public class RoadElement
extends java.lang.Object
| Modifier and Type | Class and Description |
|---|---|
static class |
RoadElement.Attribute
Defined values for different road attributes
|
static class |
RoadElement.FormOfWay
Form of Way Types
|
static class |
RoadElement.PluralType
Plural type identifies when a Junction is made up of multiple Road Elements.
|
| Modifier and Type | Method and Description |
|---|---|
boolean |
equals(java.lang.Object obj) |
java.util.EnumSet<RoadElement.Attribute> |
getAttributes()
Gets the road attributes.
|
int |
getAverageSpeed()
Gets the average speed of the road element.
|
RoadElement.FormOfWay |
getFormOfWay()
Gets the form of way.
|
java.util.List<GeoCoordinate> |
getGeometry() |
double |
getGeometryLength()
Returns the length of the polyline associated with this RoadElement in meters.
|
int |
getNumberOfLanes()
Gets number of lanes in this road element.
|
RoadElement.PluralType |
getPluralType()
Gets the plural type of the road element.
|
java.lang.String |
getRoadName()
Gets the name of the road element.
|
java.lang.String |
getRouteName()
Gets the route name of the road element.
|
float |
getSpeedLimit()
Gets the speed limit.
|
java.util.Date |
getStartTime()
Gets the (estimated) time at which this road element starts.
|
int |
hashCode() |
boolean |
isPedestrian()
Checks, if the road is allowed only for pedestrians.
|
boolean |
isPlural()
Tests if the road element is plural.
|
public java.util.List<GeoCoordinate> getGeometry()
public java.util.EnumSet<RoadElement.Attribute> getAttributes()
RoadElement.Attribute
public RoadElement.FormOfWay getFormOfWay()
RoadElement.FormOfWay
public boolean isPlural()
public RoadElement.PluralType getPluralType()
RoadElement.PluralType
public java.lang.String getRoadName()
public java.lang.String getRouteName()
public float getSpeedLimit()
public int getAverageSpeed()
public int getNumberOfLanes()
public boolean isPedestrian()
public java.util.Date getStartTime()
RouteOptions
associated with this road element, than
the time is relative to the system time when the route calculation took place. Otherwise, the
times are relative to the specified departure time.null
if not availableRouteOptions.setTime(Date, TimeType)
public double getGeometryLength()
public int hashCode()
hashCode
in class java.lang.Object
public boolean equals(java.lang.Object obj)
equals
in class java.lang.Object


The following demo is using all of the default LiveFilter options.
The following demo is using custom settings which can be supplied by the user.
| Film Name | Released |
|---|---|
| The Shawshank Redemption | 1994 |
| The Godfather | 1972 |
| The Godfather: Part II | 1974 |
| Il buono, il brutto, il cattivo. | 1966 |
| Pulp Fiction | 1994 |
| The Dark Knight | 2008 |
| Schindler's List | 1993 |
| One Flew Over the Cuckoo's Nest | 1975 |
| 12 Angry Men | 1957 |
| Star Wars: The Empire Strikes Back | 1980 |
| Casablanca | 1942 |
| Star Wars: A New Hope | 1977 |
| Shichinin no samurai | 1954 |
| Lord of the Rings: The Return of the King | 2003 |
| Goodfellas | 1990 |
| Rear Window | 1954 |
| Cidade de Deus | 2002 |
| Raiders of the Lost Ark | 1981 |
| C'era una volta il West | 1968 |
| Lord of the Rings: The Fellowship of the Ring | 2001 |
| Fight Club | 1999 |
| The Usual Suspects | 1995 |
| Psycho | 1960 |
| The Silence of the Lambs | 1991 |
| Sunset Blvd. | 1950 |
| Dr. Strangelove | 1964 |
| The Matrix | 1999 |
| Momento | 2000 |
| North by Northwest | 1959 |
| It's a Wonderful Life | 1946 |
| Citizen Kane | 1941 |
| Se7en | 1995 |
| Lord of the Rings: The Two Towers | 2002 |
| Léon | 1994 |
| Apocolypse Now | 1979 |
| American Beauty | 1999 |
| Taxi Driver | 1976 |
| American History X | 1998 |
| Lawrence of Arabia | 1962 |
| Vertigo | 1958 |
| Wall-E | 2008 |
| Forrest Gump | 1994 |
| Le fabuleux destin d'Amélie Poulain | 2001 |
| M | 1931 |
| Double Indemnity | 1944 |
| To Kill a Mockingbird | 1962 |
| Alien | 1979 |
| A Clockwork Orange | 1971 |
| The Treasure of Sierra Madre | 1948 |
| This one is ignored. | 9000 |
| This one is ignored. | 9000 |
| This one is ignored. | 9000 |
| This one is ignored. | 9000 |


Warm-starts a model using the given settings.
tf.compat.v1.train.warm_start( ckpt_to_initialize_from, vars_to_warm_start='.*', var_name_to_vocab_info=None, var_name_to_prev_var_name=None )
If you are using a tf.estimator.Estimator, this will automatically be called during training.
ckpt_to_initialize_from
: [Required] A string specifying the directory with
checkpoint file(s) or path to checkpoint from which to warm-start the
model parameters.vars_to_warm_start
: [Optional] One of the following:
A regular expression (string) that captures which variables to warm-start (see tf.compat.v1.get_collection). This expression will only consider variables in the TRAINABLE_VARIABLES collection -- if you need to warm-start non_TRAINABLE vars (such as optimizer accumulators or batch norm statistics), please use the below option.
Variable
objects at the call site, please use the above option.None
, in which case only TRAINABLE variables specified in
var_name_to_vocab_info
will be warm-started.Defaults to '.*'
, which warm-starts all variables in the
TRAINABLE_VARIABLES collection. Note that this excludes variables such
as accumulators and moving statistics from batch norm.
* var_name_to_vocab_info
: [Optional] Dict of variable names (strings) to
tf.estimator.VocabInfo
. The variable names should be "full" variables,
not the names of the partitions. If not explicitly provided, the variable
is assumed to have no (changes to) vocabulary.
* var_name_to_prev_var_name
: [Optional] Dict of variable names (strings) to
name of the previously-trained variable in ckpt_to_initialize_from
. If
not explicitly provided, the name of the variable is assumed to be same
between previous checkpoint and current model. Note that this has no
effect on the set of variables that is warm-started, and only controls
name mapping (use vars_to_warm_start
for controlling what variables to
warm-start).
ValueError
: If the WarmStartSettings contains prev_var_name or VocabInfo
configuration for variable names that are not used. This is to ensure
a stronger check for variable configuration than relying on users to
examine the logs.


Each time I go to save my emblem that I used a code to get it doesn't save right. It shows me the emblem but then once I try an save it, it says "IMAGE_NOT_SAVED" It shows the emblem in the creator window but not up top. I have no idea how to fix this.
ORFK
Global Moderator
well... we are "Better Battlelog", not DICE and/or ESN.
DICE / ESN are companies from EA, who created Battlelog, the Emblem Editor and, shure, Battlefield. Ask them in their forums, we cant do here anything.
Meaurk
Global Moderator
It is indeed a Battlelog bug. We can't fix the bug, and there is no fix for it, yet. However you can keep clicking the save button and eventually it'll work. :)


My first paragraph.
Jump to Chapter 4 This is a linksMy Bonnie lies over the ocean. My Bonnie lies over the sea. My Bonnie lies over the ocean. Oh, bring back my Bonnie to me.
This is a paragraph.
If target="_blank", the link will open in a new browser window or tab.
_self - Default. Opens the document in the same window/tab as it was clicked
_blank - Opens the document in a new window or tab
_parent - Opens the document in the parent frame
_top - Opens the document in the full body of the window
| Firstname | Lastname | Age |
|---|---|---|
| Jill | Smith | 50 |
| Eve | Jackson | 94 |
| John | Doe | 80 |
London is the capital of England.
Paris is the capital of France.
Tokyo is the capital of Japan.
JavaScript can change the style of an HTML element.


'Tk' is the absolute root of the application, it is the first widget that needs to be instantiated and the GUI will shut down when it is destroyed.
 It is possible to create many 'Toplevel' windows. They are not separate processes; if the program exits, all 'Toplevel' windows are erased.
import tkinter as tk root = tk.Tk() # we should start from root root.title("root") # Create root window contents... # In Button, command=root.quit kills all windows. top = tk.Toplevel() #top = tk.Toplevel(root) # using explicit parent top.title("top") # Create top window contents... # In Button, command=top.destroy only kills the current top window. root.mainloop() # run the tkinter event loop #top.mainloop() # also works


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Metrics for /UglyTriviaGame
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Eclipe Metrics
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Lack of Cohesion in Methods (Henderson-Sellers)
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Produced by
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on Wed Jun 08 09:17:44 CDT 2005


Finish setting Up your profile for better experience, start enjoying Happy Tunez now.
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Take this test to find out what you're good at and where you can improve. We'll use your results to find you learning opportunities.


⚠ Documentation is version-specific: This page was generated for ScottPlot 4.1.4-beta
Additional documentation and more version-specific cookbooks are on the ScottPlot Website
Scatter plots have paired X/Y points.
var plt = new ScottPlot.Plot(600, 400);
// sample data
double[] xs = DataGen.Consecutive(51);
double[] sin = DataGen.Sin(51);
double[] cos = DataGen.Cos(51);
// plot the data
plt.AddScatter(xs, sin);
plt.AddScatter(xs, cos);
// customize the axis labels
plt.Title("ScottPlot Quickstart");
plt.XLabel("Horizontal Axis");
plt.YLabel("Vertical Axis");
plt.SaveFig("quickstart_scatter.png");
Signal plots have evenly spaced Y points. Signal plots are very fast and can interactively display millions of data points. There are many different types of plottable objects, each serving a different purpose.
var plt = new ScottPlot.Plot(600, 400);
double[] values = DataGen.RandomWalk(1_000_000);
plt.AddSignal(values, sampleRate: 48_000);
plt.Title("One Million Points");
plt.SaveFig("quickstart_signal.png");
Axis labels and limits can be customized
var plt = new ScottPlot.Plot(600, 400);
double[] time = DataGen.Consecutive(51);
double[] voltage = DataGen.Sin(51);
plt.AddScatter(time, voltage);
// Axes can be customized
plt.XAxis.Label("Time (milliseconds)");
plt.YAxis.Label("Voltage (mV)");
plt.XAxis2.Label("Important Experiment");
// Set axis limits to control the view
plt.SetAxisLimits(-20, 80, -2, 2);
plt.SaveFig("quickstart_axis.png");
You can create a plot manually, then add it to the plot with Add(). This allows you to create custom plot types and add them to the plot.
var plt = new ScottPlot.Plot(600, 400);
double[] xs = DataGen.Consecutive(51);
double[] sin = DataGen.Sin(51);
// instantiate a plottable
var splt = new ScottPlot.Plottable.ScatterPlot(xs, sin);
// customize its style or change its data as desired
splt.Color = Color.Navy;
splt.MarkerSize = 10;
splt.MarkerShape = MarkerShape.filledDiamond;
// add it to the plot
plt.Add(splt);
plt.SaveFig("quickstart_add.png");
Call Clear() to remove all plottables from the plot. Overloads of Clear() allow you to remote one type of plottable, or a specific plottable.
var plt = new ScottPlot.Plot(600, 400);
double[] xs = DataGen.Consecutive(51);
double[] sin = DataGen.Sin(51);
double[] cos = DataGen.Sin(51);
plt.AddScatter(xs, sin, color: Color.Red);
plt.Clear();
plt.AddScatter(xs, cos, color: Color.Blue);
plt.SaveFig("quickstart_clear.png");


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And did those feet? Well, did they? I don't give two pins about the time, whether it was in ancient time or modern time or some other time, I just want to know if those feet did, and if they did, what it was, exactly, that they did. I suppose you will tell me that they walked. Lawks-a-mercy!, I'd never have guessed. Those feet walked, did they? Take me to the foot of our stairs! And don't get me started on that holy lamb of God. If I catch sight of it I'll have it sheared and its fleece spun and knitted into a pair of woolly socks before you can say Jack Spraggins. And I will put those socks on my feet and I will walk, yes, I will walk upon England's mountains green. Just try to stop me, buster.


Dear all,
first of all I would like to wish you happy new year.
I found out about Openenergymonitor one month ago and since I have already spent some time playing around with various arduino sensors etc I wanted to create a power monitor for my apartment and I thought that this is the right equipment for me to start with.
So I ordered from OpenEnergyMonitor shop the emonTX shield V2 (no RF) to start with. I got also 3 CT clips and the AC-AC euro adapter for the voltage.
I finished with the Shield soldering and I put it on an Arduino Uno to give it a try.
I used the default sketches from github for the TX shield.
First test with the Shield_CT1234_3Phase_Voltage sketch, with the AC AC adapter and the 3 CTs connected to the shield with no connection to any device cable to get a measurement.
The first issue I have is that always the first measurement I get when the sketch is running it shows a very high voltage value:
emonTX Shield CT1234 Voltage 3 Phase example
OpenEnergyMonitor.org
Node: 10 Freq: 868Mhz Network: 210
Total Samples: 283 Power Samples: 269 Time: 233 Crossings: 22
Voltage: 387.80
Current 1: 91.28 Power 1: 30659.53 VA 1: 35397.49 PF 1: 0.87
Current 2: 90.80 Power 2: 31936.00 VA 2: 35210.78 PF 2: 0.91
Current 3: 91.09 Power 3: 33184.83 VA 3: 35324.41 PF 3: 0.94
the next measurements are similar to the below:
Total Samples: 285 Power Samples: 270 Time: 235 Crossings: 22
Voltage: 194.05
Current 1: 0.15 Power 1: -1.08 VA 1: 28.86 PF 1: -0.04
Current 2: 0.11 Power 2: -0.34 VA 2: 20.79 PF 2: -0.02
Current 3: 0.10 Power 3: 0.77 VA 3: 19.04 PF 3: 0.04
or
Total Samples: 284 Power Samples: 269 Time: 233 Crossings: 22
Voltage: 194.16
Current 1: 0.15 Power 1: -4.46 VA 1: 29.27 PF 1: -0.15
Current 2: 0.10 Power 2: -0.74 VA 2: 20.02 PF 2: -0.04
Current 3: 0.10 Power 3: 0.77 VA 3: 20.37 PF 3: 0.04
but then again, when it finishes with the measurements and start over again, it gives another high voltage value:
emonTX Shield CT1234 Voltage 3 Phase example
OpenEnergyMonitor.org
Node: 10 Freq: 868Mhz Network: 210
Total Samples: 284 Power Samples: 270 Time: 233 Crossings: 22
Voltage: 400.65
Current 1: 91.64 Power 1: 32124.77 VA 1: 36714.03 PF 1: 0.87
Current 2: 91.16 Power 2: 32438.34 VA 2: 36521.48 PF 2: 0.89
Current 3: 91.46 Power 3: 33008.75 VA 3: 36642.04 PF 3: 0.90
I commented out all other readings and left only the Voltage and it seems that for some reason always the first reading gives a high value around 500 and then it smoothly goes down to aprox. 200 and again the same.
What might be the reason for this? Any ideas?
Without changing anything on the setup, I run the EmonTx Shield 4 x CT example sketch, and getting below values:
emonTX Shield CT123 example
OpenEnergyMonitor.org
Node: 10 Freq: 433Mhz Network: 210
10583 10525 10553
31 34 39
24 23 27
22 39 24
22 40 25
21 41 24
21 38 23
23 41 25
21 41 26
22 41 25
22 40 25
21 41 25
22 39 24
21 40 25
Is this normal to have such values with the CTs just plugged into the shield?
I have a 2500 W heating device (atlantic thermo heater) and tried to test with the TC1 attached to the power cable when it is on heating. The readings on TC1 are almost the same as before.
By reading some posts around the forum I read somewhere to test with the power cable to pass 2 times through the TC.
I tried this and the readings I get now are :
5 40 25
47 42 25
48 41 25
44 42 26
47 41 26
47 40 22
46 41 26
45 41 24
I would expect a bigger figure since without any power cable attached on the TC1, the reading is aprox. 20 and the difference is around 25.
i would like to thank you in advance for any help on these.
And something else I would like to ask, can you please confirm if pin 8 or some other pin on the TX shield is not used by the shield and I can use it with the ARduino to put another sensor I have at the same time?
Thanks and Happy new year again !!!
Re: Newbie questions on emonTX shield V2
John, it may be worth running the first few sketches on my Summary Page. They will show you how your hardware is working. If you loop (one core of) the supply cable twice around your CT, the current values should indeed double. This section of my PV Diversion article may be helpful too.
If using the emonTx Shield, you may need to change some of the pin numbers.
Re: Newbie questions on emonTX shield V2
The first issue I have is that always the first measurement I get when the sketch is running it shows a very high voltage value:
This is because the software high pass filters have not had time to settle. If you wish, you can inhibit the output in the same way that RF transmission is inhibited while the filters settle.
when it finishes with the measurements and start over again, it gives another high voltage value
It should not do that. I'll take a look at the sketch later.
Is this normal to have such values with the CTs just plugged into the shield?
Unfortunately, yes. It is due to noise picked up by the ADC input, we think from the processor's own digital circuits.
I can't check the calibration without knowing what your system voltage is, and which c.t's you have used. When you say "the TC1 attached to the power cable" - how? Are you passing the whole 3-core cable through the c.t? If so, I would expect zero output. As calypso_rae says, only one core - either line or neutral - should pass through the c.t.
I will check on pin 8 later, however you can find a set of circuit diagrams on Solderpad - details are on the Shield page
Re: Newbie questions on emonTX shield V2
Hi Robert,
thanks for the prompt reply.
Regarding your first comment: "If you wish, you can inhibit the output in the same way that RF transmission is inhibited while the filters settle." I am not sure what exactly to do here.
What I did as soon as I saw this first high number, I put more time for the filters to settle (10000 instead of 5000), but no difference.
The CTs I have are these sold by OpenEnergyMonitor (purchased from OpenEnergyMonitor).
You are right. I am embarrassed to say that I did this wrong connection and it is true that there was no change to the output values (with the same noise) ;-)
Thanks a lot. I will continue testing and maybe then I will have more questions for calibration.
For sure the first high voltage value I am getting at the restart point of the sketch is an issue. By the way, I tested and this value is always there, even if there is no voltage connected to the EmonTX shield !!! So, first value is a high number and all the others around 0.3-0.4
Re: Newbie questions on emonTX shield V2
John, you may find it helpful to run some of the sketches near the top of my Summary Page. This will show how your hardware is behaving.
Your AC voltage sensor will work best when its output spans most of the 10-bit range of the ADC, i.e. 0 - 1023. Similarly, your current sensor should use most of this range when the maximum current that you want to measure is flowing through the CT. When a smaller current is flowing, the amplitude (range) of the output signal will be doubled if you loop the current-carrying conductor twice around the CT rather than just once. When no current is flowing, the resulting signal from the ADC should be very small, no more than a couple of ADC steps, e.g. 511 - 513. If your output values (for either sensor) are not fairly symmetrical around 512, then your reference circuit is suspect.
MinMaxAndRangeChecker is a simple tool which displays the raw ADC values from each of the first four analog inputs (AN0 - AN3). RawSamplesTool_4ss_2 provides a snapshot of your V and I waveforms during one or more individual mains cycles. If this sketch runs correctly, it shows that your voltage sensor is OK. Prior to the display appearing on the Serial Monitor, there should be a slow countdown (one per second). If this sketch doesn't run properly, there is something wrong with your voltage sensor. When using the Shield, you may need to alter the pin number definitions.
Hardware issues are much easier to track down and fix while using simple tools like these. Once your hardware is behaving as expected, then you can run the appropriate software for whatever you want your rig to do.
Hope this helps.
Re: Newbie questions on emonTX shield V2
I made the right connection of the CT to the heater cable and I managed to get good readings. Tested voltage with the multi meter and by adjusting the variable in the sketch I have good readings now.
The only thing is that I am still getting the high voltage reading at the beginning of each cycle. It should be something in the sketch causing this. I put some more delay to the initial one (20000) but nothing.
Did anyone else phased the same issue with this sketch?
thanks in advance
Re: Newbie questions on emonTX shield V2
Initial false values due to the filters: The output you see on the serial monitor and the values sent to emonCMS or the emonGLCD are sent by different methods. If you look at the code, the RF transmission is inside a conditional branch "if (settled) { ... }"
If you put the "Serial.print(...)" statements inside a similar conditional, you will get no output printed until FILTERSETTLETIME has expired. But you must continue measuring because the filters need to run to be able to settle.
I can't see any other reason for the high voltage each time - and I never saw it, other than when starting the sketch for the first time, when developing and testing the sketch on an emonTx V2. I don't have a shield, and nobody else has reported this problem. I'm checking further.
[Edit]
That's weird. I see the high voltage each time I start the serial monitor - but only under Linux. I have a new machine and I've just switched from Windows to Ubuntu 12.04, I don't see the same effect with my old machine under Windows (which is why I never saw it before). It has to be tied up with the way the serial port is handled inside the monitoring computer, interrupts and the timing of the measurement. I don't know of a way to test if the output is being received and handled by the monitoring computer.
As a work-around, when you have finished testing, comment out this line near the top of the sketch:
#define SERIALPRINT
That should cure the problem.
Re: Newbie questions on emonTX shield V2
Hi Robin.
Thanks once more for the valuable and fast reponce.
I checked your simple tool and now I am more confident that the shield it works fine.
Please find below the raw data I get from the serial monitor, with CT connected only on CT1:
ready ...
The Min, Max and Range ADC values for analog inputs 0 to 3:
0 0 0; 0 0 0; 0 269 269; 0 512 512
0 0 0; 0 0 0; 249 768 519; 512 513 1
0 0 0; 0 0 0; 248 764 516; 512 513 1
0 0 0; 0 0 0; 248 764 516; 512 513 1
0 0 0; 0 0 0; 248 764 516; 512 513 1
0 0 0; 0 0 0; 249 767 518; 512 513 1
0 0 0; 0 0 0; 248 766 518; 512 513 1
0 0 0; 0 0 0; 248 765 517; 512 513 1
0 0 0; 0 0 0; 248 765 517; 512 513 1
0 0 0; 0 0 0; 248 765 517; 512 513 1
0 0 0; 0 0 0; 250 766 516; 512 513 1
0 0 0; 0 0 0; 249 765 516; 512 513 1
0 0 0; 0 0 0; 249 764 515; 512 513 1
0 0 0; 0 0 0; 249 764 515; 512 513 1
0 0 0; 0 0 0; 249 764 515; 512 513 1
Since you know better to read the outcome, as you previous wrote me ADC steps around 511-513 should be fine.
Regarding your latest post:
I also checked the shield on a laptop running Windows (my main machine is an imac), and I am still getting these high values.
But you are totally right that there is no reason to worry about such values, since the values that we are using for further processing are the ones within the if settled statement.
Thanks a lot for the help.
Re: Newbie questions on emonTX shield V2
John, the results that you've posted using MinMaxAndRangeChecker show that:
Analog inputs 0 & 1 are earthed.
Analog i/p 2 has an AC signal that occupies 50% of the ADC's range. The DC bias looks fine.
Analog i/p 3 has the correct DC bias but no AC signal is present.
Is this what you were expecting? If an AC current was flowing through your CT at the time of these measurements, then either it (or the AC voltage signal) was not being seen by the processor.
If you turn off the voltage source, do your readings change?
Re: Newbie questions on emonTX shield V2
John, according to the SolderPad schematic for the emonTx Shield, the AC voltage signal is processed via Analog i/p 0. CTs 1-4 are processed via Analog inputs 1-4 respectively. This is different than for the emonTx V2 where the voltage sensor was on An i/p 2.
The results that you've posted do not suggest to me that your voltage sensor, which needs to be on An 0 for the Shield, is working as intended.
My MinMaxAndRangeChecker sketch does not care what platform it's running on. Its results will be in different columns according to the hardware platform.
Send me a PM if you're still having difficulties with running this tool.
Re: Newbie questions on emonTX shield V2
Hi Robin,
below you can see the settings I ve done in your sketch:
val_a0 = analogRead(2); // CT2
val_a1 = analogRead(3); // CT3
val_a2 = analogRead(0); // Vsensor
val_a3 = analogRead(1); // CT1
The results that I previously posted are with CT1 attached on the shield with no current flowing through CT1.
Re: Newbie questions on emonTX shield V2
OK, that demo sketch was intended to be run without requiring any changes.


WITNESS LIST Redistricting Committee April 10, 2003-10:30A HB 2944 For: McKeithen, Steve (9th Court of Appeals) Against: Heagy, Warren (Ector County Bar Association President Katherine Clifton) On: Barajas, Richard (8th District Court of Appeals) Brister, Scott (14th Court of Appeals) Enoch, Craig (Texas Supreme Court) Radack, Sherry (First Judicial District of the Court of Appeals of Texas) Smith, Jr., Jackson (Self) Thomas, Linda (5th and 7th Courts of Appeals; Council of Chief Justices) HB 3398 For: Morales, Rick (Self) Against: Agnew, Virginia (Self) Calvert, Tommy T. C. (Neighborhoods First Alliance) Farrar, Jessica (Mexican American Legislative Caucus) Ortega, Frank (Self) Smith, Clint (Self and Gray Panthers) Yanez-Correa, Ana (Texas LULAC and Hector Flores LULAC's National President) On: Christian, Elizabeth (Self) Flynn, Charlotte (Self and Gray Panthers of Austin)


Journal
Journal Title:
Content of journal entry:
Add to journal!
Teaser:
Number of words in entry:
Number of vowels in entry:
Number of consonants in entry:


Ezekiel 40:32
And he brought me into the inner court toward the east: and he measured the gate according to these measures.


Emotional Intelligence is the ability to understand and manage your own emotions, and those of people around you. People with high degree of emotional intelligence know what they are feeling, what their emotions mean, and how these emotions can affect other people. This is essencial for leaders. There are 5 key elements to it:
If you are self-aware, you always know how you feel, and you know how emotions and actions can affect people around you. Being self-aware when you are in a ledership position also means having a clear picture of your strengths and weekness, and it means behaving with humility.
Self-regulation is about staying in control. This element also covers flexibility and commitment. You must have a clear idea of the most important values to you.  Practice being calm. Practice exercises to calm youself. Challenge your reaction to ensure that they are fair.
Every time you face a challenge, or even a failure, try to find at least one good thing about the situation. It might be something small, like a new contact, or something with long term effects, like an important lesson learned. But there is almost always something positive, if you look for it. Self-motivated leaders work consistently toward their goals, and they have extremely high standards for the quality of their work.
Always put yourself in someone else's position. Take the time to loook at situations from others people's perspective. Pay attention to the body language. It tells how people really feel. This gives the opportunity to to respond appropriately.
Be open to hearing bad news as good news, and get team to support them and be excited about a new mission or project. Learn how to manage conflicts, how to praise others and improve your overall communication skills.


{# Modified page layout. Refer to https://bashtage.github.io/sphinx-material/customization.html#customizing-the-layout. #}
{% extends '!layout.html' %}
{%- block extrahead %}
{# Adds custom things to the head HTML tag. #}
{# First call parent block #}
{{ super() }}
{# Open Graph #}
{# Currently, there is no description available. #}
{# #}
{%- endblock %}


dotdot demo
Type any number in the inputs below.
Attached to a single element
Attached to many elements
It works with jQuery too


abstract fun buildFilteredTransaction(filtering: Predicate<Any>): FilteredTransaction
Helper function to directly build a FilteredTransaction using provided filtering functions, without first accessing the WireTransaction.


Add KML Layer (Google KML Data)
KML and KMZ files (Keyhole Markup Language) are stored in an XML notation designed for visualizing and annotating geographic information.
KML is a "flat text" format which can be read and edited with an ordinary text editor. KMZ is a compressed version of the KML to save disk space and transfer time. In our exercise, we will prefer the KML format, which we can view and manipulate as needed.
The KML technology was purchased by Google in 2004, and became the main format used by the Google Earth application. Since KML files can be created using the free (and relatively easy to use) Google Earth software, it has become quite popular.
However, there are some particular aspects of the KML notation that make it less than optimal for data entry, especially for the annotation of spatial features (aka "placemarks") with attributes, as we expect to do in GIS.
In this module we will demonstrate the basic use of KML in QGIS and a few tricks that will make it possible to store attributes (in a separate spreadsheet) and join them to the correct spatial features.
A quick search for KML of Egypt found some layers of Egyptian Pyramids. Opening the KML file with GOOGLE EARTH shows the typical placemark symbols (pushpins) scattered along the Nile River
Clicking on one of the placemarks brings up the "Name" and "Description" associated with that spatial feature. For example, the placemark for Pyramid of Djoser, has a snippet of the Wikipedia entry.
This looks fine, and works perfectly in the context of Google Earth, but if you right-click on the Pyramid of Djoser feature in the Places list, and go to Properties, you will see the actual code that is stored in the two FIELDS
1. Name "Pyramid of Djoser"
2. Description [all the embedded HTML from the Wikipedia page]
If we were to look at the actual KML file, in other words the XML document, we see that the situation is further complicated by the "Description" section being encapsulated within CDATA
From this example, we can see that the <name> section is fairly straightforward, but that the <description> is problematic because it includes a great deal of <div> or <span> or other elements within the CDATA section. It turns out that parsing this CDATA, without having an exact schema of the contents is not trivial.
Essentially these are the only free-text fields containing attributes related to the placemrk. NAME, which is a simple string, and DESCRIPTION, which is also a text string, but is wrapped within CDATA section.
Later in this module, we will make use of the NAME and DESCRIPTION fields in a way that makes them actually functional when importing into GIS.
But first, let's simply open the Pyramids file in QGIS to take a look at it.
KML is considered a regular Vector format, so go to ADD VECTOR DATA and browse to your KML file, then change the encoding to UTF-8 and after you click BROWSE change the file format (on the lower right) to either Keyhole Markup, or All Files, in order to see your .kml file listed. Then click OPEN and OPEN again.
You should now have the KML file opened, and you can adjust the symbolization, for example to red stars, by right-clicking on the KML layer and going to PROPERTIES - STYLE and setting the Marker Symbol and Color.
Now right-click on the kml file in the Layers Panel and OPEN ATTRIBUTE TABLE. You can see that the NAME field looks okay, but the DESCRIPTION field contains the entire text string that was found within the CDATA section.
Basically, the purpose of examining the KML format and importing it into QGIS here, was to demonstrate that there is no reliable way to convert attributes that are stored in the DESCRIPTION field of KML into normalized fields in the QGIS attribute table.
There is a trick, though!
It is not to hard to see that the NAME field being stored with the placemark in KML is not being wrapped in CDATA, nor is it being parsed out of the CDATA section into text string when importing to QGIS.
Therefore, it is expedient to use the NAME field for Unique Identifiers, such as UNIQUE ID NUMBERS, and only put in a simple feature description in the DESCRIPTION field, such as the placename of the feature.
This is may seem counter-intuitive, but the method is simply something like:
Name = 128
Description = Great Pyramid of Giza
If we edit a version of the KML file this way, the Properties of the placemark will be quite readable.
Opening the revised KML in QGIS we can examine the ATTRIBUTE TABLE and see that use of DESCRIPTION field was fine for a SINGLE attribute, the Name of the place, and the NAME field preserved the UNIQUE ID NUMBER as a string.
If we were to store other attributes and variables related to these spatial features in a table (Calc, CSV, etc), we could join them using the following steps;
1. save the KML to Shapefile
2. open the tabular data in QGIS using Add Vector Layer
3. go to the Shapefile layer PROPERTIES - JOINS tab, and run the join, using the KML.Name field as the Unique Identifier for the Join.
Jump ahead to the JOINS module for complete guide to Joins in QGIS.
To sum up, the import of KML into QGIS is very simple, but the import will not be able to parse out multiple attributes saved into the "Description" field.
Therefore, the recommended use of KML as a data entry tool is to store UNIQUE IDENTIFIERS in the "Name" field, and one textual attribute in the "Description" field.
Any additional attributes or variables related to specific Placemarks should be stored in a separate spreadsheet, using one UNIQUE IDENTIFIER for each row. Finally the tabular data can be JOINED to the spatial features in QGIS.
See also:
- Connect to WMS in National Map.
- WMS tutorial from Ujaval Gandhi.
Proceed to Georeferencing A Scanned Map Instructions


Youtube Gesture Control Demo
This is a simple demo web page that uses hand gestures to control the youtube video below.
Instructions:
- Grant permission for the web page to use the web camera. Try using newer versions of chrome or firefox
- To play/pause the video, make a hand gesture of closed fist in front of the camera
- To reset any settings, just refresh the page
One of the following errors occurred:
- Browser does not support using webcamera. Try new versions of chrome or firefox
- Permission to use webcaamera is denied


WHAT IS THORCHAIN?
THORChain is a groundbreaking technology that allows for fully decentralized swaps between any supported blockchain, and earns yield from native assets.
THORChain will insure liquidity providers against impermanent loss.
The network is run by dozens of anonymous node operators who bond RUNE and are rewarded for their services. Attempting to fork and bootstrap a clone would be a difficult task to achieve.
The design of the network ruthlessly maximizes revenue for liquidity providers and node operators.
RUNE is required to be paired as a settlement asset 1:1 in pools. But the network's economic design causes the value of RUNE to increase with liquidity depth.
THORCHAIN STATS
The THORChain protocol is totally transparent -- you can verify its solvency for yourself. View the nodes that run the network, the vaults that they host, and the total value locked in the network.
THORCHAIN TOOLS
The THORChain project is made up of a team of core developers, but is augmented by a enormous community that has built various tools that provide resources for the community.
View the status of the network, node health, value locked, and more.
Simulate profit and loss for various pools.
Visualize liquidity positions, rewards, and total percent gain versus holding.
THORCHAIN ECONOMY
The RUNE network asset plays a crucial role in the THORChain ecosystem. It's not a governence token -- it's the settlement asset that enables liquidity across pairs, and is bonded to secure the network.
A balance between bonded and pooled RUNE is key to a secure and liquid network. If the network is under-bonded, node operators are incentivized to increase their bonds, if it’s over-bonded, liquidity providers are incentivized to pool more assets.
The price of RUNE is deterministic — since the network requires it to be bonded 2:1 by node operators, and paired 1:1 with pooled assets by liquidity providers, the market cap of RUNE is at least 3x the TVL of non-RUNE assets.
The combination of the various economic incentives result in a network that produces high APY for both node operators and liquidity providers.
A liquidity-sensitive slip-based fee solves many issues — including bootstrapping shallow pools, discouraging dust and sandwich attacks, and forcing high volume/frequency traders to pay their fair share.
The use of a CLP allows for many benefits, such as the ability to sense prices without an oracle. Simply by knowing the asset depth in pools, the network is able to determine price while arbitrageurs ensure the rate is inline with current market conditions.
ROADMAP & PLANS
At its core, THORChain is a cross-chain liquidity network. But the design of the protocol enables much more than just swaps -- synths, composites, self-paying loans -- anything is possible.


My Education
Sri Sharadha Shishu Mandir
I have studied in this school from LKG to 8th Standard. My favorite class is Maths, because I love to solve problems and it helps me to increase my logical thinking. My memory about the school is when i was become the school leader and continued for five years.
Kakatiya High School
I have studied 9th and 10th standard in this school. My favorite calss is english, because this is where my english has been improved alot and had a chance to speak in english with all the school students. The best memory of Kaktiya school is when I won the medal for the best essay writing in english even though i was studying in the telugu medium.
Gnanadeep Junior College
I have studied my 11th and 12th in this college. My favorite class is Physics because of the professor, he explains the topic very clearly and the knowledge which i have gain was very helpful for my further career. The best memory of this college is when I become a second topper of the college.
CMR College of Engineering and Technology
I have done my Bachelor's in Computer Science. My favorite subjects are C and C++ because we need to write the code from the scratch. The best memory of the college is that I was the topper for all the eight semesters and when I got a full time job in TEKsystems.
Stevens Institute of Technology
I am currently my masters in Computer Science. My favorite class is Multivariate Data Analytics, which has given me clear idea on what i want to become. The best memory of the college is when I took Data Warehouse and Business Intelligence course, because this will help alot in my career.


A large part of the content in this handbook was adopted from the Hacking Materials Handbook.
{% seo %} {% if page.tipue_search_active or layout.tipue_search_active %} {% endif %}
A large part of the content in this handbook was adopted from the Hacking Materials Handbook.


Quality Applications for Android
Breedr Apps strives to open source projects, when possible, to allow the community to contribute, learn and collaborate.
Our apps are designed with you in mind. We aim to create innovative, intuitive and user-friendly applications.
We are passionate about the apps we make and use this passion to ensure we deliver exceptional quality.


| 448 | (A) | Couerde with a castełłe þat craftily was wroghte |
| 450 | (C) | Couered with a castełł . þat craftyly is wrowȝte |
| 447 | (D) | Coverid wiþ a castełł craftily wrogħt |
| 446 | (E) | coueryd with a castel . crayftly y-wrougħt |
| (Ex) | ---- no text ---- | |
| 463 | (L) | keuered myd a castel was craftily ywroȝt |
| 429 | (P) | Couyrde with a castiłł þat craftely was wroght |
| 444 | (U) | Couerd witħ a castel / that craftly is wrougħt |
| (V) | ---- no text ---- |


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BrawlCrate v0.40a
Wii File Editor
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Allows read-write access to Custom Song Volume code. This class will store the entire codeset, split between itself (the CSV code) and the portions before/after (in raw byte[]). More...
Public Member Functions | |
| CustomSongVolumeCodeset (string[] s) | |
| CustomSongVolumeCodeset (byte[] data) | |
| CustomSongVolumeCodeset (string filename) | |
| override string | ToString () |
| byte[] | ExportCode () |
| string | ExportCodeString () |
| byte[] | ExportGCT () |
Properties | |
| byte[] | DataBefore [get] |
| byte[] | DataAfter [get] |
| Dictionary< ushort, byte > | Settings [get] |
| CNMT | CNMT [get] |
| Gets read-only access to instances of the CMM Setting Code [JOJI] in this codeset. More... | |
Allows read-write access to Custom Song Volume code. This class will store the entire codeset, split between itself (the CSV code) and the portions before/after (in raw byte[]).
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inline |
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inline |
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inline |
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inline |
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inline |
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inline |
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inline |
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get |
Gets read-only access to instances of the CMM Setting Code [JOJI] in this codeset.
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get |


Introduction
Modulz is an open–source design system for scalable web development. Modulz includes a component library, layout templates, coding and design guidelines, tutorials, resources and much more to help you build your next marketing site or web project.
Quick start
Occasionally, if an action is more significant, essential or impactful, one of three pronounced buttons can be used.
Principles
Occasionally, if an action is more significant, essential or impactful, one of three pronounced buttons can be used.
Modulz
Occasionally, if an action is more significant, essential or impactful, one of three pronounced buttons can be used.
Modulz
Occasionally, if an action is more significant, essential or impactful, one of three pronounced buttons can be used.
Team
Just little ol' me.
Community
Occasionally, if an action is more significant, essential or impactful, one of three pronounced buttons can be used.


The Parallel class handles parallelism of loops, allowing for a functionality close to OpenMP (with some limitations)
More...
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| | Parallel (unsigned nbThreads=0) |
| | Parallel Constructor for a parallel context. More...
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unsigned | getID () |
| | getID Returns current thread ID, as a value between 0 and nbThreads - 1 (useful for avoiding race condition)
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| void | For (Index start, Index end, Index step, Callable func) |
| | For Parallelized for loop - Warning, works only in increasing order, with step positive, and end > start The type of start, end, and step has to be the same, but can be anything comparable with "<". More...
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The Parallel class handles parallelism of loops, allowing for a functionality close to OpenMP (with some limitations)
◆ Parallel()
| Parallel::Parallel |
( |
unsigned |
nbThreads = 0 | ) |
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|
inline |
Parallel Constructor for a parallel context.
- Parameters
-
| nbThreads | Number of threads to use, 0 (default) means all available threads are used |
◆ For()
template<typename Index , typename Callable >
| void Parallel::For |
( |
Index |
start, |
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Index |
end, |
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Index |
step, |
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Callable |
func |
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inline |
For Parallelized for loop - Warning, works only in increasing order, with step positive, and end > start The type of start, end, and step has to be the same, but can be anything comparable with "<".
- Parameters
-
| start | Starting value for the loop |
| end | Ending value for the loop (not included) |
| step | Step for increasing the loop from start to end |
| func | Lambda function to launch inside the loop (can call getID() to get current thread number) |
The documentation for this class was generated from the following file:


Gynaecology
Medical School - University of North Carolina, Doctor of Medicine
University of Massachusetts, Residency in Obstetrics and Gynecology
Yergalem Regional Hospital, Ethiopia
| Timetable | ||
|---|---|---|
| Monday | 08:00am - 4:00pm | |
| Tuesday | Closed | |
| Wednesday | Closed | |
| Thursday | 08:00am - 4:00pm | |
| Friday | Closed | |
| Saturday | 08:00am - 4:00pm | |
| Sunday | Closed |
| August 2019 | ||||||
|---|---|---|---|---|---|---|
| M | T | W | T | F | S | S |
| 2 | 4 | |||||
| 6 | 7 | 9 | 11 | |||
| 13 | 14 | 16 | 18 | |||
| 20 | 21 | 23 | 25 | |||
| 27 | 28 | 30 |
Choose a date to see available times and book an appointment.


Chapter 1 Getting used to R and R Studio
In this chapter, my solutions are in with the problems.
## Warning: package 'MASS' was built under R version 4.0.5
## Warning: package 'nnet' was built under R version 4.0.5
## Warning: package 'lme4' was built under R version 4.0.5
## Warning: package 'Matrix' was built under R version 4.0.5
1.1 Running R Studio on Jupyterhub
This is described as a “proof-of-concept” way of running R Studio online (for free, for anyone with a UTorID and password). This is a good way to get started with R Studio. It looks the same as any other version of R Studio.
- To get started, in your web browser, visit https://jupyter.utoronto.ca/hub/login. You should see something that looks like this:
If you don’t see this, you might see this instead:
which looks almost the same, but lacks the option to start R Studio.
- On the line where it says “After logging in, start…” make sure you have clicked next to (on the left of) R Studio, so that the circle is blue, and then click the orange “Log in to start”. Log in with your UTorID and password. This is about what you should see after you have done that:
On the left is where you will (later) have code to run. Top right is the Console, where you can run quick disposable bits of code, and bottom right you see any files you may happen to have (probably only one at this stage).
- To test what you have, click on the top right Console window, type
library(tidyverse)
and press Enter. You might see R Studio offering you some suggestions as you type. If you see what you want, you can select it rather than typing the whole thing.
Here’s what you should see now. You can ignore the error messages from Jupyter:
Still in the Console window, type mtcars
and press Enter again. This will bring up one of R’s built-in datasets:
This is information about a number of cars, as featured in Motor Trends magazine. If you can see this, you are good to go. A good thing to tackle next is the problem called Getting Started, which uses the same dataset.
1.2 Getting an R Studio Cloud account
Follow these steps to get an R Studio Cloud account.
- Point your web browser at link. (If you already have R and R Studio installed on your computer, you can use that instead, throughout the course; just do part (d) of this question. Any references to R Studio Cloud in this assignment also apply to R Studio on your computer.)
Solution
You should see this:
. Click on Get Started. You might instead see the screen in the next part.
\(\blacksquare\)
- Choose an account to use.
Solution
Here’s what you should see now:
If you’re happy with using your Google account, click that
button. You will probably have to enter your Google password. (If
you are doing this on your own computer, you might not have to do
that.) If you have a GitHub account and you want to use
that, same principle.
You can also use an email address as your login to R Studio
Cloud. (You can use any e-mail address; I’m not checking.) Enter
it in the top box, and enter a password to use with R Studio Cloud
in the second. (This does not have to be, and indeed probably
should not be, the same as your email password.) Below that,
enter your first and last name. This will appear at the top right
of the screen when you are logged in. Then click Sign Up. After
that, you will have to make a unique account name (which
you actually never use, but which
rstudio.cloud
uses to
name your files).
After that, you are automatically logged in.
\(\blacksquare\)
- Take a look around, and create a new Project. Give the new project any name you like.
Solution
This is what you see now:
Click on the blue New Project button to create a new Project. (A project is a self-contained piece of work, like for example an assignment.) You will see the words “Loading Project” and spinning circles for a few moments. Then you see this:
To give your project a name, click at the top where it says Untitled Project and type a name like Assignment 0 into the box.
\(\blacksquare\)
- Before we get to work, look for the blue
>
at the bottom left. Click next to it to get a flashing cursor, and then type what you see here (in blue):
Then press Enter.
 It may take some
time. If you are watching it, look out for lines beginning with
g++
, which are C++ code that needs to be compiled. This is
the end of what I had. Look out for the word DONE near the bottom:
\(\blacksquare\)
- Not for now, but for later: if you are on a lab computer, you should probably log out when you are done. To do that, find your name at the top right. Click on it, and two things should pop out to the right: Profile and Log Out. Select Log Out. You should be returned to one of the screens you began with, possibly the Welcome to R Studio Cloud one. To log back in, now or next time, look for Log In at the top right. Click it, to get this:
and then you can log in with your email and password, or Google or Github IDs, whichever you used. Now we can get down to some actual work.
1.3 Getting started
This question is to get you started using R.
- Start R Studio Cloud, or the R Studio on Jupyter, in some project. (If you started up a new project in the previous question and are still logged in, use that; if not, create a new project with File, New Project, and New Directory. Then select New Project and give it a name. Click Create Project. This will give you an empty workspace to start from.)
Solution
You ought to see something like this. I have a dark blue background here, which you probably do not.
It won’t look exactly like that (for example, the background will probably be white) but there should be one thing on the left half, and at the top right it’ll say “Environment is empty”. Extra: if you want to tweak things, select Tools (at the top of the screen) and from it Global Options, then click Appearance. You can make the text bigger or smaller via Editor Font Size, and choose a different colour scheme by picking one of the Editor Themes (which previews on the right). My favourite is Tomorrow Night Blue. Click Apply or OK when you have found something you like. (I spend a lot of time in R Studio, and I like having a dark background to be easier on my eyes.)
\(\blacksquare\)
- We’re going to do some stuff in R here, just to get used to it. First, make an R Notebook by selecting File, New File and R Notebook.
Solution
The first time, you’ll be invited to “install some packages” to make the Notebook thing work. Let it do that by clicking Yes. After that, you’ll have this:
Find the Insert and Run buttons along the top of the R Notebook window. We’ll be using them shortly. (The template notebook may or may not be maximized; it doesn’t matter either way. You might see all four panes or as few as one. If you want to control that, select View at the top, then Panes, then either Show All Panes or Zoom Source, as you prefer. In the menus, you’ll also see keyboard shortcuts for these, which you might find worth learning.)
\(\blacksquare\)
- Change the title to something of your choosing. Then go down to line 5, click on the Insert button and select R. You should see a “code chunk” appear at line 5, which we are going to use in a moment.
Solution
Something like this:
\(\blacksquare\)
- Type the line of code shown below into the chunk in the R Notebook:
mtcars
Solution
What this will do: get hold of a built-in data set with information about some different models of car, and display it.
In approximately five seconds, you’ll be demonstrating that for yourself.
\(\blacksquare\)
- Run this command. To do that, look at the top right of your code chunk block (shaded in a slightly different colour). You should see a gear symbol, a down arrow and a green “play button”. Click the play button. This will run the code, and show the output below the code chunk.
Solution
Here’s what I get (yours will be the same).
This is a rectangular array of rows and columns, with
individuals in rows and variables in columns, known as a
“data frame”. When you display a data frame in an R Notebook, you see
10 rows and as many columns as will fit on the screen. At the
bottom, it says how many rows and columns there are altogether
(here 32 rows and 11 columns), and which ones are being
displayed. You can see more rows by clicking on Next, and if
there are more columns, you’ll see a little arrow next to the
rightmost column (as here next to am
) that you can
click on to see more columns. Try it and see. Or if you want to
go to a particular collection of rows, click one of the numbers
between Previous and Next: 1 is rows 1–10, 2 is rows 11–20,
and so on.
The column on the left without a header (containing the names of
the cars) is called “row names”. These have a funny kind of
status, kind of a column and kind of not a column; usually, if
we need to use the names, we have to put them in a column first.
In future solutions, rather than showing you a screenshot,
expect me to show you something like this:
## # A tibble: 32 x 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## # … with 22 more rows
The top bit is the code, the bottom bit with the ##
the
output. In this kind of display, you only see the first ten rows (by
default).
If you don’t see the “play button”, make sure that what you have really is a code chunk. (I often accidentally delete one of the special characters above or below the code chunk). If you can’t figure it out, delete this code chunk and make a new one. Sometimes R Studio gets confused.
On the code chunk, the other symbols are the settings for this chunk (you have the choice to display or not display the code or the output or to not actually run the code). The second one, the down arrow, runs all the chunks prior to this one (but not this one).
The output has its own little buttons. The first one pops the output out into its own window; the second one shows or hides the output, and the third one deletes the output (so that you have to run the chunk again to get it back). Experiment. You can’t do much damage here.
\(\blacksquare\)
- Something a little more interesting:
summary
obtains a summary of whatever you feed it (the five-number summary plus the mean for numerical variables). Obtain this for our data frame. To do this, create a new code chunk below the previous one, typesummary(mtcars)
into the code chunk, and run it.
Solution
This is what you should see:
or the other way:
## mpg cyl disp hp drat wt qsec vs
## Min. :10.40 Min. :4.000 Min. : 71.1 Min. : 52.0 Min. :2.760 Min. :1.513 Min. :14.50 Min. :0.0000
## 1st Qu.:15.43 1st Qu.:4.000 1st Qu.:120.8 1st Qu.: 96.5 1st Qu.:3.080 1st Qu.:2.581 1st Qu.:16.89 1st Qu.:0.0000
## Median :19.20 Median :6.000 Median :196.3 Median :123.0 Median :3.695 Median :3.325 Median :17.71 Median :0.0000
## Mean :20.09 Mean :6.188 Mean :230.7 Mean :146.7 Mean :3.597 Mean :3.217 Mean :17.85 Mean :0.4375
## 3rd Qu.:22.80 3rd Qu.:8.000 3rd Qu.:326.0 3rd Qu.:180.0 3rd Qu.:3.920 3rd Qu.:3.610 3rd Qu.:18.90 3rd Qu.:1.0000
## Max. :33.90 Max. :8.000 Max. :472.0 Max. :335.0 Max. :4.930 Max. :5.424 Max. :22.90 Max. :1.0000
## am gear carb
## Min. :0.0000 Min. :3.000 Min. :1.000
## 1st Qu.:0.0000 1st Qu.:3.000 1st Qu.:2.000
## Median :0.0000 Median :4.000 Median :2.000
## Mean :0.4062 Mean :3.688 Mean :2.812
## 3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :1.0000 Max. :5.000 Max. :8.000
For the gas mileage column mpg
, the mean is bigger than the
median, and the largest value is unusually large compared with the
others, suggesting a distribution that is skewed to the right.
There are 11 numeric (quantitative) variables, so we get the five-number summary plus mean for each one. Categorical variables, if we had any here, would be displayed a different way.
(In case you are wondering, the way without screenshots is obtained by my writing a notebook with code chunks and running them, so this output genuinely is obtained by running the code you see.)
\(\blacksquare\)
- Let’s make a boxplot of the gas mileage data. This is a
“poor man’s boxplot”; we’ll see a nicer-looking way later. To do it
this way, make another new code chunk, enter the code
boxplot(mtcars$mpg)
into it, and run the chunk.
Solution
This is what you should see:
The long upper whisker supports our guess from before that the distribution is right-skewed.
\(\blacksquare\)
- Some aesthetics to finish with: delete the template notebook (all the stuff you didn’t type below your code chunks and output). Then add some narrative text above and below your code chunks. Above the code chunk is where you say what you are going to do (and maybe why you are doing it), and below is where you say what you conclude from the output you just obtained.
Solution
My complete R Notebook is at http://ritsokiguess.site/datafiles/a0-notebook-1.Rmd. Take a look at it. I added one extra thing: my variable names have “backticks” around them. You’ll see the effect of this in a moment. Backtick is on the key to the left of 1 and below Esc on your keyboard, along with a “squiggle” symbol that we’ll be using later in the course.
\(\blacksquare\)
- Save your notebook (the usual way with File and Save). This saves it on the R Studio Cloud servers (and not on your computer). This means that when you come back to R Studio Cloud later, even from another device, this notebook will still be available to you. Now click Preview. This produces a pretty HTML version of your notebook.
Solution
Note that the HTML document only contains output from the chunks
you’ve run in the notebook, so it’s up to you to run them there
first.
My HTML document is at
http://ritsokiguess.site/datafiles/a0-notebook-1.nb.html.
Here’s where you see the effect of the backticks: all the
variable names are in typewriter font
so that you can
see they are variable names and not something else. If you want
to try this notebook out yourself, you have a couple of options:
(i) make a new R Notebook on R Studio Cloud and copy-paste the
contents of my file (it’s just text), or (ii) download my R
Notebook onto your computer, and then upload it to R Studio
Cloud. Look in the Files pane bottom right, and next to New
Folder you should see Upload. Upload the file from wherever it
got saved to when you downloaded it.
Extra: if you’re feeling ambitious, click the arrow to the right
of Preview and select Knit to Word. The button changes to Knit
with a ball of wool beside it. Now, when you “knit” the
notebook, you get a Word document directly — look for it in
the Files pane. If you want to, you can hand this kind of thing
in (on later assignments), but you’ll have to do a little work
first: first, find it in your Files list, then click the
checkbox to the left of it, then click More (with the gear, on
the same line as New Folder and Upload), then select Export (and
click Download). This will put a copy in your downloads folder
on your computer, and you can open it from there.
If you’re feeling extra-ambitious, you can try Knit to PDF. This
produces something that looks as if it was written in LaTeX,
but actually wasn’t. To make this work, if you have a
library(tidyverse)
line somewhere, as you probably
will, find the code chunk it’s in, and make it look like this:
Then it will work. Extra extra: if you like the keyboard better than the mouse, R Studio has a lot of keyboard shortcuts. Two that are useful now: control-alt-i inserts a code chunk where the cursor is, and control-shift-enter runs the code chunk that the cursor is in, if it is in one. (Mac users, “command” instead of “control” in both cases.) I use these two a lot.
\(\blacksquare\)
- Optional extra: practice handing in your previewed R notebook, as if it were an assignment that was worth something. (It is good to get the practice in a low-stakes situation, so that you’ll know what to do next week.)
Solution
There are two steps: download the HTML file onto your computer,
and then handing it in on Quercus.
To download: find the HTML file that you want to download in the
Files pane bottom right. There should be two files starting with
the same thing, eg. test1.Rmd
, which is the notebook
you wrote, and test1.nb.html
, which is the previewed
version of it, and is the one you want to download. (The
test1
part is the name you chose when you saved
it.) Click the checkbox to the left of the HTML file.
Now click on More above the bottom-right pane. This pops up a
menu from which you choose Export. This will pop up another
window called Export Files, where you put the name that the file
will have on your computer. (I usually leave the name the same.)
Click Download. The file will go to your Downloads folder, or
wherever things you download off the web go.
Now, to hand it in. Open up Quercus at q.utoronto.ca
,
log in and navigate to this course. Click Assignments. Click
(the title of) Assignment 0. There is a big blue Submit
Assignment button top right. Click it. You’ll get a File Upload
at the bottom of the screen.
Click Choose File and find the HTML file that you
downloaded. Click Open (or equivalent on your system). The name
of the file should appear next to Choose File. Click Submit
Assignment. You’ll see Submitted at the top right.
If you want to try this again, you can Re-submit Assignment as
many times as you like. (For the real thing, you can use this if
you realize you made a mistake in something you submitted. The
graders’ instructions, for the real thing, are to grade the
last file submitted, so in that case you need to make
sure that the last thing submitted includes everything
that you want graded. Here, though, it doesn’t matter.)
\(\blacksquare\)
- Optional extra. Something more ambitious: make a scatterplot of gas
mileage
mpg
, on the \(y\) axis, against horsepower,hp
, on the \(x\)-axis.
Solution
That goes like this. I’ll explain the steps below.
$ %$ %$
This shows a somewhat downward trend, which is what you’d expect,
since a larger hp
value means a more powerful engine, which
will probably consume more gas and get fewer miles per gallon.
As for the code: to make a ggplot
plot, as we will shortly
see in class, you first need a ggplot
statement that says
what to plot. The first thing in a ggplot
is a data frame
(mtcars
here), and then the aes
says that the plot
will have hp
on the
\(x\)-axis and mpg
on the \(y\)-axis, taken from the data frame
that you specified. That’s all of the what-to-plot. The last thing is
how to plot it; geom_point()
says to plot the data values as
points.
You might like to add a regression line to the plot. That is a matter of adding this to the end of the plotting command:
## `geom_smooth()` using formula 'y ~ x'
The line definitely goes downhill. Decide for yourself how well you think a line fits these data.
\(\blacksquare\)
1.4 Reading data from a file
In this question, we read a file from the web and do some descriptive statistics and a graph. This is very like what you will be doing on future assignments, so it’s good to practice it now.
Take a look at the data file at http://ritsokiguess.site/datafiles/jumping.txt. These are measurements on 30 rats that were randomly made to do different amounts of jumping by group (we’ll see the details later in the course). The control group did no jumping, and the other groups did “low jumping” and “high jumping”. The first column says which jumping group each rat was in, and the second is the rat’s bone density (the experimenters’ supposition was that more jumping should go with higher bone density).
- What are the two columns of data separated by? (The fancy word is “delimited”).
Solution
Exactly one space. This is true all the way down, as you can check.
\(\blacksquare\)
- Make a new R Notebook. Leave the first four lines, but get rid
of the rest of the template document. Start with a code chunk
containing
library(tidyverse)
. Run it.
Solution
You will get either the same message as before or nothing. (I got
nothing because I had already loaded the tidyverse
in
this session.)
\(\blacksquare\)
- Put the URL of the data file in a variable called
my_url
. Then useread_delim
to read in the file. (See solutions for how.)read_delim
reads data files where the data values are always separated by the same single character, here a space. Save the data frame in a variablerats
.
Solution
Like this:
##
## ── Column specification ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## cols(
## group = col_character(),
## density = col_double()
## )
The second thing in read_delim
is the thing that separates
the data values. Often when you use read_delim
it’ll be a space.
\(\blacksquare\)
- Take a look at your data frame, by making a new code chunk and
putting the data frame’s name in it (as we did with
mtcars
).
Solution
## # A tibble: 30 x 2
## group density
## <chr> <dbl>
## 1 Control 611
## 2 Control 621
## 3 Control 614
## 4 Control 593
## 5 Control 593
## 6 Control 653
## 7 Control 600
## 8 Control 554
## 9 Control 603
## 10 Control 569
## # … with 20 more rows
There are 30 rows and two columns, as there should be.
\(\blacksquare\)
- Find the mean bone density for rats that did each amount of jumping.
Solution
This is something you’ll see a lot: group_by
followed by
summarize
. Reminder: to get that funny thing with the
percent signs (called the “pipe symbol”), type control-shift-M (or
equivalent on a Mac):
## # A tibble: 3 x 2
## group m
## <chr> <dbl>
## 1 Control 601.
## 2 Highjump 639.
## 3 Lowjump 612.
The mean bone density is clearly highest for the high jumping group, and not much different between the low-jumping and control groups.
\(\blacksquare\)
- Make a boxplot of bone density for each jumping group.
Solution
On a boxplot, the groups go across and the values go up and down, so the right syntax is this:
Given the amount of variability, the control and low-jump groups are very similar (with the control group having a couple of outliers), but the high-jump group seems to have a consistently higher bone density than the others.
This is more or less in line with what the experimenters were guessing, but it seems that it has to be high jumping to make a difference.
You might recognize that this is the kind of data where we would use analysis of variance, which we will do later on in the course: we are comparing several (here three) groups.
\(\blacksquare\)
1.5 Reading files different ways
This question is about different ways of reading data files. If you’re using R Studio Cloud (online), start at the beginning. If you’re using R Studio running on your own computer, start at part (here).
- Log in to R Studio Cloud. Open up a project (or start a new
one), and watch the spinning circles for a few minutes. When that’s
done, create a new R Notebook with File, New File, R
Notebook. Delete the “template” notebook, but not the top four
lines with
title:
andoutput:
in them. Add a code chunk that containslibrary(tidyverse)
and run it.
Solution
So far you (with luck) have something that looks like this:
If you have an error rather than that output, you probably need to
install the tidyverse
first. Make another code chunk,
containing
and run it. Wait for it to finish. It may take a while. If it
completes successfully (you might see the word DONE at the end),
delete that code chunk (you don’t need it any more) and try again with
the library(tidyverse)
chunk. It should run properly this
time.
\(\blacksquare\)
- * The easiest kind of files to read
in are ones on the Internet, with a URL address that begins with
http
orhttps
. I have a small file at link. Click the link to see it, and keep the tab open for the next part of this question. This is a text file with three things on each line, each separated by exactly one space. Read the data file into a data frame, and display your data frame.
Solution
Data values separated by exactly one space is the kind of thing that read_delim
reads, so make another code chunk and fill it with this:
##
## ── Column specification ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## cols(
## x = col_double(),
## y = col_double(),
## g = col_character()
## )
## # A tibble: 6 x 3
## x y g
## <dbl> <dbl> <chr>
## 1 1 10 a
## 2 2 11 b
## 3 3 14 a
## 4 4 13 b
## 5 5 18 a
## 6 6 21 b
When you run that, you’ll see something like my output. The first part
is read_delim
telling you what it saw in the file: two
columns of (whole) numbers and one column of text. The top line of the
file is assumed to contain names, which are used as the names of the
columns of your data frame. The bottom part of the output, obtained by
putting the name of the data frame on a line by itself in your code
chunk, is what the data frame actually looks like. You ought to get
into the habit of eyeballing it and checking that it looks like the
values in the data file.
The things on the left side of the equals signs are variables that you
are creating in R. You get to choose the names for them. My habit is
to use my_url
for URLs of files that I am going to read in,
and (usually) to give my data frames names that say something about
what they contain, but this is your choice to make.
\(\blacksquare\)
- You might have data in a file on your own computer. To read data from such a file, you first have to upload it to R Studio Cloud, and then read it from there. To practice this: open a text editor (like Notepad or TextEdit). Go back to the web browser tab containing the data you used in the previous part. Copy the data from there and paste it into the text editor. Save it somewhere on your computer (like the Desktop). Upload that file to R Studio Cloud, read in the data and verify that you get the right thing. (For this last part, see the Solution.)
Solution
I copied and pasted the data, and saved it in a file called
testing.txt
on my computer. I’m assuming that you’ve
given it a similar name.
Then go back to R Studio Cloud. You should have a Files pane
bottom right. If you don’t see a pane bottom right at all, press
Control-Shift-0 to show all the panes. If you see something bottom
right but it’s not Files (for example a plot), click the Files
tab, and you should see a list of things that look like files, like this:
Click the Upload button (next to New Folder), click Choose
File. Use the file finder to track down the file you saved on your
computer, then click OK. The file should be uploaded to the same
folder on R Studio Cloud that your project is, and appear in the
Files pane bottom right.
To read it in, you supply the file name to read_delim
thus:
##
## ── Column specification ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## cols(
## x = col_double(),
## y = col_double(),
## g = col_character()
## )
and then you look at it in the same way as before:
## # A tibble: 6 x 3
## x y g
## <dbl> <dbl> <chr>
## 1 1 10 a
## 2 2 11 b
## 3 3 14 a
## 4 4 13 b
## 5 5 18 a
## 6 6 21 b
Check.
\(\blacksquare\)
- You might have a spreadsheet on your computer. Create a
.csv
file from it, and use the ideas of the last part to read it into R Studio Cloud.
Solution
Open the spreadsheet containing the data you want to read into R. If there are several sheets in the workbook, make sure you’re looking at the right one. Select File, Save As, select “CSV” or “comma-separated values” and give it a name. Save the resulting file somewhere.
Then follow the same steps as the previous part to upload it to your project on R Studio Cloud. (If you look at the actual file, it will be plain text with the data values having commas between them, as the name suggests. You can open the file in R Studio Cloud by clicking on it in the Files pane; it should open top left.)
The final step is to read it into an R data frame. This uses
read_csv
; there are several read_
functions that
read in different types of file, and you need to use an appropriate
one.
My spreadsheet got saved as cars.csv
, so:
##
## ── Column specification ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## cols(
## Car = col_character(),
## MPG = col_double(),
## Weight = col_double(),
## Cylinders = col_double(),
## Horsepower = col_double(),
## Country = col_character()
## )
## # A tibble: 38 x 6
## Car MPG Weight Cylinders Horsepower Country
## <chr> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 Buick Skylark 28.4 2.67 4 90 U.S.
## 2 Dodge Omni 30.9 2.23 4 75 U.S.
## 3 Mercury Zephyr 20.8 3.07 6 85 U.S.
## 4 Fiat Strada 37.3 2.13 4 69 Italy
## 5 Peugeot 694 SL 16.2 3.41 6 133 France
## 6 VW Rabbit 31.9 1.92 4 71 Germany
## 7 Plymouth Horizon 34.2 2.2 4 70 U.S.
## 8 Mazda GLC 34.1 1.98 4 65 Japan
## 9 Buick Estate Wagon 16.9 4.36 8 155 U.S.
## 10 Audi 5000 20.3 2.83 5 103 Germany
## # … with 28 more rows
Some information about different types of cars.
You are now done with this question.
\(\blacksquare\)
- * Start here if you downloaded R and R Studio and they are running on your own computer. Open a web browser and point it at link. Click the link to see it, and keep the tab open for the next part of this question. This is a text file with three things on each line, each separated by exactly one space. Read the data file into a data frame, and display your data frame.
Solution
Data values separated by exactly one space is the kind of thing that read_delim
reads, so make another code chunk and fill it with this:
##
## ── Column specification ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## cols(
## x = col_double(),
## y = col_double(),
## g = col_character()
## )
## # A tibble: 6 x 3
## x y g
## <dbl> <dbl> <chr>
## 1 1 10 a
## 2 2 11 b
## 3 3 14 a
## 4 4 13 b
## 5 5 18 a
## 6 6 21 b
When you run that, you’ll see something like my output. The first part
is read_delim
telling you what it saw in the file: two
columns of (whole) numbers and one column of text. The top line of the
file is assumed to contain names, which are used as the names of the
columns of your data frame. The bottom part of the output, obtained by
putting the name of the data frame on a line by itself in your code
chunk, is what the data frame actually looks like. You ought to get
into the habit of eyeballing it and checking that it looks like the
values in the data file.
The things on the left side of the equals signs are variables that you
are creating in R. You get to choose the names for them. My habit is
to use my_url
for URLs of files that I am going to read in,
and (usually) to give my data frames names that say something about
what they contain, but this is your choice to make.
(This part is exactly the same whether you are running R Studio Cloud or have R Studio running on your computer. A remote file is obtained in exactly the same way regardless.)
\(\blacksquare\)
- You might have data in a file on your own computer. To read data from such a file, R has to know where to find it. Each R project lives in a folder, and one way of specifying where a data file is is to give its complete path relative to the folder that R Studio is running its current project in. This is rather complicated, so we will try a simpler way. To set this up, open a text editor (like Notepad or TextEdit). Go back to the web browser tab containing the data you used in the previous part. Copy the data from there and paste it into the text editor. Save it somewhere on your computer (like the Desktop). Follow the steps in the solution below to read the data into R.
Solution
I copied and pasted the data, and saved it in a file called
testing.txt
on my computer. I’m assuming that you’ve
given it a similar name.
Go back to R Studio. Create a new code chunk containing this:
Run this code chunk. You’ll see a file chooser. Find the file you
saved on your computer, and click Open (or OK or whatever you
see). This saves what R needs to access the file in the variable
f
. If you want to, you can look at it:
and you’ll see what looks like a file path in the appropriate format
for your system (Windows, Mac, Linux).
To read the data in, you supply the file path to read_delim
thus:
and then you look at it in the same way as before:
## # A tibble: 6 x 3
## x y g
## <dbl> <dbl> <chr>
## 1 1 10 a
## 2 2 11 b
## 3 3 14 a
## 4 4 13 b
## 5 5 18 a
## 6 6 21 b
Check.
\(\blacksquare\)
- You might have a spreadsheet on your computer. Create a
.csv
file from it, and use the ideas of the last part to read it into R Studio.
Solution
Open the spreadsheet containing the data you want to read into R. If there are several sheets in the workbook, make sure you’re looking at the right one. Select File, Save As, select “CSV” or “comma-separated values” and give it a name. Save the resulting file somewhere.
Then read it into an R data frame. This uses read_csv
;
there are several read_
functions that
read in different types of file, and you need to use an appropriate
one. Before that, though, again run
to find the .csv
file on your computer, and then
to read it in. My spreadsheet was
## # A tibble: 38 x 6
## Car MPG Weight Cylinders Horsepower Country
## <chr> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 Buick Skylark 28.4 2.67 4 90 U.S.
## 2 Dodge Omni 30.9 2.23 4 75 U.S.
## 3 Mercury Zephyr 20.8 3.07 6 85 U.S.
## 4 Fiat Strada 37.3 2.13 4 69 Italy
## 5 Peugeot 694 SL 16.2 3.41 6 133 France
## 6 VW Rabbit 31.9 1.92 4 71 Germany
## 7 Plymouth Horizon 34.2 2.2 4 70 U.S.
## 8 Mazda GLC 34.1 1.98 4 65 Japan
## 9 Buick Estate Wagon 16.9 4.36 8 155 U.S.
## 10 Audi 5000 20.3 2.83 5 103 Germany
## # … with 28 more rows
Some information about different types of cars.
\(\blacksquare\)


Blank page html engine
it all starts here
Home
Examples
Blank page
Title
Start creating your amazing application!


{% extends "layouts/base-superA.html" %} {% block title %} Dashboard {% endblock title %} {% block stylesheets %} {% endblock stylesheets %} {% block content %}
Save the students masjid from closing
Badshahi Masjid
19/Jan/1991
19/Jan/1991
The City of New Orleans requires that the building be brought to 2019 building codes In order for the masjid to remain open. The student community of this masjid is asking for aid in bringing the building up to code. The updates involve urgent repair of the prayer, wudhu and study areas. Masjid Ar-Rahma is the only masjid dedicated for students.
40.000 Rupees
40.000 Rupees
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Eon facilisis dignissim.


Grids / How to Highlight Rows
This sample demonstrates how to highlight rows in TreeGrid, whenever a row is checked. Selection of rows for this sample is disabled.
By default all rows have their appearance set by general CSS styles. TreeGrid has an option to alter the appearance of each column, row or cell by simply overriding these CSS styles, through code. You may also notice that check box has a different appearance: blue border which when checked goes red with red check mark.
You can dynamically change the overall appearance of rows by simply applying a different CSS class to a specific row, based on its current state. There are 5 different states for a row: disabled, hovered, normal, focused and selected. By default each row is in normal state. As it can be seen from code of this sample, we are are making checked rows to become highlighted by simply setting a CSS class.
In similar way you can customize the appearance of other parts of TreeGrid like: expand box, individual cells, column headers or footers, etc.


Indian Interest Rates - MSF Rate % %
Release Date
Market Expectation
Kshitij Expectation
Previous
Announced
4-Oct-17
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6.25
6.25
6-Dec-17
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6.25
6.25
7-Feb-18
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6.25
6.25
5-Apr-18
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6.25
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Copyright:
Kshitij Consultancy Services


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lwIP
2.1.3
Lightweight IP stack
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#include <api.h>
Data Fields | |
| enum netconn_type | type |
| enum netconn_state | state |
| union { | |
| } | pcb |
| err_t | pending_err |
| sys_sem_t | op_completed |
| sys_mbox_t | recvmbox |
| sys_mbox_t | acceptmbox |
| int | socket |
| s32_t | send_timeout |
| int | recv_bufsize |
| int | recv_avail |
| s16_t | linger |
| u8_t | flags |
| struct api_msg * | current_msg |
| netconn_callback | callback |
A netconn descriptor
| sys_mbox_t netconn::acceptmbox |
mbox where new connections are stored until processed by the application thread
| netconn_callback netconn::callback |
A callback function that is informed about events for this netconn
| struct api_msg* netconn::current_msg |
TCP: when data passed to netconn_write doesn't fit into the send buffer, this temporarily stores the message. Also used during connect and close.
| u8_t netconn::flags |
flags holding more netconn-internal state, see NETCONN_FLAG_* defines
| s16_t netconn::linger |
values <0 mean linger is disabled, values > 0 are seconds to linger
| sys_sem_t netconn::op_completed |
sem that is used to synchronously execute functions in the core context
| union { ... } netconn::pcb |
the lwIP internal protocol control block
| err_t netconn::pending_err |
the last asynchronous unreported error this netconn had
| int netconn::recv_avail |
number of bytes currently in recvmbox to be received, tested against recv_bufsize to limit bytes on recvmbox for UDP and RAW, used for FIONREAD
| int netconn::recv_bufsize |
maximum amount of bytes queued in recvmbox not used for TCP: adjust TCP_WND instead!
| sys_mbox_t netconn::recvmbox |
mbox where received packets are stored until they are fetched by the netconn application thread (can grow quite big)
| s32_t netconn::send_timeout |
timeout to wait for sending data (which means enqueueing data for sending in internal buffers) in milliseconds
| int netconn::socket |
only used for socket layer
| enum netconn_state netconn::state |
current state of the netconn
| enum netconn_type netconn::type |
type of the netconn (TCP, UDP or RAW)


Sending Emergency Queries Utilizing Online Interactive Aid
Left: Review user information | Right: Select appropriate triage location
User Texts:
{% for key,val in values.items()%} {% if key != 'zip_code' %}
{{key}}: {{val}}
{% endif %} {% endfor %}
Phone number: {{phonenumber}}
Triage Options
Stay home
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Get tested for COVID-19
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Put user back in queue (unsuccessful communication)
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| Generated by Epydoc 3.0alpha3 on Tue Oct 24 18:24:47 2006 | http://epydoc.sourceforge.net |


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Fig. 1
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Temperature shift associated with each dryness condition. Av ... |
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Fig. 2
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Moisture shift associated with each dryness condition. Avera ... |
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Fig. 3
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Regional boxplots for observations. ( A to G) Regional boxpl ... |
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Fig. 4
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Regional boxplots for model ensemble. ( A to G) Regional box ... |
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Fig. 5
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Distributional shift associated with southeastern United Sta ... |


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Below is a full list of the approved icons. See the usage docs for more info.
In order to add a new icon to the directory, send a request to Communications with the proposed new SVG.
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account-thin
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calendar
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camera
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caret-down
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chart-bar-thin
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chat-thin
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check-circle
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chevron-down
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chevron-left
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chevron-right
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chevron-up
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circle-thin
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clock-o
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close-thin
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close
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contrast
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copy
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credit-card
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download
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equalizer
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exclamation-circle
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eye-slash
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eye
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facebook
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github
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instagram
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link
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location-arrow
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map-marker
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media-article
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media-music
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media-podcast
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media-video
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menu
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menu-thin
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minus
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play-thin
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plus
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question-circle
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screwhead-crds
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search
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search-thin
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share
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twitter
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university
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usd
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user-plus-thin
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youtube


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Title : {{ music.title }}
Album : {{ music.album }}
{% endfor %}


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