatives to preserve commentary between scopes.
(commentary sym)
operative? combiner?
return the comment string associated to the symbol
Typically used by operatives to preserve commentary between scopes.
Use (doc) instead for prettier output.
(if cond yes no)
operative? combiner?
if then else (branching logic)
Evaluates a condition. If nil or false, evaluates the third operand. Otherwise, evaluates the second operand.
(- num & nums)
applicative? combiner?
subtract ys from x
If only x is given, returns the negation of x.
(next src & default)
applicative? combiner?
receive the next value from a source
If the stream has ended, no value will be available. A default value may be provided, otherwise an error is raised.
(reduce-kv f init kv)
applicative? combiner?
reduces an object
Takes a 3-arity function, an initial value, and an object. If the object is empty, the initial value is returned. Otherwise, calls the function for each key-value pair, with the current value as the first argument.
(reduce-kv assoc {:d 4} {:a 1 :b 2 :c 3})
{
:a
1
:b
2
:c
3
:d
4
}
(assoc obj & kvs)
applicative? combiner?
assoc[iate] keys with values in a clone of an object
Takes an object and a flat pair sequence alternating keywords and values.
Returns a clone of the object with the keyword fields set to their associated value.
(substring str start & end)
applicative? combiner?
returns a portion of a string
With one number supplied, returns the portion from the offset to the end.
With two numbers supplied, returns the portion between the first offset and the last offset, exclusive.
(object->list obj)
applicative? combiner?
returns a flat list alternating an object's keys and values
The returned list is the same form accepted by (map-pairs).
(list & values)
applicative? combiner?
construct a list from a sequence of values
(list 1 2 3)
(
1
2
3
)
(list* & args)
applicative? combiner?
prepend a sequence of values to a list given as the final argument
(rest (_ & r))
applicative? combiner?
return the second value in a pair, i.e. the rest of a linked list
(op formals eformal & body)
operative? combiner?
construct an operative
An operative is a combiner that is called with unevaluated arguments and the caller's dynamic environment.
Operatives are used to define new syntactic constructs.
(defop name formals eformal & body)
operative? combiner?
construct an operative and bind it to a symbol
Returns the bound symbol. Write a comment before (defop) to provide documentation.
(fn formals & body)
operative? combiner?
construct a function
Functions are applicative combiners which evaluate their arguments before passing them to an underlying operative.
(defn name formals & body)
operative? combiner?
construct a function and bind it to a symbol
Returns the bound symbol. Write a comment before (defn) to provide documentation.
(map f xs)
applicative? combiner?
returns a list containing the result of applying f to each member of xs
(map-pairs f ps)
applicative? combiner?
calls a function with alternating pairs in a flat list (i.e. with pairs ungrouped)
Takes 2-arity function and a flat pair sequence. Walks the sequence and calls f with 2 values at a time.
Raises an error if the list has uneven length.
(map-pairs cons [:a 1 :b 2 :c 3])
(
(:a & 1)
(:b & 2)
(:c & 3)
)
(let bindings & body)
operative? combiner?
binds values in a child environment
Takes a flat pair sequence alternating bindings and their values. Binds and evaluates each value in sequence, allowing later bindings to refer to earlier bindings.
Returns the result of evaluating the body in the child environment.
(provide symbols & body)
operative? combiner?
provide bindings to the current scope from a nested scope
Allows for modularity in code, selectively providing bindings while encapsulating bindings that they use.
(import source & symbols)
operative? combiner?
binds symbols in the current environment to their values from the source environment
(cond & clauses)
operative? combiner?
if-then-else with many clauses
Takes a flat pair sequence alternating tests to evaluate and an expression to evaluate if the test returns a truthy value.
Returns the result of the evaluated branch, or null if no tests were true.
By convention, :else is used as the final catch-all test, though any truthy value works.
(apply appv arg & opt)
applicative? combiner?
call an applicative's underlying operative with a list of arguments
An environment may be provided as the third argument. If not specified, the operative will be called in a new empty environment.
Used to call an applicative with pre-evaluated arguments, skipping the normal evaluation the applicative would perform prior to calling the underlying operative.
(-> x f & fs)
operative? combiner?
threads a value through forms
Calls the first form with the given value, passing the result to the second form, and so on, returning the final value.
A form may be a list or a single value. For a list, the value is inserted before the second value, becoming the first argument. For a single value, it is wrapped in a list with the value as the single argument.
(list->object kwargs)
applicative? combiner?
constructs an object from a list of flat keyword/value pairs
(last stream & default)
applicative? combiner?
returns the last value from the stream
As with (next), a default may be provided to be returned when the stream is empty. If not provided, an error will be raised if the stream is empty.
(arg & vals)
applicative? combiner?
returns a structure which will join the given values into a single string value
Used to concatenate paths with string values to be passed as an argument to a workload.
(with-entrypoint workload & entrypoint)
applicative? combiner?
sets the :entrypoint field of the workload
($ cmd & args)
operative? combiner?
constructs a workload with args set as :args
Symbol arguments are automatically converted to strings. Symbols beginning with $ are resolved to their binding with the leading $ removed.
*default-platform*
object?
the default platform for workloads that configure an image
{
:os
"linux"
}
(response-from workload source)
applicative? combiner?
sets the :response field of the workload
If source is :stdout, sets it to {:stdout true}. If source is :exit, sets it to {:exit-code true}. If source is a path?, sets it to {:file source}.
(with-mount workload source target)
applicative? combiner?
appends a mount to the :mounts field of the workload
(with-env-var workload name value)
applicative? combiner?
inserts an env var and value into the :env field of the workload
TODO: append, add in stable order
(not x)
applicative? combiner?
negates the given bool-ish value
Returns true for false and null. Returns false otherwise.
(not true)
false
(not null)
true
(not false)
true
(load (.strings))
info loading {"workload": "<workload: 9bd3b8606144f1b30c031e9fa327879b0bd32959>"}
<env>
(load (.concourse))
info loading {"workload": "<workload: e5127b2fb0a6aa915b32dd6807dd3fa285ae7168>"}info loading {"workload": "<workload: f5a12ef6a0fb81a1896ff193c4f6f4308f5b2e13>"}
<env>
*default-config*
object?
the default configuration, if none is supplied on *stdin*
{
:platforms
{
:linux
{
:os
"linux"
}
}
:types
{
:docker-image
"concourse/docker-image-resource"
:git
"concourse/git-resource"
:registry-image
"concourse/registry-image-resource"
:time
"concourse/time-resource"
}
}
(resource type source)
applicative? combiner?
constructs a resource commandline interpreter
If type is a keyword, it is mapped to an image via :types in the module configuration.
Otherwise, it is passed along to `in-image`.
(run-task config-path & kwargs)
applicative? combiner?
run a task with the given parameters
The :inputs param provides as a mapping from name to workload path.
Returns an object with :outputs bound to a mapping from name to workload path, and :result bound to the workload's stream.
bind symbols to values in the current env


|
ATR ROS2 Interfaces Project
Documentation of the ROS Packages
|
Provides a ros2 server and a redis client to publish a polygon message. More...
#include <Ros2RedisPolygon.h>
Public Member Functions | |
| Ros2RedisPolygon () | |
| Construct a new Ros 2 Redis Polygon object. More... | |
| ~Ros2RedisPolygon () | |
| Terminates the client connection to the Redis DB and destroys the redis objects. More... | |
Provides a ros2 server and a redis client to publish a polygon message.
| ros2redis::Ros2RedisPolygon::Ros2RedisPolygon | ( | ) |
Construct a new Ros 2 Redis Polygon object.
| ros2redis::Ros2RedisPolygon::~Ros2RedisPolygon | ( | ) |
Terminates the client connection to the Redis DB and destroys the redis objects.


{% extends 'foundation_tenant/base.html' %} {% load staticfiles i18n compress %} {% block content %} {% compress js inline %} {% include 'tenant_team/details/js.html' %} {% endcompress %}
{% trans 'A temporary password has been generated for this employee. Please give this password to the employee ask them to change their password once they login with it.' %}


#include <Ioctl.h>
Public Attributes | |
| ULONG | devID |
| ULONG | busNum |
| USHORT | deviceNum |
| USHORT | functionNum |
| ULONG | UINumber |
| bool | hasDmaBuf |
| ULONG | DmaBufSize |
| bool | DmaAddr64 |
| ULONG | DmaPhyAddrHi |
| ULONG | DmaPhyAddrLo |
| char | DriverName [MAX_DRIVER_NAME_LEN] |
Definition at line 32 of file lscpcie2/Ioctl.h.
|
|
PCI bus number board located on Definition at line 37 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(), and LatticeSemi_PCIe::SFIF::SFIF(). |
|
|
PCI device number assigned to board Definition at line 38 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(), and LatticeSemi_PCIe::SFIF::SFIF(). |
|
|
board number of specific device Definition at line 35 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(). |
|
|
true if the address mode is 64 bit (almost always 32 bit) Definition at line 45 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(). |
|
|
size in bytes of said buffer Definition at line 44 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(), and LatticeSemi_PCIe::SFIF::SFIF(). |
|
|
Upper 32 bits of 64 bit address for 64 bit mode Definition at line 46 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(). |
|
|
DMA bus address to be programmed into device Definition at line 47 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(), and LatticeSemi_PCIe::SFIF::SFIF(). |
|
|
version and name compiled into driver Definition at line 50 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(). |
|
|
our function number, which is always 0 (no multi-function Definition at line 39 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(), and LatticeSemi_PCIe::SFIF::SFIF(). |
|
|
true if DMA buffer has been allocated by driver Definition at line 43 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(). |
|
|
motherboard slot number (not always implemented/valid) Definition at line 40 of file lscpcie2/Ioctl.h. Referenced by LatticeSemi_PCIe::LSCPCIe2_IF::getPCIExtraInfoStr(). |


As clued by the title and flavortext, these Slitherlink variants take place on a Möbius strip. Each strip should be joined with a half twist such that red and blue arrows line up. Notice that when solving on a Möbius strip, the Slitherlink loop may or may not be contractible. So in contrast with regular Slitherlinks where the number of horizontal segments in each vertical must always be even, the number of horizontal segments here may either always be even or always be odd. Three Slitherlink variants are given and their solutions are shown below.
While solving the Slitherlinks, we might notice that there are additional diagonal red and blue lines that have not yet been used. When the Slitherlinks are printed and assembled as Möbius strips, each red line is on the opposite side of a blue lines. The type of line dash pattern on the red lines indicate they are mountain folds and the line dash patterns on the blue lines indicate they are valley folds. Each Möbius strip can be folded along the 3 folds and flattened to form a shape similar to the universal recycling symbol. When the Möbius strips are folded and flattened, the solution the Slitherlink traces out a character on each flattened face. Below is a color coded Möbius strip and the flattened faces with the Slitherlink solutions traced.
This string of characters can be parsed as per the enumeration given by the blanks at the bottom of the puzzle page. Doing so gives us MU FUNC OF LENGTH MOD 3. Here, MU FUNC refers to the thematic Möbius function which is often denoted with the Greek letter mu. The Möbius function takes as input positive integers and returns either 0, 1, or -1. Applying the Möbius function to the length of loop in each Slitherlinks solution and taking the value modulo 3 gives us the following values.
| Loop Length | Möbius function value modulo 3 |
|---|---|
| 86 | 1 |
| 118 | 1 |
| 138 | 2 |
| 128 | 0 |
| 122 | 1 |
| 154 | 2 |
| 114 | 2 |
| 124 | 0 |
| 130 | 2 |
Each Slitherlink puzzle extracts to either 0, 1, or 2 and there are 3 Slitherlink puzzles per Slitherlink variant. This suggests extraction via ternary. Converting the numbers 112, 012, 202 in ternary produces the answer NET.


Contributing to Jetty
Comments, contributions, feedback, bugs,
testing, sponsorship etc. are all
welcome, please....
Jetty Discuss
This is the mailing list where much of the public discussion regarding development issues occurs. If you are interested in contributing to the Jetty project, this is a must read.
Jetty Discuss
Jetty Tasks
The official list of subprojects and tasks is kept on Source Forge.
sourceforge.net/pm/?group_id=7322
Jetty CVS (Concurrent Versions System)
As open source software, a developer can download, modify, and contribute to the active code base of Jetty server. The Jetty code base resides in a CVS repository hosted by Source Forge.
To learn more about CVS, check out www.cvshome.org/new_users.html .
To go directly to the Jetty CVS page on Source Forge, click sourceforge.net/cvs/?group_id=7322 .


Perfect Prime
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Netflix Version


We specialize in web, mobile, desktop app design & development and other-related services
Mujaware is software business entity that specializes on mobile app designing, mobile app development, web app designing, web app development. We started operating several years ago and have gathered more in experience in working with individual, group, organisation and companies in developing apps that bring great value to their clients and the users. We have prided ourself on the team that have done great jobs in bringing us to this level of professionalism.
Our team comprises of local and foreign web designers, web developers, mobile app developer and mobile app designer. With this team we are able to discern ourselves remarkably from our competitors in many ways.
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Sqlalchemy Model:AssetPermission
permissions on assets granted to users
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| asset_id | INTEGER | asset reference id | foreign |
| user_id | INTEGER | user's id | foreign |
| can_update | BOOLEAN | if the user can update the asset | n/a |
| can_delete | BOOLEAN | if the user can delete the asset | n/a |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_asset_permissions_user_id_users | user_id |
| fk_asset_permissions_asset_id_asset_storage | asset_id | |
| PrimaryKeyConstraint | pk_asset_permissions | id |
Sqlalchemy Model:AssetStorage
holds references to assets uploaded by users
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| ref_id | VARCHAR | unique id for file | n/a |
| title | VARCHAR | file title with extension | n/a |
| url | VARCHAR | file url | n/a |
| date_added | DATETIME | row timestamp | n/a |
| date_updated | DATETIME | timestamp for last updated | n/a |
| added_by_id | INTEGER | None | foreign |
| updated_by_id | INTEGER | fk for user's table | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_asset_storage_updated_by_id_users | updated_by_id |
| fk_asset_storage_added_by_id_users | added_by_id | |
| PrimaryKeyConstraint | pk_asset_storage | id |
| UniqueConstraint | uq_asset_storage_ref_id | ref_id |
Sqlalchemy Model:Entity
None
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| name | VARCHAR | entity name | n/a |
| description | VARCHAR | short discription of the entity | n/a |
| Type | Name | Columns |
|---|---|---|
| PrimaryKeyConstraint | pk_entities | id |
| UniqueConstraint | uq_entities_name | name |
Sqlalchemy Model:ErrorLog
None
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| code | VARCHAR | Application Error identifier code | n/a |
| user_id | INTEGER | logged in user | foreign |
| message | VARCHAR | error message | n/a |
| stack_trace | VARCHAR | error stack trace | n/a |
| date_added | DATETIME | row timestamp | n/a |
| added_by_id | INTEGER | None | foreign |
| session_id | INTEGER | None | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_error_log_session_id_sessions | session_id |
| fk_error_log_added_by_id_users | added_by_id | |
| fk_error_log_user_id_users | user_id | |
| PrimaryKeyConstraint | pk_error_log | id |
Sqlalchemy Model:Organization
None
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| name | VARCHAR | Unique name of Organization | n/a |
| description | VARCHAR | Short description of organization | n/a |
| addr_line1 | VARCHAR | Address line 1 | n/a |
| addr_line2 | VARCHAR | Address line 1 | n/a |
| country | VARCHAR | Country's ISO code | n/a |
| city | VARCHAR | City's name | n/a |
| contact_email | VARCHAR | n/a | |
| contact_phone | VARCHAR | n/a | |
| contact_user_id | INTEGER | None | foreign |
| slug | VARCHAR | identifier slug for organization | n/a |
| date_added | DATETIME | row timestamp | n/a |
| date_updated | DATETIME | timestamp for last updated | n/a |
| added_by_id | INTEGER | None | foreign |
| updated_by_id | INTEGER | fk for user's table | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_organizations_contact_user_id_users | contact_user_id |
| fk_organizations_added_by_id_users | added_by_id | |
| fk_organizations_updated_by_id_users | updated_by_id | |
| PrimaryKeyConstraint | pk_organizations | id |
| UniqueConstraint | uq_organizations_slug | slug |
| uq_organizations_name | name |
Sqlalchemy Model:OrganizationDepartment
None
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| org_id | INTEGER | foreign | |
| name | VARCHAR | department's name | n/a |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_organization_departments_org_id_organizations | org_id |
| PrimaryKeyConstraint | pk_organization_departments | id |
Sqlalchemy Model:Project
holds references to assets uploaded by users
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| cancelled_at | DATETIME | timestamp for cancellation of record | n/a |
| title | VARCHAR | Project's Title | n/a |
| description | VARCHAR | Description for created project | n/a |
| slug | VARCHAR | unique project's slug | n/a |
| org_id | INTEGER | foreign | |
| is_completed | BOOLEAN | flags the project as complete | n/a |
| is_public | BOOLEAN | flags the project as public | n/a |
| start_date | DATE | project's start date | n/a |
| time_frame | INTEGER | estimated time-frame for project in days | n/a |
| logo | VARCHAR | url to project's logo | n/a |
| date_added | DATETIME | row timestamp | n/a |
| date_updated | DATETIME | timestamp for last updated | n/a |
| added_by_id | INTEGER | None | foreign |
| updated_by_id | INTEGER | fk for user's table | foreign |
| cancelled_by_id | INTEGER | fk for user's table | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_projects_org_id_organizations | org_id |
| fk_projects_updated_by_id_users | updated_by_id | |
| fk_projects_added_by_id_users | added_by_id | |
| fk_projects_cancelled_by_id_users | cancelled_by_id | |
| PrimaryKeyConstraint | pk_projects | id |
| UniqueConstraint | uq_projects_slug | slug |
Sqlalchemy Model:ProjectAsset
references for assets available to projects
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| project_id | INTEGER | None | foreign |
| asset_id | INTEGER | None | foreign |
| date_added | DATETIME | row timestamp | n/a |
| date_updated | DATETIME | timestamp for last updated | n/a |
| added_by_id | INTEGER | None | foreign |
| updated_by_id | INTEGER | fk for user's table | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_project_asset_updated_by_id_users | updated_by_id |
| fk_project_asset_asset_id_asset_storage | asset_id | |
| fk_project_asset_project_id_projects | project_id | |
| fk_project_asset_added_by_id_users | added_by_id | |
| PrimaryKeyConstraint | pk_project_asset | id |
Sqlalchemy Model:ProjectUser
holds references to users assigned to a project
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| cancelled_at | DATETIME | timestamp for cancellation of record | n/a |
| project_id | INTEGER | None | foreign |
| user_id | INTEGER | None | foreign |
| is_active | BOOLEAN | flags the validity of user in the project | n/a |
| role_id | SMALLINT | user's role in this project | n/a |
| date_added | DATETIME | row timestamp | n/a |
| date_updated | DATETIME | timestamp for last updated | n/a |
| added_by_id | INTEGER | None | foreign |
| updated_by_id | INTEGER | fk for user's table | foreign |
| cancelled_by_id | INTEGER | fk for user's table | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_project_users_user_id_users | user_id |
| fk_project_users_cancelled_by_id_users | cancelled_by_id | |
| fk_project_users_project_id_projects | project_id | |
| fk_project_users_added_by_id_users | added_by_id | |
| fk_project_users_updated_by_id_users | updated_by_id | |
| PrimaryKeyConstraint | pk_project_users | id |
Sqlalchemy Model:Role
contains basic roles for the aplication
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| name | VARCHAR | role name | n/a |
| description | VARCHAR | short discription of the role | n/a |
| Type | Name | Columns |
|---|---|---|
| PrimaryKeyConstraint | pk_roles | id |
Sqlalchemy Model:RoleEntityPermission
None
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| entity_id | INTEGER | entity's table foreign key | foreign |
| role_id | INTEGER | role's table foreign key | foreign |
| can_create | BOOLEAN | can create flag | n/a |
| can_edit | BOOLEAN | can edit flag | n/a |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_role_entity_permissions_role_id_roles | role_id |
| fk_role_entity_permissions_entity_id_entities | entity_id | |
| PrimaryKeyConstraint | pk_role_entity_permissions | id |
Sqlalchemy Model:Session
table for user's active sessions
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| user_id | INTEGER | user's table foreign key | foreign |
| token | VARCHAR | session's token | n/a |
| ip_address | VARCHAR | machine's ip address | n/a |
| platform | VARCHAR | machine's os platform | n/a |
| browser | VARCHAR | registered browser | n/a |
| active | BOOLEAN | None | n/a |
| slug | VARCHAR | unique's slug identifier | n/a |
| created_at | TIMESTAMP | session's creation date | n/a |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_sessions_user_id_users | user_id |
| PrimaryKeyConstraint | pk_sessions | id |
| UniqueConstraint | uq_sessions_slug | slug |
Sqlalchemy Model:User
Holds users' data
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| username | VARCHAR | User's identifier | n/a |
| is_active | BOOLEAN | Denotes active users | n/a |
| password | VARCHAR | Password hash | n/a |
| VARCHAR | User's personal unique email | n/a | |
| photo | VARCHAR | User's avatar url | n/a |
| phone | VARCHAR | Contact number | n/a |
| first_name | VARCHAR | First Name | n/a |
| last_name | VARCHAR | Last Name | n/a |
| manager_id | INTEGER | None | foreign |
| date_added | DATETIME | row timestamp | n/a |
| date_updated | DATETIME | timestamp for last updated | n/a |
| added_by_id | INTEGER | None | foreign |
| updated_by_id | INTEGER | fk for user's table | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_users_manager_id_users | manager_id |
| fk_users_added_by_id_users | added_by_id | |
| fk_users_updated_by_id_users | updated_by_id | |
| PrimaryKeyConstraint | pk_users | id |
| UniqueConstraint | uq_users_email | |
| uq_users_username | username |
Sqlalchemy Model:UserAffiliation
None
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| user_id | INTEGER | foreign | |
| org_id | INTEGER | foreign | |
| department_id | INTEGER | foreign | |
| position_id | INTEGER | n/a |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_user_affiliation_department_id_organization_departments | department_id |
| fk_user_affiliation_org_id_organizations | org_id | |
| fk_user_affiliation_user_id_users | user_id | |
| PrimaryKeyConstraint | pk_user_affiliation | id |
Sqlalchemy Model:UserEntityPermission
None
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| entity_id | INTEGER | entity's table foreign key | foreign |
| user_id | INTEGER | user's table foreign key | foreign |
| can_create | BOOLEAN | can create flag | n/a |
| can_edit | BOOLEAN | can edit flag | n/a |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_user_entity_permissions_entity_id_entities | entity_id |
| fk_user_entity_permissions_user_id_users | user_id | |
| PrimaryKeyConstraint | pk_user_entity_permissions | id |
Sqlalchemy Model:UserRoles
holds user roles pairs
| Database Field Name | Data Type | Description | Primary/Foreign |
|---|---|---|---|
| id | INTEGER | Unique row identifier | primary |
| user_id | INTEGER | user's table foreign key | foreign |
| role_id | INTEGER | role's table foreign key | foreign |
| Type | Name | Columns |
|---|---|---|
| ForeignKeyConstraint | fk_user_roles_role_id_roles | role_id |
| fk_user_roles_user_id_users | user_id | |
| PrimaryKeyConstraint | pk_user_roles | id |


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| vec-rep {vctrs} | R Documentation |
vec_rep()
repeats an entire vector a set number of times
.
vec_rep_each()
repeats each element of a vector a set number of times
.
vec_unrep()
compresses a vector with repeated values. The repeated values
are returned as a key
alongside the number of times
each key is
repeated.
vec_rep(x, times) vec_rep_each(x, times) vec_unrep(x)
x |
A vector. |
times |
For For |
Using vec_unrep()
and vec_rep_each()
together is similar to using
base::rle()
and base::inverse.rle()
. The following invariant shows
the relationship between the two functions:
compressed <- vec_unrep(x) identical(x, vec_rep_each(compressed$key, compressed$times))
There are two main differences between vec_unrep()
and base::rle()
:
vec_unrep()
treats adjacent missing values as equivalent, while rle()
treats them as different values.
vec_unrep()
works along the size of x
, while rle()
works along its
length. This means that vec_unrep()
works on data frames by compressing
repeated rows.
For vec_rep()
, a vector the same type as x
with size
vec_size(x) * times
.
For vec_rep_each()
, a vector the same type as x
with size
sum(vec_recycle(times, vec_size(x)))
.
For vec_unrep()
, a data frame with two columns, key
and times
. key
is a vector with the same type as x
, and times
is an integer vector.
# Repeat the entire vector vec_rep(1:2, 3) # Repeat within each vector vec_rep_each(1:2, 3) x <- vec_rep_each(1:2, c(3, 4)) x # After using `vec_rep_each()`, you can recover the original vector # with `vec_unrep()` vec_unrep(x) df <- data.frame(x = 1:2, y = 3:4) # `rep()` repeats columns of data frames, and returns lists rep(df, each = 2) # `vec_rep()` and `vec_rep_each()` repeat rows, and return data frames vec_rep(df, 2) vec_rep_each(df, 2) # `rle()` treats adjacent missing values as different y <- c(1, NA, NA, 2) rle(y) # `vec_unrep()` treats them as equivalent vec_unrep(y)


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Welcome to Baltimore, Mary!
Review of Pecker (1998)
"Life isn't anything if you're not obsessed," declares young Pecker (Edward Furlong). He ought to know. He's obsessed with taking photos of everything he sees, froom a burger sizzling in griddle grease to rats rutting in the trash. The movie opens in an almost sitcom fashion as we are introduced to all the other obsessed people in his life.
Pecker holds a photo show in the greasy burger joint where he works, and art dealer Rorey Wheeler (the ubiquitous Lili Taylor) walks in and turns him into a star. She holds a show of his artwork up in New York, and has her sights set on a show at the Whitney.
In equally sitcom fashion, there is a trip made up to his gallery show, by all the aforementioned principals. Their homey and homespun obsesses Ozzie-and-Harrietness is contrasted as fundamentally good and pure next to the pretentious New York art scene. Mom has the homeless in for dinner while his shoplifting buddy gets unheard-of action from not one but two girls--being an instant celebrity just for appearing as a photo subject at a gallery.
Fame and fortune turns them all off, and turns their lives upside down. Pecker ensues by eschewing New York and his opportunities by only having his art shows in Baltimore. A lot of this clearly comes from writer and director John Waters's own experience from dealing with the New York art world, and having home in both cities. But Baltimore is home and where his heart is. And this is part of why the movie fails. The heavy handed treatment of Baltimore is good and real and New York is bad and pretentious makes everything a little stilted. It's like a campy version of *Sunrise*.
But there are lots of wonderful little John Waters moments and dialogue throughout the film that alleviate the sitcom stylings and more black-and-white nature of the two-city rivalry. There are some great lines, too: "I beg of you, do no become an asshole," "Public hair causes crime," and Rorey telling Pecker, "How can you be so kind and gentle and still have talent?"
And while the stiltedness is oppressive, his love of Baltimore is not. He clearly loves his home town. I haven't seen so many scenes on public buses since *A Bronx Tale*. The distinctly nondescript skyline of Baltimore is featured prominently. A pit beef stand and a lesbian strip joint called "The Pelt Room" are shown with great love and affection, as are most of the "little places" and "little people" in the film.
One of the best scenes: Pecker and Shelly make out in a voting booth while an unnaturally obsessed election worker seeks out the troublemakers disrespecting the sanctity of the polling process. When disturbed, Shelly retorts "I'm trying to VOTE!"
*Pecker*. Not one of John Waters's best, but still very enjoyable. Be warned: Hairspray it ain't. Cameo appearances by Patty Hearst, Greg Gorman, and photographer Cindy Sherman. Original music by Stewart Copeland.
More movie reviews by Seth Bookey, with graphics, can be found at http://www.geocities.com/Athens/2679/kino.html
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
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.
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Related links: index of all rec.arts.movies.reviews reviews


| chipKIT Sketch Help |
Once the plug-in is installed in MPLAB X IDE, you need to connect the chipKIT Max32 board to the MPLAB ICD 3 in-circuit debugger.Connect the MPLAB ICD 3 using the SIL adapter and cable to the chipKIT Max32 board. Connect the MPLAB ICD 3 to the PC using the USB cable. Connect power to the chipKIT Max32 board. See Figure: Connect Board to MPLAB ICD 3.Figure: Connect Board to MPLAB ICD 3
|
Microchip Support
Help Updated: 2017-04-13 14:25:13Z
Help Page: 14
|


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Fourth year computer science student at Rochester Institute of Technology. Seeking opportunities relating to computer science and software engineering. Looking to combine skill in the field of programming with interests in the high tech field.
My high school education is where I began my interest in my programming by taking both Honors and AP Computer science as well as interning with the IT department during my study periods.
Expected to graduate in Spring 2019, I have studied at this school where I have had the opportunity to learn many languages and practices while being given the opportunity to gain work experience before graduation.
I was responsible for assisting in basic computer repairs along with the moving and setup of computers, network cables, and servers during a company move. I was also responsible for the indexing of spare computers and rebuilding and updating the hardware of company computers.
While a student intern, I was responsible for the fixing of common computer issues, being on call, repair and the setup of other technical system. I also was responsible for spearheading the pilot program of implementing a one-to-one ratio of personal computers to students for academic purposes. This involved the research of which computers to order, what software and restrictions to implement, upgrading of current hardware such as ethernet cabling, routers and firewalls, and comparing the costs to the advantages. This program was accepted an implemented for the academic year of 2014 /15.
Proposed, Designed, Tested, and Deployed an internal price comparison application. Built with Django, this web-application is able to be accessed internally and is a centralized hub for comparing item prices with competitor's list prices. Features include statistics, multiple integrated competitors, spreadsheet upload and export, and comparison results.
Fullstack software engineer with a focus on web application development. Here I have applied the skills gained from my education and expanded upon them while growing as a developer. I have worked on a variety of web application development projects that have helped hone my Java, Javascript, and HTML skills while learning more about SQL, Angular, and more.