class: center, middle, inverse, title-slide # 2.4 — Property vs. Liability Remedies ## ECON 315 • Economics of the Law • Spring 2021 ### Ryan Safner
Assistant Professor of Economics
<EMAIL_ADDRESS>ryansafner/lawS21
lawS21.classes.ryansafner.com
--- class: inverse # Outline ### [Remedies: Injunctions vs. Damages](#7) ### [Unalienability](#35) --- # Two Normative Approaches to Law & Economics .pull-left[ .smaller[ Design the law to: 1) .hi-purple[Minimize the cost of bargaining] - .hi[Normative Coase]: “Structure the law so as to remove the impediments to private bargaining” 2) .hi-purple[Minimize the need for bargaining] - .hi[Normative Hobbes]: “Structure the law so as to minimize the harm caused by failures in private agreements” ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Two Normative Approaches to Law & Economics .pull-left[ .smallest[ - Compare the .hi-turquoise[costs] of each approach - **Normative Coase**: .hi-turquoise[cost of bargaining], lubricate private exchange - **Normative Hobbes**: .hi-turquoise[information costs] of determining how to efficiently allocate property rights ] .smaller[ - When .hi-purple[transaction costs are low] and .hi-purple[information costs are high], structure the law so as to .hi-purple[minimize transaction costs] - When .hi-purple[transaction costs are high] and .hi-purple[information costs are low], structure the law so as to .hi-purple[allocate property rights to whomever values them the most] ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # What Would an Efficient Property Law Look Like? .pull-left[ - Recall the 4 questions any property system must answer: 1. What can be privately owned? 2. What can (and can't) an owner do with her property? 3. How are property rights established? 4. What remedies are available when property rights are violated? ] .pull-right[ .center[ ![](../images/propertybundleofrights.png) ] ] --- # What Would an Efficient Property Law Look Like? .pull-left[ - Recall the 4 questions any property system must answer: 1. What can be privately owned? 2. What can (and can't) an owner do with her property? 3. How are property rights established? 4. .hi-purple[What remedies are available when property rights are violated?] ] .pull-right[ .center[ ![](../images/propertybundleofrights.png) ] ] --- class: inverse, center, middle # Remedies: Injunctions vs. Damages --- # Some Common Law Terms & History .pull-left[ .quitesmall[ - .hi[Legal remedy]: focuses on relief via payment of money compensation for damages to “make the Plaintiff whole” - grew out of Courts of Law - .hi[Equitable remedy]: an order by the court to provide relief requiring the Defendant perform (or refrain from) some action - grew out of the Court of Chancery, originally made to streamline - most typically, an .hi[injunction] which .hi[enjoins] party to (not) perform a specific action - A court ruling on a case may provide *both* types of relief - Note legal remedies are “backward-looking” vs. equitable remedies are “forward-looking” ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Some Common Law Terms & History .pull-left[ - We often summarize by referring to the difference between: - .hi[“Property rule”]: equitable relief for .hi-purple[appropriation], .hi-purple[trespass], .hi-purple[interfering] with another's property - More common in law of property - .hi[“Liability rule”]: damages awarded for broken promises and accidents - More common in law of contracts & torts ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Applied to Our Farmer-Rancher Example .pull-left[ - With Rancher's cattle straying onto Farmer's crops - .hi[Liability rule]: Court may require Rancher to compensate Farmer for .hi-purple[damages] - .hi[Property rule]: Court may .hi-purple[enjoin] Rancher from letting cattle trespass onto Farm (if Farmer found to have property right to be free of cattle's interference) ] .pull-right[ .center[ ![:scale 70%](../images/wheat2.jpg) ![:scale 70%](../images/grazing_cattle.jpg) ] ] --- # Calabresi & Melamed on Efficient Remedies .left-column[ .center[ ![:scale 70%](../images/calabresi.jpg) .smallest[ Guido Calabresi 1932— Fmr. U.S. 2nd Circuit Judge ] ] ] .right-column[ - **Guido Calabresi**: Major figure in Law & Economics field - 1994—2009 Judge of U.S Court of Appeals for the 2nd Circuit - Yale Law Professor - **A. Douglas Melamed**: Stanford Law professor specializing in antitrust law; general counsel of Intel; antitrust lawyer - Along with Coase (1960), one of the first applications of a consistent framework to unify property, contract, and (esp.) tort law ] --- # Calabresi & Melamed on Efficient Remedies .left-column[ .center[ ![:scale 70%](../images/calabresi.jpg) .smallest[ Guido Calabresi 1932— Fmr. U.S. 2nd Circuit Judge ] ] ] .right-column[ - How are property rights .hi-purple[enforced]? What .hi-purple[remedies] are used when rights are violated? - C&M: Treat property and liability law (different areas) under common framework - Both are cases of .hi[entitlements] - is the Farmer .hi[entitled] to land free from trespassing animals? - is the Rancher .hi[entitled] to the natural actions of her cattle? ] --- # Three Ways to Protect Entitlements .left-column[ .center[ ![:scale 70%](../images/calabresi.jpg) .smallest[ Guido Calabresi 1932— Fmr. U.S. 2nd Circuit Judge ] ] ] .right-column[ .smallest[ 1. .hi[Property] rule/.hi[injunctive] relief - violation of entitlement punished as a .hi-turquoise[crime] (not mere restitution owed) - but entitlement is .hi-turquoise[negotiable] (owner can choose to sell or not exercise the right) 2. .hi[Liability] rule/.hi[damages] - violations of entitlement require .hi-turquoise[compensation] - Defendant pays .hi-turquoise[damages] to make the Plaintiff whole 3. .hi[Inalienability] rule - violations are punished as a .hi-turquoise[crime] - but entitlement **cannot** be sold or waived ] ] --- # Calabresi & Melamed on Efficient Remedies .left-column[ .center[ ![:scale 70%](../images/calabresi.jpg) .smallest[ Guido Calabresi 1932— Fmr. U.S. 2nd Circuit Judge ] ] ] .right-column[ - What rule is more efficient? - Again: with low transaction costs, Coase reminds is it would not matter! - But the different rules will still lead to different distributions, and there are transaction costs to worry about ] --- # Calabresi & Melamed on Efficient Remedies .left-column[ .center[ ![:scale 70%](../images/calabresi.jpg) .smallest[ Guido Calabresi 1932— Fmr. U.S. 2nd Circuit Judge ] ] ] .right-column[ - .hi[Liability] (damages) rule is more favorable to the Defendant (injurer) - injurer has higher BATNA — has option to just violate and compensate - .hi[Property] rule is more favorable to the Plaintiff (injuree) - punishment is severe - if two sides need to negotiate, injurer's BATNA is lower ] --- # Comparing Injunctive Relief to Damages: Example .pull-left[ .smallest[ .bg-washed-green.b--dark-green.ba.bw2.br3.shadow-5.ph4.mt5[ .hi-green[Example]: An .red[electric company (E)] emits smoke, which dirties the laundry at a nearby .blue[laundromat (L)]. Suppose: ] - .red[E] earns profits of .red[1,000] - Without smoke, .blue[L] would earn profits of .blue[300] - Smoke reduces L's profits from .blue[300] to .blue[100] - .red[E] could install scrubbers to cease pollution at cost .red[-500] - .blue[L] could prevent smoke damage by installing a filter at cost .blue[-100] ] ] .pull-right[ .center[ ![](../images/pollution3.jpg) ] ] --- # Comparing Injunctive Relief to Damages: Example .pull-left[ .smallest[ .bg-washed-green.b--dark-green.ba.bw2.br3.shadow-5.ph4.mt5[ .hi-green[Example]: An .red[electric company (E)] emits smoke, which dirties the laundry at a nearby .blue[laundromat (L)]. Suppose: ] - .red[E] earns profits of .red[1,000] - Without smoke, .blue[L] would earn profits of .blue[300] - Smoke reduces L's profits from .blue[300] to .blue[100] - .red[E] could install scrubbers to cease pollution at cost .red[-500] - .blue[L] could prevent smoke damage by installing a filter at cost .blue[-100] ] ] .pull-right[ .center[ ![](../images/smokepollutiongame1.png) ] ] --- # Comparing Injunctive Relief to Damages: Example .pull-left[ .smallest[ - Consider the non-cooperative outcomes 1. Polluter's rights (.hi[no remedy]) - .red[E] earns .red[1,000] - .blue[L] installs filters, earns .blue[300-100=200] ] ] .pull-right[ .center[ ![](../images/smokepollutiongame2.png) ] ] --- # Comparing Injunctive Relief to Damages: Example .pull-left[ .smallest[ - Consider the non-cooperative outcomes 1. Polluter's rights (.hi[no remedy]) - .red[E] earns .red[1,000] - .blue[L] installs filters, earns .blue[300-100=200] 2. .blue[Laundromat] has right to .hi[damages] - .red[E] earns .red[1,000-200=800] - .blue[L] earns .blue[300-200+200=300] ] ] .pull-right[ .center[ ![](../images/pollution3.jpg) ] ] --- # Comparing Injunctive Relief to Damages: Example .pull-left[ .smallest[ - Consider the non-cooperative outcomes 1. Polluter's rights (.hi[no remedy]) - .red[E] earns .red[1,000] - .blue[L] installs filters, earns .blue[300-100=200] 2. .blue[Laundromat] has right to .hi[damages] - .red[E] earns .red[1,000-200=800] - .blue[L] earns .blue[300-200+200=300] 3. .blue[Laundromat] has right to .hi[injunction] - .red[E] installs .bred[scrubbers], earns .red[1,000-500=500] - .blue[L] earns .blue[300] ] ] .pull-right[ .center[ ![](../images/pollution3.jpg) ] ] --- # Noncooperative Payoffs | | Polluter's Rights | Damages | Injunction | |----|------------------:|--------:|-----------:| | .red[E] payoff (non-coop) | .red[1,000] | .red[800] | .red[500] | | .blue[L] payoff (non-coop) | .blue[200] | .blue[300] | .blue[300] | | **Joint payoff (non-coop)** | **1,200** | **1,100** | **800** | - Polluter's rights is most efficient in non-cooperative case (no bargains) - .blue[L] buys .blue[filters] to reduce smoke damage (cheapest) - Maximized joint payoff --- # Payoffs with Potential Bargaining | | Polluter's Rights | Damages | Injunction | |----|------------------:|--------:|-----------:| | .red[E] payoff (non-coop) | .red[1,000] | .red[800] | .red[500] | | .blue[L] payoff (non-coop) | .blue[200] | .blue[300] | .blue[300] | | **Joint payoff (non-coop)** | **1,200** | **1,100** | **800** | | .hi-purple[Gains from cooperation] | .purple[0] | .purple[100] | .purple[400] | .smaller[ - What if they were to bargain from these outcomes? - **Polluter's Rights**: No gains to be had (already efficient outcome) - **Damages**: .purple[100] to be gained (.red[E] was paying .red[-200] to reduce damage that can be prevented at .blue[-100] by .blue[L]) - **Injunction**: .purple[400] to be gained (.red[E] was paying .red[-500] to reduce damage that can be prevented at .blue[-100] by .blue[L]) ] --- # Payoffs with Potential Bargaining | | Polluter's Rights | Damages | Injunction | |----|------------------:|--------:|-----------:| | .red[E] payoff (non-coop) | .red[1,000] | .red[800] | .red[500] | | .blue[L] payoff (non-coop) | .blue[200] | .blue[300] | .blue[300] | | **Joint payoff (non-coop)** | **1,200** | **1,100** | **800** | | .hi-purple[Gains from cooperation] | .purple[0] | .purple[100] | .purple[400] | - Again, for simplicity, assume parties split any .hi-purple[gains from cooperation] 50-50 --- # Payoffs with Potential Bargaining | | Polluter's Rights | Damages | Injunction | |----|------------------:|--------:|-----------:| | .red[E] payoff (non-coop) | .red[1,000] | .red[800] | .red[500] | | .blue[L] payoff (non-coop) | .blue[200] | .blue[300] | .blue[300] | | **Joint payoff (non-coop)** | **1,200** | **1,100** | **800** | | .hi-purple[Gains from cooperation] | .purple[0] | .purple[100] | .purple[400] | | .red[E] payoff (deal) | .red[1,000] | .red[850] | .red[700] | | .blue[L] payoff (deal) | .blue[200] | .blue[350] | .blue[500] | | **Joint payoff (deal)** | **1,200** | **1,200** | **1,200** | - Gains from cooperation larger under Injunction than Damages (.red[E] has lower BATNA) - .hi-turquoise[Coase Theorem] again implies we get the same efficient outcome, max'ed joint payoffs under any rule --- # Comparing Damages and Injunctions .pull-left[ - Injunctions are generally cheaper for court to administer - no need to estimate value of harm done - But damages are generally more efficient when bargaining is unlikely | | Damages | Injunction | |----|--------:|-----------:| | .red[E] payoff (non-coop) | .red[800] | .red[500] | | .blue[L] payoff (non-coop) | .blue[300] | .blue[300] | | **Joint payoff (non-coop)** | **1,100** | **800** | ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Comparing Damages and Injunctions .pull-left[ - In general, three possible outcomes: injurer prevents harm, injuree prevents harm, or nobody prevents harm (injurer pays damages for it instead) - Efficient outcome is the cheapest of the three - **Damages**: injurer can prevent harm or compensate for it, injurer chooses whatever is cheapest - **Injunction**: injurer can only prevent harm ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Summing Up Damages and Injunctions .pull-left[ - So per Coase (1960), any rule leads to efficiency under no transaction costs - Injunctions are cheaper to implement - Damages lead to more efficient outcomes when transaction costs are high ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # Calabresi & Melamed on Efficient Remedies .left-column[ .center[ ![:scale 70%](../images/calabresi.jpg) .smallest[ Guido Calabresi 1932— Fmr. U.S. 2nd Circuit Judge ] ] ] .right-column[ - When .hi-purple[transaction costs are low], a .hi[property rule] (injunctive relief) is more efficient - When .hi-purple[transaction costs are high], a .hi[liability rule] (damages) is more efficient ] --- # This is Consistent With Before .pull-left[ .smallest[ - When .hi-purple[transaction costs are low] and .hi-purple[information costs are high], structure the law so as to .hi-purple[minimize transaction costs] - .hi[Property] rule does this: clarify right and allow trade - When .hi-purple[transaction costs are high] and .hi-purple[information costs are low], structure the law so as to .hi-purple[allocate property rights to whomever values them the most] - .hi[Liability] rule does this: give injurer right to violate entitlement when efficient, even without prior consent ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ] --- # This is Consistent With Our Previous Principle > “Private bargaining is unlikely to succeed in disputes involving a large number of geographically dispersed strangers because communication costs are high, monitoring is costly, and strategic behavior is likely to occur.” > “.hi[Large numbers of land owners] are typically affected by .hi[nuisances], such as air pollution or the stench from a feedlot. In these cases, .hi[damages are the preferred remedy].” > “On the other hand, .hi[property disputes generally involve a small number of parties who live near each other] and can monitor each others’ behavior easily after reaching a deal; so .hi[injunctive relief is usually used] in these cases.” .source[Cooter and Ulen] --- # Injunctive Relief for When Transaction Costs are Low .pull-left[ - Cheaper for court to administer - With low transaction costs, we expect parties to bargain when right is inefficiently allocated ] .pull-right[ .center[ ![:scale 100%](../images/propertyrights.png) ] ] --- # Injunctive Relief for When Transaction Costs are Low .pull-left[ - Cheaper for court to administer - With low transaction costs, we expect parties to bargain when right is inefficiently allocated - .hi-purple[But do they?] ] .pull-right[ .center[ ![:scale 100%](../images/propertyrights.png) ] ] --- # Injunctive Relief for When Transaction Costs are Low .pull-left[ .smallest[ > “When transaction costs preclude bargaining, the court should protect a right by an injunctive remedy if it knows which party values the right relatively more and it does not know how much either party values it absolutely.” > “Conversely, the court should protect a right by a damages remedy if it knows how much one of the parties values the right absolutely and it does not know which party values it relatively more.” ] .source[Cooter and Ulen] ] .pull-right[ .center[ ![:scale 100%](../images/transactionscosts.JPG) ] ] --- # Damages for When Transaction Costs are High .pull-left[ .smallest[ - Examine 20 nuisance cases; found no bargaining made after court judgment > “In almost every case the lawyers said that acrimony between the parties was an important obstacle to bargaining...Frequently the parties were not on speaking terms...The second recurring obstacle involves the parties’ disinclination to think of the rights at stake… as readily commensurable with cash.” ] .source[Farnsworth, Ward, 1999, “Do Parties to Nuisance Cases Bargain After Judgment? A Glimpse Inside The Cathedral”] ] .pull-right[ .center[ ![:scale 100%](../images/transactionscosts.JPG) ] ] --- class: inverse, center, middle # Unalienability --- # Third Way to Protect Entitlements: Unalienability Rule .left-column[ .center[ ![:scale 70%](../images/calabresi.jpg) .smallest[ Guido Calabresi 1932— Fmr. U.S. 2nd Circuit Judge ] ] ] .right-column[ - .hi[Inalienability]: when an entitlement is not transferable or sellable (regardless of consent) - Entitlement not see as “property” - .hi-green[Examples]: sex, kidneys, cocaine, babies, nuclear weapons, votes - Often the result of statutes governing “health, safety, and morals” for the public good, .hi[paternalism] ] --- # Unalienability .pull-left[ - From a Coasian perspective, this does not appear to make sense - Let people trade their entitlements as they please to achieve efficient allocation! - Does makes more sense in certain scenarios (when allocating rights imposes an externality) ] .pull-right[ .center[ ![](../images/notforsale.png) ] ] --- # Unalienability .pull-left[ - .hi-green[Example 1]: enriched uranium ] .pull-right[ .center[ ![](../images/uranium.jpg) ] ] --- # Unalienability .pull-left[ - .hi-green[Example 2]: human organs like kidneys, lungs ] .pull-right[ .center[ ![](../images/organtransplant.jpeg) ] ] --- # Unalienability .pull-left[ - .hi-green[Example 2]: human organs like kidneys, lungs ] .pull-right[ .center[ ![:scale 80%](../images/kidneyregret.png) ] ] --- # Unalienability .left-column[ .center[ ![](../images/jefferson1.jpg) .smallest[ Thomas Jefferson 1743—1826 ]] ] .right-column[ > “We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain unalienable Rights, that among these are Life, Liberty and the pursuit of Happiness” .source[1776, *United States Declaration of Independence*] ] --- # Alternative Interpretation of Unalienability .left-column[ .center[ ![](../images/alroth.jpg) .smallest[ Alvin Roth 1951— 2012 Economics Nobel ] ] ] .right-column[ - .hi[“Repugnant markets”]: exchanges made illegal because people find them morally or aesthetically objectionable > “Many Californians not only don’t wish to eat horses or dogs themselves, but find it repugnant that anyone else should do so, and they enacted this repugnance into California law… in 1998” .source[Roth, Alvin E, 2007, “Repugnance as a Constraint on Markets,” *Journal of Economic Perspectives* 21(3)] ] --- # Alternative Interpretation of Unalienability .pull-left[ - .hi[“Repugnant markets”]: exchanges made illegal because people find them morally or aesthetically objectionable - .hi-green[Examples]: Ticket scalping, price gouging, gambling, drugs, prostitution, dwarf tossing, paying for kidneys, babies, etc - Note what people find repugnant changes over time! (charging interest) ] .pull-right[ .center[ ![:scale 70%](../images/disgust.png) ] ] --- # Summing Up Remedies .pull-left[ .smallest[ - When transaction costs are low, use .hi[injunctive relief] - either rule will lead to efficiency (Coase) - but injunctions are easier to implement - .hi-purple[Normative Coase]: design law to .hi-purple[facilitate exchange] - When transaction costs are high, use .hi[damages] - if bargaining unlikely, damages lead to more efficient outcomes - .hi-purple[Normative Hobbes]: design law to .hi-purple[not rely on bargaining] ] ] .pull-right[ .center[ ![:scale 100%](../images/court1.jpg) ] ]


lingvo.core.plot module¶
Utilities for generating image summaries using matplotlib.
-
lingvo.core.plot.
AddPlot
(unused_fig, axes, data, title=u'', xlabel=u'', ylabel=u'', fontsize='small', xlim=None, ylim=None, suppress_xticks=False, suppress_yticks=False)[source]¶ Convenience function to add a plot.
-
lingvo.core.plot.
AddImage
(fig, axes, data, cmap='bone_r', clim=None, show_colorbar=True, title=u'', xlabel=u'', ylabel=u'', fontsize='small', suppress_xticks=False, suppress_yticks=False)[source]¶ Convenience function to plot data as an image on the given axes.
-
class
lingvo.core.plot.
_SubplotMetadata
(tensor_list, plot_func)¶ Bases:
tuple
-
_asdict
()¶ Return a new OrderedDict which maps field names to their values
-
_fields
= ('tensor_list', 'plot_func')¶
-
classmethod
_make
(iterable, new=<built-in method __new__ of type object>, len=<built-in function len>)¶ Make a new _SubplotMetadata object from a sequence or iterable
-
_replace
(**kwds)¶ Return a new _SubplotMetadata object replacing specified fields with new values
-
plot_func
¶ Alias for field number 1
-
tensor_list
¶ Alias for field number 0
-
-
class
lingvo.core.plot.
MatplotlibFigureSummary
(name, figsize=(8, 10), max_outputs=3, subplot_grid_shape=None, gridspec_kwargs=None, plot_func=<function AddImage>, shared_subplot_kwargs=None)[source]¶ Bases:
object
Helper to minimize boilerplate in creating a summary with several subplots.
Typical usage:
>>> fig_helper = plot.MatplotlibFigureSummary( ... 'summary_name', shared_subplot_kwargs={'xlabel': 'Time'}) >>> fig_helper.AddSubplot([tensor1], title='tensor1') >>> fig_helper.AddSubplot([tensor2], title='tensor2', ylabel='Frequency') >>> image_summary = fig_helper.Finalize()
-
AddSubplot
(tensor_list, plot_func=None, **kwargs)[source]¶ Adds a subplot from tensors using plot_fun to populate the subplot axes.
Parameters: - tensor_list – A list of tensors to be realized as numpy arrays and passed as arguments to plot_func. The first dimension of each tensor in the list corresponds to batch, and must be the same size for each tensor.
- plot_func – A function with signature f(fig, axes, data1, data2, …, datan, **kwargs) that will be called with the realized data from tensor_list to plot data on axes in fig. This function is called independently on each element of the batch. Overrides plot_func passed in to the constructor.
- **kwargs – A dict of additional non-tensor keyword args to pass to plot_func when generating the plot, overridding any shared_subplot_kwargs. Useful for e.g. specifying a subplot’s title.
-
-
lingvo.core.plot.
_RenderMatplotlibFigures
(figsize, max_outputs, plot_func, *numpy_data_list)[source]¶ Renders a figure containing several subplots using matplotlib.
This is an internal implementation detail of MatplotlibFigureSummary.Finalize and should not be called directly.
The unconventional function signature is used to work around the behavior of
tf.py_func
which always passes in different tensors as positional arguments.Parameters: - figsize – A 2D tuple containing the overall figure (width, height) dimensions in inches.
- max_outputs – The maximum number of images to generate.
- plot_func – A function with signature f(fig, data1, data2, …, datan) that will be called with *numpy_data_list to plot data in fig.
- *numpy_data_list – A list of numpy matrices to plot specified as separate arguments.
Returns: A numpy 4D array of type np.uint8 which can be used to generate a
tf.image_summary
when converted to a tf tensor.
-
lingvo.core.plot.
_FigureToSummary
(name, fig)[source]¶ Create tf.Summary proto from matplotlib.figure.Figure .
-
lingvo.core.plot.
Matrix
(name, figsize, matrix, setter=None, **kwargs)[source]¶ Plot a numpy matrix and generates tf.Summary proto for it.
Parameters: - name – Image summary name.
- figsize – A 2D tuple containing the overall figure (width, height) dimensions in inches.
- matrix – A 2D numpy array.
- setter – A callable taking (fig, axes). Useful to fine-control layout of the figure, xlabel, xticks, etc.
Returns: A
tf.Summary
proto contains one image visualizing ‘matrix.
-
lingvo.core.plot.
Curve
(name, figsize, xs, ys, setter=None, **kwargs)[source]¶ Plot curve(s) to a
tf.Summary
proto.Parameters: - name – Image summary name.
- figsize – A 2D tuple containing the overall figure (width, height) dimensions in inches.
- xs – x values for matplotlib.pyplot.plot.
- ys – y values for matplotlib.pyplot.plot.
- setter – A callable taking (fig, axes). Useful to fine-control layout of the figure, xlabel, xticks, etc.
- **kwargs – Extra args for matplotlib.pyplot.plot.
Returns: A
tf.Summary
proto contains the line plot.


DEAR Friend, Please reply to<EMAIL_ADDRESS>I know that this letter will come to you as a surprise considering the fact that we have not met before.May the Almighty God bless you as you read this email.I am trully looking for someone that will assist me with a business that has to do with my family estate which my late father left behind for us.i am contacting you based on the fact that i want someone that is not known to my family to assist me in this business and this is for security reasons which i will explain to you as we make progress. I am the first son of the late Joseph Desire Mobutu, the former President of "ZAIRE" now democratic republic of congo .I am presently on political asylum in Nigeria . I got your contact over the internet during my search for a person that will assist me in this business.this became neccessary as i do not want anybody known to me or my family to be associated with this money. I want you to note that this business will benefit both of us and that it is 100% risk free. However, you must confirm your ability to handle this because it involves a large amount of money. The funds "THIRTY SEVEN MILLION UNITED STATES DOLLARS" ($37million)is my share of my father's estate. I boxed and shipped the money to a security company abroad at the peak of the a political uprising that rocked my country few years ago. Now that the crisis has ended , I need a trustworthy person to proceed to the place of the security company in order to clear the fund and afterwards,i will come to your country for us to start a joint business venture as i do not have the intention of bringing the funds back to Africa for a very long time.Note that I will send to you the relevant documents that will enable you take possession of the fund for onward investment for our mutual benefit. All I need from you is as follows: 1. Your confirmation of your ability to handle this business for me. 2.your word that you will keep this business as confidential as possible at all times until we conclude this business. 3. Your telephone and fax numbers for communication. 4. Your full permanent address. As soon as I get the above information from you, I will disclose to you the name and the country of the security company, the contact of the diplomat that i have hired to assist us in this business,as well as your name and particulars to the security company as my representative and my partner to enable them contact you accordingly. As we make progress,i will send to you a"LETTER OF AUTHORITY" and "AGREEMENT LETTER" to enable you clear the fund on my behalf. Note that this is a very safe transaction as this funds is my share of my father's estate.Please reply to<EMAIL_ADDRESS>I await your response to enable us proceed. Regards, Nzanga Joseph Desire Mobutu ___________________________________________________________________________ Mail sent from WebMail service at PHP-Nuke Powered Site - http://www.blitz-krieg.de


--- layout: default layout_keyword: knowledge_base_page title: Group Toolbox tags: group_admin_pages left_col_section_nav: [basic_user_nav] user_help_videos: [basic_user_videos] ---
As a group administrator, you have access to buttons and links in your Group Toolbox that other group members will not see.
The buttons and links that appear in your Group Toolbox are based on the features you have enabled for the group.
The most common tools used by group administrators appear as buttons, so you have quick access to communicate and share with your group members.

You can close and reopen your Group Toolbox by clicking [open] or [close] at the top right of your toolbox at any time.


Django forms are easily rendered as tables, paragraphs, and unordered lists. However, elegantly rendered div based forms are something you have to do by hand. The purpose of this application is to provide a simple tag and/or filter that lets you quickly render forms in a div format.
Uni-form has been selected as the base model for the design of the forms.
Django Uni-Form lets you easily display Django forms as divs.
Contents:


Application middlewares are configured at application level (which run for every request handled by dino). Dinoloop supports both sync/async versions of middlewares. The following is a list of classes for creating dinowares at application level
1. RequestStartMiddleware
RequestStart middlewares are the first to run when dino receives a request. Please read
Flow of dinowares.
Return values of middlewares are ignored. The only way to pass the control to next middleware is using next()
- You have to extend RequestStartMiddleware and implement invoke() method.
- return type is void for middlewares because return values are ignored.
- Request, Response, NextFunction are the Expressjs types, whatever you can do with Expressjs might get done.
- You can read next(err) on Expressjs.
- RequestStart middlewares are similar to Expressjs middlewares in functioning. However, they provide a class-based approach with Dependency Injection support as shown below
2. RequestStartMiddlewareAsync
Asnyc version of RequestStart middleware.
3. RequestEndMiddleware
RequestEnd middlewares are the last to run in the chain of middlewares. Please read
Flow of dinowares.
- result is a placeholder for the return value received from an action method.
4. RequestEndMiddlewareAsync
Async version of RequestEnd middleware.
5. ErrorMiddleware
Following example explains how to create error middlewares that handle uncaught exceptions/errors thrown by the application.
- err is the placeholder for original Error that occured.
- Please read Express docs for robust error handling.
6. ErrorMiddlewareAsync
Async version of ErrorMiddleware.
7. ApplicationStartMiddleware
ApplicationStart middlewares run as soon as server starts and they run only once. Here we can put startup or initialization
code.
AppStartMiddleware are normal typescript classes which execute as normal javascript function calls. They dont require next() to pass the control to next middleware.
- You can register multiple AppStartMiddleware and their execution is based on the order of registration.
- Currently, there is no async version of AppStartMiddleware which is planned to be released in future versions.
- AppStartMiddleware are not dinowares since they dont handle user request, hence they dont require invoking next().


{% load i18n %} {% load foirequest_tags %} {% load account_tags %} {% load form_helper %}
{% if object.status_is_final %} {% blocktrans with title=object.title %}The request "{{ title }}" received documents that we are not allowed to publish. However, every person can get individual access to these documents by requesting them below.{% endblocktrans %} {% else %} {% blocktrans with title=object.title %}The request "{{ title }}" is for documents that we are not allowed to publish. However, every person can get individual access to these documents by requesting them just for themselves.{% endblocktrans %} {% endif %}
{% if user.is_authenticated %} {% if object.user == user %}{% blocktrans with email=SITE_EMAIL %}You stated that you are not allowed to publish the received documents. If this was a mistake, please contact {{ email }}.{% endblocktrans %}
{% else %} {% if object.same_as.user == user %}{% blocktrans %}You made the original request.{% endblocktrans %}
{% else %} {% check_same_request object user "same_request" %} {% if same_request %} {% blocktrans %}You made an identical request.{% endblocktrans %} {% else %} {% endif %} {% endif %} {% endif %} {% else %} {% endif %}{% blocktrans count counter=object.identical_count %}So far one person also requested this document.{% plural %}So far {{ counter }} people requested this document.{% endblocktrans %}


Sokkia Guides and Manuals Collection
Ultimate Surveying Spreadsheets Tools for Surveyors
Leica Social Support Guides
Topcon Positioning Social Support Guides
Trimble Social Support Guides


This test checks for a regression against rdar://problem/4214080 document.embeds: embeds[0].Play() undefined at languageguide.org.
Each test below states its expected outcome.


“Low Fat” Virtualization
6e Séminaire fribourgeois
Linux embarqué
Dr Jacques Supcik
Ecole d’ingénieurs et d’architectes de Fribourg
8 mai 2014
“Classical” Virtualization…
Effective…
but not light
Virtualization needs a lot of resources
Virtualization works best with special hardware
So what about a more “skinny” virtualization
Types of Virtualization
chroot
- The chroot system call was introduced during development of Version 7 Unix in
1979 is was available since 1982
(32 years old).
- Provides (partial) file system isolation only.
- “root” users can still escape chroot.
- requires some manual linking (or copying) of system files.
BSD's “Jail”
BSD's “Jail”
- Available since 1998 (16 years old).
- Provides disk and CPU quotas, memory limits, network and root privilege
isolation.
OpenVZ
- Available since 2005 (9 years old).
- Requires a special kernel.
- Adds I/O rate limiting, partition checkpointing and live migration.
- Still used by hosting companies to provide virtual private servers.
OpenVZ
Source: OpenVZ Web site
- Container looks like a normal Linux system. It has standard startup scripts,
software from vendors can run inside Container without OpenVZ-specific modifications or adjustment.
- A user can change any configuration file and install additional software.
- Containers are fully isolated from each other (file system, processes, Inter Process
Communication (IPC), sysctl variables).
OpenVZ
Source: OpenVZ Web site
- Containers share dynamic libraries, which greatly saves memory.
- Processes belonging to a Container are scheduled for execution on all available
CPUs. Consequently, Containers are not bound to only one CPU and can use all available CPU power.
LXC Linux Container
LXC Linux Container
- Available since 2008 (6 years old).
- Relies on the Linux kernel “cgroups” functionality that
was released in version 2.6.24.
- Full file system isolation and root privilege isolation since version 1.0
(February 2014 / Linux kernel 3.8)
- No partition checkpointing and no live migration!
- “chroot on steroids”.
Cgroups (control groups)
Name space Isolation
- PID namespace : Isolation for the allocation of process identifiers.
- Network namespace : Isolates the NIC, iptables rules, routing, etc.
- “UTS” namespace : Allows changing the hostname.
- Mount namespace : Allows creating a different file system layout.
- IPC namespace : Isolates the System V IPC.
Docker
- Available since 2013 (1 year
old young).
- Based on LXC.
- Is currently under heavy development. Docker should not be used in production
(yet).
- “Docker is an open-source engine that automates the deployment of any
application as a lightweight, portable, self-sufficient container that will run virtually
anywhere.”
Docker
If you want to try “Docker” you can easilly do it on a “Droplet” at Digital
Ocean. (5$ for 1 month)
Thank You!
References
- http://japanese.lingualift.com/blog/what-sumo-eat-wrestlers-diet/
- http://community.futureshop.ca/t5/Tech-Blog/How-to-build-a-PC-How-to-upgrade-your-RAM/ba-p/426769
- https://en.wikipedia.org/wiki/Western_Digital_Raptor
- http://www.pcper.com/news/General-Tech/ARM-aims-make-TSMC-Fab-choice-their-customers
- http://www.reflexandwellnessclinic.com/projects/services/
- https://en.wikipedia.org/wiki/Chroot
- http://sysadvent.blogspot.ch/2010/12/day-14-freebsd-jails.html
- http://openvz.org/User_Guide/OpenVZ_Philosophy
- https://linuxcontainers.org/
- http://www.linuxadvocates.com/2013/04/linux-containers-and-why-they-matter.html
- https://www.docker.io/
- https://en.wikipedia.org/wiki/Operating_system-level_virtualization
- https://en.wikipedia.org/wiki/LXC


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your browser doesn't support audio tag
Web audio analyzer and MIR application
Select an audio file and hit play button.
RMS meter
L
R
Peak
L
R
RESET PEAKS
Select features star position:
3:
rms
energy
zcr
flatness
slope
centroid
rolloff
spread
skewness
kurtosis
2:
rms
energy
zcr
flatness
slope
centroid
rolloff
spread
skewness
kurtosis
4:
rms
energy
zcr
flatness
slope
centroid
rolloff
spread
skewness
kurtosis
1:
rms
energy
zcr
flatness
slope
centroid
rolloff
spread
skewness
kurtosis
5:
rms
energy
zcr
flatness
slope
centroid
rolloff
spread
skewness
kurtosis
All features results
rms:
energy:
zcr:
centroid hz:
flatness:
slope:
rolloff hz:
spread:
skewness:
kurtosis:
Spectrum analyzer
Spectrogram


Previous: Define-method-combination Arguments Lambda Lists, Up: Lambda Lists
In a number of situations, a documentation string can appear amidst a series of declare expressions prior to a series of forms.
In that case, if a string S appears where a documentation string is permissible and is not followed by either a declare expression or a form then S is taken to be a form; otherwise, S is taken as a documentation string. The consequences are unspecified if more than one such documentation string is present.


My name is Batool Ayyad, I'm 25 years old, I studied electrical engineering al a Balqa university and graduated in 2020. My favorit things to do are traveling and meeting new people.
Job experience
- Fast food crew/Barista at Dunkin Donuts
- Relail at Noah’s ark water park
Education
- studied electrical engineering al a Balqa university
- studied softweer developer developing at LTUS
My Top Ten Series:
-
Anne with an e
-
breaking bad
-
Vikings
-
GOT
-
Peaky blinders
-
Last kingdom
-
Friends
-
la casa de papel
-
Chernobyl
-
When they see us


// Example: void render() { load_camera(); // Create a medium sized iso surface. static CIsosurface iso; iso.setSize(10, 10, 10); // Create a metaball. CIsosurfaceMetaball ball; ball.p[0] = sin(time); ball.p[1] = 0.0; ball.p[2] = cos(time); ball.a = 1.0; iso.calculate(&ball, 1); // Calculate energy values using metaballs. iso.calculateNormals(); // Calculate normals. // Output triangles. CIsosurfaceVertex v[300]; glVertexPointer(GL_FLOAT, 3, v, sizeof(CIsosurfaceVertex)); glEnableClientState(GL_NORMAL_ARRAY); glNormalPointer(GL_FLOAT, v, sizeof(CIsosurfaceVertex)); glEnableClientState(GL_VERTEX_ARRAY); glBegin(GL_TRIANGLES); { iso.output(100, v, render_triangle); } glEnd(); } void render_triangle(int triangles, CIsosurfaceVertex* v) { glDrawArrays(0, triangles*3); }
Definition at line 111 of file CIsosurface.h.
Public Member Functions | |
| void | setSize (int sx, int sy, int sz) |
| void | calculate (CIsosurfaceMetaball *ball, int balls) |
| void | calculateNormals () |
| void | output (void(*triangle)(CIsosurfaceVertex *v)) |
| void | output (int triangles, CIsosurfaceVertex *v, void(*triangle)(int num, CIsosurfaceVertex *v)) |
| void | output (CMesh &mesh) |
Public Attributes | |
| CIsosurfaceValue *** | v |
| Energy values. | |
| CIsosurfaceCube *** | cube |
| Cube for marching cubes algo. | |
| int | sx |
| int | sy |
| int | sz |
| Size of the grid. | |
| float | treshold |
| Isosurface border. If energy(x, y, z) >= treshold, (x, y, z) is solid. |
|
|
Sets the size of the grid. Passing (0, 0, 0) will free memory.
|
|
|
Calculates energy values for a given number of mataballs. Note that you don't have to use this function to generate energy values. You can use all kinds of custom functions to do this.
|
|
|
Call this just before output() to have valid normal values if you need them. |
|
|
Spawns triangles. The callback function will be called for every triangle with three metavert_t structures.
|
|
|
Spawns multiple triangles at once. Triangles is the maximum number of triangles to spawn at once. v must be an array of triangles*3 metavert_t structures. The callback function will be called with the number of triangles to render and a pointer to v. Triangles are stored 123.123.123.
|
|
|
Spawn triangles to a mesh. This method isn't recommended for real-time use.
|


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StuGo 2020 Election
Here you will find information about the 2020 StuGo election.
Election Rules
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Registration Form
Link to Registration Form


Karen K Dike
Democrat
Retired
Clarkson School of Nursing, Registered Nurse; Regis University Bachelors of Science in Nursing, Regis University Masters of Science in Nursing
80503
I am a long time environmental advocate. Now that I am retired I have time to become personally engaged by working on issues important to me. I bring my skills that include close to 40 years in management to this work. I am able to bring strategic decision making, collaboration, planning and financial ability to the organizations I work with. Building support for sustainability throughout our community is vital to the work that Sustainable Resilient Longmont (SRL) undertakes. SRL engages residents across the community, including youth and people of color in events such as earth day. SRL Earth day is a focus on children and how they interact with the earth. In 2020, the event moved on line with youth from local high schools discussing what climate change means in their lives. Another important aspect in community/ grassroots activism is working with city government. I know all of the city council members personally. I frequently speak at council meetings to advocate for environmental issues. This relationship was a key element in achieving a Longmont Resolution to commit to 100% renewable energy by 2030.
Being involved in our democracy is important to me. My involvement includes donations to candidates at all levels of our government, working with organizations to promote candidates, and personal engagement such as door to door campaigning. Locally I work with a grassroots group that delivers candidate information to residents in Longmont. Through my local Sierra Club group in Boulder County, I work on candidate endorsements based on environmental priorities. Also, I am on the board of Sustainable Resilient Longmont. This organization holds candidate forums where candidates are asked questions about sustainability. This election season, I determined that I needed to engage in the Presidential Election. I wrote letters, texted and made phone calls to battleground states through Sierra Club Independent Action. Donations: Federal: Clinton, Inslee, Buttigeig, Warren, Biden, Romanoff State: Singer, Foote, Jones, Bernett, County: Jones, Singer City: Martin, Peck, Rodriguez, Waters Colorado Democratic Party, Boulder County Dems, Longmont Area Dems
Climate Reality, trained climate leader Sierra Club Indian Peaks Group Executive Committee, Colorado Chapter of the Sierra Club,Executive committee, currently Chair of Executive Committee Sustainable Resilient Longmont, Board Member Our Health, Our Future Our Longmont, Board Member North Colorado Partners for Clean Energy, Coalition member City of Longmont Climate Action Task Force, member Longmont Newcomers Coloradans Resisting Extreme Energy Development
I have a growing awareness of the divisines in our politics. There are many who don’t feel heard when they raise concerns. Where I live, in Longmont, I know that the chances of electing a person to the Federal House of Representatives who reflects my community are almost nil. It is crucial that our political landscape become more about representing people and the local/ regional aspects of the communities where we live. My hope is that by serving on the committee, I can advocate for a fair map where everyone can know that their voice will be heard when voting. A map that realizes the dream of equal representation, without favoring parties or special interests, while also acknowledges areas of our communities have special circumstances, such as race and economic status that must be reflected in the maps. I continue to hope for a return to civility in politics where we listen to and learn from each other.
As I look at the current political landscape, I see so much division. I grew up in rural Nebraska. I know and love many folks who are conservative. I am not afraid to reach out to those who do not share my political views. In my work in Nursing Administration, being able to build relationships with people in other divisions was paramount to the success in my area of responsibility. Also, working on projects that involved caregivers on several shifts, in several units on two campuses, required skills in building consensus. To bring in physician acceptance required negotiating skills. I use these skills of negotiating, relationship and consensus building, plus willingness to work with people of diverse backgrounds to my activism work. I also bring the nursing art and skill of empathy. Stepping back to see the people behind decisions and how they are affected is needed in any work. My work with SRL provides an example of how I can apply these skills. Acceptance of the possibility of renewable energy is difficult for many people. Acknowledging that jobs in the fossil fuel industry will be lost, then discussing the potential of jobs in renewable energy requires listening first instead of arguing. This usually leads to a good conversation while planting seeds that may change minds.
My success in Nursing Administration was based on my ability to analyze issues and apply data to arrive at a solution. I will relate a quality improvement project in my last position. There were three ICU’s. A QI project to reduce ventilator associated pneumonia was very successful in 2 of the 3. The third, the Neuro Trauma ICU, was difficult, but knowing that there had to be a reason, a team explored the differences. We discovered that patients who had head trauma were being transported daily for head CT scans. The transport was putting them at risk and we were able to define some simple steps to prevent this complication. I apply the same type of skills to my activist work. When planning educational events about topics, such as renewable energy, exploring data and research studies informs how we plan events. Reading through online records of meetings and attending board meetings at Platte River Power Authority gives me the ability to discuss electricity generation with our city council and to speak with other community members.
female


Magister Dieter:
As I said, you must go to
Devil's Isle
, slay
Sairon, Sairon's doll and Sairon's puppet
and bring back
Sairon's Silver Hair
. You will be amply rewarded.
"I want to quit."
"I will continue working for you."


Projects
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The viewBox attribute is required if you wish to resize icons with background-size. Note that the xmlns attribute is required.
The viewBox attribute is required if you wish to resize icons with background-size. Note that the xmlns attribute is required.


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Copyright 2021 STMicroelectronics
The STM32CubeMP1 Firmware package comes with a rich set of examples running on STMicroelectronics boards, organized by board and provided with preconfigured projects for the main supported toolchains.
The examples are classified depending on the STM32Cube level they apply to, and are named as follows:
The examples are located under STM32Cube_FW_STM32CubeMP1_VX.Y.Z\Projects\, and all of them have the same structure:
To run the example, you have to do the following:
The provided examples can be tailored to run on any compatible hardware; user simply need to update the BSP drivers for his board, if it has the same hardware functions (LED, push buttons...etc.). The BSP is based on a modular architecture that allows it to be ported easily to any hardware by just implementing the low level routines.
The table below contains the list of examples provided within STM32CubeMP1 Firmware package.
The execution of the examples could be done in 2 different mode :
STM32MP157C-EV1 projects :
| Level | Module Name | Project Name | Description | STM32MP157C-EV1 | STM32MP157C-DK2 | Mode | Core |
|
Templates |
- |
Starter project |
This projects provides a reference template that can be used to build any firmware application. | x (**) | x | Engineering | Cortex-M4 |
| Total number of templates: 2 | 1 | 1 | |||||
|
Examples |
ADC |
ADC_SingleConversion_TriggerTimer_DMA |
Use ADC to convert a single channel at each trig from timer, conversion data are transferred by DMA into an array, indefinitely (circular mode). | x | x | Production & Engineering |
Cortex-M4 |
| ADC_AnalogWatchdog | How to use the ADC peripheral to perform conversions with an analog watchdog and out-of-window interrupts enabled. | x | - | Production & Engineering | Cortex-M4 | ||
| ADC_OverSampler | How to configure and use the ADC to convert an external analog input combined with oversampling feature to increase resolution through the HAL API. | x | - | Production & Engineering | Cortex-M4 | ||
| ADC_MultiChannelSingleConversion | How to use an ADC peripheral to convert several channels. ADC conversions are performed successively in a scan sequence. | x | - | Production & Engineering | Cortex-M4 | ||
|
CRC |
CRC_UserDefinedPolynomial |
How to configure the CRC using the HAL API. The CRC (cyclic redundancy check) calculation unit computes the 8-bit CRC code for a given buffer of 32-bit data words, based on a user-defined generating polynomial. | x | x | Production & Engineering |
Cortex-M4 | |
|
CRYP |
CRYP_AES_DMA |
This example provides a short description of how to use the CRYPTO peripheral to encrypt and decrypt data using AES-128 Algorithm with ECB chaining mode. | x | x | Production & Engineering |
Cortex-M4 | |
|
Cortex |
CORTEXM_MPU |
Presentation of the MPU feature. This example configures a memory area as privileged read-only, and attempts to perform read and write operations in different modes. | x | x | Production & Engineering |
Cortex-M4 | |
|
DAC |
DAC_SimpleConversion |
How to use the DAC peripheral to do a simple conversion. | x | - | Production & Engineering |
Cortex-M4 | |
|
DMA |
DMA_FIFOMode |
This example provides a description of how to use a DMA to transfer a word data buffer from Flash memory to embedded SRAM with FIFO mode enabled through the HAL API. | x | x | Production & Engineering |
Cortex-M4 | |
|
FDCAN |
FDCAN_Loopback |
How to configure the FDCAN to operate in loopback mode. | x | x | Engineering Only | Cortex-M4 | |
|
GPIO |
GPIO_EXTI |
How to configure external interrupt lines. | x | x | Production & Engineering |
Cortex-M4 | |
|
HASH |
HASH_SHA224SHA256_DMA |
This example provides a short description of how to use the HASH peripheral to hash data using SHA224 and SHA256 Algorithms. | x | x | Production & Engineering |
Cortex-M4 | |
|
I2C |
I2C_TwoBoards_ComDMA |
How to handle I2C data buffer transmission/reception between two boards, via DMA. | x | - | Production & Engineering |
Cortex-M4 | |
|
I2C_TwoBoards_ComIT |
How to handle I2C data buffer transmission/reception between two boards, using an interrupt. | x | x | Production & Engineering |
Cortex-M4 | ||
|
LPTIM |
LPTIM_PulseCounter |
This example describes how to configure and use LPTIM to count pulses through the LPTIM HAL API. | x | x | Production (only for
DK2) & Engineering (EV1 and DK2) |
Cortex-M4 | |
| LPTIM_PWM_LSE | This example describes how to configure and use LPTIM to generate a PWM in low power mode using the LSE as a counter clock, through the HAL LPTIM API. | x | - | Production & Engineering | Cortex-M4 | ||
| PWR | PWR_STOP_CoPro | How to enter the CSTOP and STOP modes using CM4 core (aka Co-processor) and wake up from this mode by using external wakeup interrupt. |
x | x | Production Only | Cortex-M4 | |
|
QSPI |
QSPI_ReadWrite_IT |
This example describes how to erase part of the QSPI memory, write data in IT mode, read data in IT mode and compare the result in a forever loop. | x | - | Production & Engineering |
Cortex-M4 | |
|
SPI |
SPI_FullDuplex_ComDMA_Master |
Data buffer transmission/reception between two boards via SPI in Polling. | x | x | Production & Engineering |
Cortex-M4 | |
|
SPI_FullDuplex_ComDMA_Slave |
Data buffer transmission/reception between two boards via SPI using DMA. | x | x | Production & Engineering |
Cortex-M4 | ||
|
SPI_FullDuplex_ComIT_Master |
Data buffer transmission/reception between two boards via SPI using Interrupt mode. | - | x | Production & Engineering |
Cortex-M4 | ||
|
SPI_FullDuplex_ComIT_Slave |
Data buffer transmission/reception between two boards via SPI using Interrupt mode. | - | x | Production & Engineering |
Cortex-M4 | ||
|
TIM |
TIM_DMABurst |
This example shows how to update the TIMER TIM2_CH4 period and the duty cycle using the TIMER DMA burst feature. | x | x | Production & Engineering |
Cortex-M4 | |
| TIM_OnePulse | This example shows how to use the TIMER peripheral to generate a single pulse when a rising edge of an external signal is received on the TIMER Input pin. | x | - | Production & Engineering | Cortex-M4 | ||
| TIM_PWMOutput | This example shows how to configure the TIM peripheral in PWM (Pulse Width Modulation) mode. | x | - | Production & Engineering | Cortex-M4 | ||
| TIM_Synchronization | This example shows how to synchronize TIM2 and Timers (TIM8 and TIM1) in parallel mode. | x | - | Production & Engineering | Cortex-M4 | ||
| TIM_TimeBase | This example shows how to configure the TIM peripheral to generate a time base of one second with the corresponding Interrupt request. | x | - | Production & Engineering | Cortex-M4 | ||
|
UART |
UART_TwoBoards_ComDMA |
UART transmission (transmit/receive) in DMA mode between two boards. | - | x | Production & Engineering |
Cortex-M4 | |
|
UART_TwoBoards_ComIT |
UART transmission (transmit/receive) in Interrupt mode between two boards. | x | x | Production & Engineering |
Cortex-M4 | ||
| UART_Receive_Transmit_Console | UART transmission (printf/getchar) via console with user interaction. | x | x | Production & Engineering | Cortex-M4 | ||
|
WWDG |
WWDG_Example |
Configuration of the HAL API to periodically update the WWDG counter and simulate a software fault that generates an MCU WWDG reset when a predefined time period has elapsed. | x | x | Production & Engineering |
Cortex-M4 | |
| Total number of examples: 48 | 28 | 20 | |||||
|
Applications |
CoproSync |
CoproSync_ShutDown |
Send of shutdown information to Cortex-M4 so that it is able to take necessary actions before going to reset state. | x | x | Production |
Cortex-M4 |
|
FreeRTOS |
FreeRTOS_ThreadCreation |
How to use the DAC peripheral and its reference regulator to do a simple conversion. | x (**) | x | Production & Engineering |
Cortex-M4 | |
| OpenAMP |
OpenAMP_Dynamic_ResMgr |
How to use OpenAMP MW + Virtual UART to create an Inter-Processor Communication channel seen as TTY device in Linux OS. | x | - | Production |
Cortex-M4 | |
|
OpenAMP_TTY_echo |
How to use OpenAMP MW + Virtual UART to create an Inter-Processor Communication channel seen as TTY device in Linux OS. | x | x | Production | Cortex-M4 | ||
|
OpenAMP_TTY_echo_wakeup |
How to enter different PWR system operating mode (Run, Stop and Standby). | x | x (*) | Production |
Cortex-M4 | ||
OpenAMP_raw | How to use OpenAMP MW to create an Inter-Processor Communication channel. | x (**) | x | Production | Cortex-M4 | ||
| OpenAMP_for_signed_fw | How to use OpenAMP MW + Virtual UART to create an Inter-Processor Communication channel seen as TTY device in Linux OS for protected firmware loaded by OP-TEE secure application. | x | x | Production | Cortex-M4 | ||
|
OpenAMP_FreeRTOS_echo |
How to use OpenAMP MW with FreeRTOS. | x | x (*) | Production |
Cortex-M4 | ||
| Total number of applications: 15 | 8 | 7 | |||||
|
Demonstrations |
- |
AI_Character_Recognition |
This project demonstrate a complex application that is running on both CPU1(CA7) and CPU2(CM4). | x | x (*) | Production |
Cortex-M4 |
| Total number of demonstrations: 2 | 1 | 1 | |||||
| Total number of projects: 67 | 38 | 29 |


Colorful T-Mobile CEO leaving, even as Sprint deal not done
by The Associated PressT-Mobile said Monday its colorful CEO John Legere is stepping down next year, even as the wireless company's long-running effort to merge with rival Sprint remains unfinished.
Its current president and chief operating officer, Mike Sievert, will become CEO in May after Legere's contract ends.
T-Mobile is trying to combine with Sprint in a $26.5 billion deal. Federal regulators have approved the deal, but attorneys general of 15 states and the District of Columbia aim to block it, saying it will raise prices for consumers. A trial is to start in December.
Legere will remain with the Bellevue, Washington-company as a board member. Sievert has worked at T-Mobile since 2012 and has been a board member for nearly two years.
The company said Monday that the move is part of its succession plan.
Legere joined T-Mobile as its CEO in 2012 and, unlike most telecom executives, has an active social-media presence where he regularly disparages his wireless rivals and promotes T-Mobile as a consumer-friendly wireless company.
"I'm not going anywhere soon. This is all part of a multiyear plan," he wrote on Twitter, where he has 6.5 million followers.
On a call with investors, Legere pushed back against reports that he had been in discussions to be CEO of the troubled office-space company WeWork.
"I was never having discussions to run WeWork," he said Monday.


Interiors hub work with designers who specializes in incorporating
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often outshine the industry standards.
The designers come up with unique ideas for interior spaces of the
clients and use various disciplines and elements of
interior design by focusing on practical application and
implications of their concepts.
Our designers are committed to design that creates clean lines and purity of space. Our services cover the entire construction process from start to finish; covering spatial planning, electrical and lighting layouts; ceiling and bulkhead designs for tender and construction purposes. This phase of the project also includes the specification or all finishes and fittings for the interior.
Our designer ensure they work closely with our clients they effortlessly create high-end interiors exclusive to their own particular style and needs. Sourcing furniture and fabrics both locally and Internationally ensures that there are no limits to the what can be achieved. Our designers natural ability to design bespoke furniture items allows us to create finished interiors that are unique, sophisticated and timeless, exceeding all expectations.
Incase of any Complaints or you would like to drop any feedback
Fill
the form below and we will be grand for your reply.


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Triangle Tracker
This is a simple application that will help you determine if a triangle is isosceles, equilateral, scalene or not a triangle by entering its sides. Enter the length of the sides below:
This is a simple application that will help you determine if a triangle is isosceles, equilateral, scalene or not a triangle by entering its sides. Enter the length of the sides below:


Donald Tramp
Résumé
― I'm the most successful person ever to run for the presidency, by far. Nobody's ever been more successful than me. I'm the most successful person ever to run. Ross Perot isn't successful like me. Romney ― I have a Gucci store that's worth more than Romney. Sorry losers and haters, but my IQ is one of the highest ― and you all know it!
Experience
Recent
-
2017
Became 45th president of the United States
-
2016
Won election race with 77 votes more than Clinton yippe-kee-yay!
-
2015
Became the most important Republican nominating for presidential election run
-
2009
Changed my mind and became Republican again
-
2005
Started Trump University with Michael Sexton and Jonathan Spitalny: no grades, certificates and other bureaucracy, but program offered courses in real estate, asset management entrepreneurship, and wealth creation. 98% students gave positive reviews while studying, however some of these ungrateful gringos filed lawsuits against Trump University after the course. I had to pay $25 million to settle that...
-
2002
Acquired the former Hotel Delmonico, which was renovated and reopened in 2004 as the Trump Park Avenue. I sure do like my surname!
-
2001
Completed Trump World Tower and joined the Democratic Party
-
1999
Started buying golf courses. They are very cheap, I have 18 of them now in USA and abroad! Also switched to the Reform Party that year
-
1997
Began a multi-building development along the Hudson River, which was named Trump Place. Me and the other investors sold our shares for $1.8 billion and that was then the biggest residential sale in the history of New York City
-
1996
Acquired the Bank of Manhattan Trust Building, which was a vacant seventy-one story skyscraper on Wall Street. After an extensive renovation, the high-rise was renamed the Trump Building
-
1994
Refurbished the Gulf and Western Building on Columbus Circle, turned it into a 44-story luxury property known as Trump International Hotel and Tower
-
1989 ― 1992
Ran a second hand airline called Trump Shuttle. What a waste of money, I had to sell it, now it is American Airlines Shuttle, btw
-
1989, 1990
Learned about Tour de France and decided to hold my very own Tour de Trump. Is America not great enough for that cycling competition?
-
1988
Acquired the Plaza Hotel in Manhattan for $407 million, invested $50 million to restore the building and boosted it from three-star to four-star hotel (I called it "the Mona Lisa" and sold it for a lot of cash in 1995)
-
1987
Registered as a Republican
-
1985
I bought the Mar-a-Lago estate in Palm Beach and turned it into a private club.You can join if you pay $200K initiation fee (and there is another annual fee for members, it is very expensive to be rich). That year I also opened a casino called Trump Castle. My wife Ivana became a manager, because she is another Trump!
-
1983
I purchased New Jersey Generals, an American football team. I changed team's play schedule and filed an antitrust lawsuit against United States Football League, so NJG are not doing so good now, but back then they were great!
-
1980
Started developing the Trump Tower skyscraper in Manhattan, I payed a crew of undocumented Polish workers to demolish the historic Bonwit Teller store, including art deco features. All this to make architectural critic Paul Goldberger say in 1983 that the tower's atrium is "the most pleasant interior public space to be completed in New York in some years". At the same time I also started a repair job on the Wollman Rink in Central Park and completed the work in three months for $1.95 million, which was $775,000 less than the initial budget!
-
1978
Purchased a 50 percent stake in the derelict Commodore Hotel and turned it into the Grand Hyatt Hotel in 2 years of remodeling
-
1971
Was promoted to president of the company and renamed it The Trump Organization
-
1968
Began my career at my father's real estate development company, Elizabeth Trump & Son
Personal life
-
2006
Melania gained United States citizenship and gave birth to our son, Barron
-
2005
Married her
-
1998
Met my future third wife, Melania Knauss
-
1999
Divorced Marla ¯\_(ツ)_/¯
-
1993
Married Marla and had a daughter, we named her Tiffany, because I like Tiffany & Company jewellery as well
-
1992
Started affair with Marla Maples, so I had to divorce. God knows I love nice women, I love them all!
-
1984
Birth of Eric Trump
-
1982
Birth of Ivanka Trump
-
1977
My first son is born. I called him Donald, of course!
-
1977
Married Czech model Ivana Zelníčková
Languages
Skills
Character
Likes😃
Dislikes😞
Wants
Education
-
2011
Asked friends who are prominent and wealthy alumni of the New York Military Academy to secure my academic records so they could not be seen by anyone, never!
-
1966
Transferred to the Wharton School of the University of Pennsylvania and graduated in May 1968 with a B.S. in economics
-
1964
Started studying in Fordham University
-
1959
Enrolled in the New York Military Academy, a private boarding school, after my parents discovered I made frequent trips into Manhattan without their permission
Media career
-
2019
Was awarded Worst Actor and Worst Screen Combo at Golden Raspberry Awards for parts in "Death of a Nation" and "Fahrenheit 11/9"
-
2015
Published a book "Crippled America: How to Make America Great Again"
-
2011
-
- Published a book "Time to Get Tough: Making America #1 Again" in coauthorship with Wynton Hall, Peter Schweizer and Meredith McIver
- Published a book "Midas Touch: Why Some Entrepreneurs Get Rich – And Why Most Don't" in coauthorship with Robert Kiyosaki
- Published a book "Trump Tower" in coauthorship with Jeffrey Robinson
-
-
2009
Published a book "Think Like a Champion: An Informal Education in Business and Life" in coauthorship with Meredith McIver
-
2008
Published a book "Never Give Up: How I Turned My Biggest Challenges into Success" in coauthorship with Meredith McIver
-
2007
Published a book "Think Big and Kick Ass" in coauthorship with Bill Zanker
-
2007
Received a star on the Hollywood Walk of Fame for being producer of Miss Universe pageant
-
2006
-
- Published a book "Why We Want You to Be Rich" in coauthorship with Meredith McIver and Robert Kiyosaki
- Published a book "How to Build a Fortune: Your Plan for Success From the World's Most Famous Businessman" coauthorship with Robert Kiyosaki
- >Published a book "The Best Real Estate Advice I Ever Received: 100 Top Experts Share Their Strategies"
- Published a book "Trump 101: The Way to Success" in coauthorship with Meredith McIver
-
-
2005
Published a book "The Best Golf Advice I Ever Received"
-
2005
Performed a song with Megan Mullally at the 57th Primetime Emmy Awards
-
2004 ― 2008
Ran short-form talk radio program "Trumped!" (one to two minutes on weekdays)
-
2004
-
- Published a book "Trump: How to Get Rich" in coauthorship with Meredith McIver
- Published a book "The Way to the Top: The Best Business Advice I Ever Received"
- Published a book "Think Like a Billionaire: Everything You Need to Know About Success, Real Estate, and Life" in coauthorship with Meredith McIver
-
-
2003 ― 2015
Produced NBC reality shows "The Apprentice" and "The Celebrity Apprentice"
-
2000
Published a book "Trump: The America We Deserve" in coauthorship with Dave Shiflett
-
1997
Published a book "Trump: The Art of the Comeback" in coauthorship with Kate Bohner
-
1991
Was awarded Worst Supporting Actor at Golden Raspberry Awards for a part in "Ghosts Can't Do It"
-
1990
Published a book "Trump: Surviving at the Top" in coauthorship with Charles Leerhsen
-
1987
Published a book "Trump: The Art of the Deal" in coauthorship with Tony Shwartz


%inherit file="base.html"/> <%def name="title()"> Welcome to Extrasolar! %def> <%def name="head()"> %def> <%include file="signup_form_dialogs.html"/>
|
The eXoplanetary Research Institute (XRI) is crowdsourcing exploration of the planet Epsilon Prime using the power of the Internet. Sign up now to help unlock the secrets of this alien world, one photo at a time.
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Ramadan Essay Contest
Introduction: This is an individual essay contest that you will submit within a specified date. You will be judged based on your depth of content, authenticity, research, a clear and coherent understanding of the material, writing style, and answering the questions. There will be three prize winners, a 1st place prize, a 2nd place prize, and a 3rd place prize. There will be two different divisions, but the topics are the same. One division is for college contestants, and the other is for high school.
Topic: Pick one single verse in the Quran that you really felt attached to and write about it (please only pick one verse). Explain the meaning of the verse, why you chose it, why you felt that this specific verse was important, and how it applies to your daily life and the life of the society at large.
Sources: The Quran and Sunnah are two obvious sources. Other sources you may use include journal articles, news articles, books or lectures/videos. Please cite your sources as plagiarism is unacceptable.
1st Place Prize: $200
2nd Place Prize: $100
3rd Place Prize: $70
Minimum requirements: College essays: minimum 1,000 words. High school essays: minimum 750 words. Essays that are well written and have depth will be considered regardless if they meet the minimum word count.
Submission dates: Essay submissions begin on May 16th and end on June 6th of 2018. In order to be considered as a potential prize winner: please make sure your first and last name is on your essay. Also on your essay, please write your age, your school name (high school or college), and how we may contact you (either email or phone so we may contact you with comments and to inform you whether you won).
If you have any questions or want to submit your essay, please email<EMAIL_ADDRESS>The winners for both high school and college categories will be announced on Eid. We look forward to reading your essays and hope that you enjoy writing it.
JazakumAllahu kheiran


hola mamá empecé programando html.
This is the first paragraph of text. This is the first paragraph of text. This is the first paragraph of text. This is the first paragraph of text.


{% import "bootstrap/wtf.html" as wtf %}
{% import "_macros.html" as macros %}
{% extends "layout.html" %}
{% block title %}Enter The Data{% endblock %}
{% block inner %}
Welcome to Enter The Data.
(Enter as in step into and explore)
I am a computer scientist, a data scientist and a finance quant.
I like to solve practical problems and create useful applications.
I love doing analytics, machine learning, algorithms and data science,
so I am thrilled that these disciplines have all become very popular and that just about
every industry is using their methods to solve problems.
It means more fun and rewarding opportunities for me.
I would also like to think it also means something positive for us all in general.


SWI-Prolog
using
WASM
running in your browser
Pre-alpha version. See
Wiki on Discourse
for status and usage
Next
Stop
?-
Abort
🗑
+
Create
(Re)consult


-1
Click the number above to modify the model.
Debug to see how the view has been changed.
By dynamic DataBinding:
By satic DataBinding:


查询结果
共
520
篇
Matt Giampietro
Friends
Matthew is an interior designer living in New York.
Joined in 2013
上一页
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Lobby
Players:
{% for player in all_players %}
{% if created == True %}
{% else %}
{{ player.name }}
{% endfor %}
Once all players have joined, {{ creator }} will start the game!
{% endif %}


WITNESS LIST General Investigating Committee June 30, 2000-10:00A Interim Charges On: Borowski, Brian (Collaborative Group) McLeroy, Don (Self) Rodriguez, Robert (Self and Southwestern Capital Markets, Inc.) Stein, Russell (Self and First Union) Washington, Christian (Self) Registering, but not testifying: On: Arnold, Stephen (Self) Ballard, Paul (Texas Education Agency) Ferris, Roger (State Auditor's Office) Smith, Carol (State Auditor's Office)


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Conserved Domain Database is a protein annotation resource that consists of a collection of well-annotated multiple sequence alignment models for ancient domains and full-length proteins.
get_cdd(data, ...) # S3 method for character get_cdd( data, output = c("short", "standard", "full"), splitter = 100L, progress = FALSE, evalue = NULL, bitscore = NULL, ... ) # S3 method for data.frame get_cdd(data, sequence, id, ...) # S3 method for list get_cdd(data, ...) # S3 method for default get_cdd(data = NULL, sequence, id, ...) # S3 method for AAStringSet get_cdd(data, ...)
| data | A data frame with protein amino acid sequences as strings in one column and corresponding id's in another. Alternatively a path to a .fasta file with protein sequences. Alternatively a list with elements of class |
|---|---|
| ... | currently no additional arguments are accepted apart the ones documented bellow. |
| output | One of "short", "standard" or "full". Default is "short". "Short" returns the highest scoring hit, for each region of the query sequence; "standard" returns the best-scoring hit from each source database, for each region of the query sequence; "full" returns the complete set of hits. |
| splitter | An integer indicating the number of sequences to be in each .fasta file that is to be sent to the server. Default is 100. Change only in case of a server side error. Accepted values are in range of 1 to 4000. |
| progress | Boolean, whether to show the progress bar, at default set to FALSE. |
| evalue | Numeric, all sequences with E-value lower or equal to this value will be retained in the function output. Used to filter out low similarity matches. If set some queried sequences might be discarded from the output. Suggested values: 1e-2 - 1e-5. |
| bitscore | Numeric, all sequences with bitscore greater or equal to this value will be retained in the function output. Used to filter out low similarity. If set some queried sequences might be discarded from the output. Suggested values: 10 - 20. |
| sequence | A vector of strings representing protein amino acid sequences, or the appropriate column name if a data.frame is supplied to data argument. If .fasta file path, or list with elements of class "SeqFastaAA" provided to data, this should be left blank. |
| id | A vector of strings representing protein identifiers, or the appropriate column name if a data.frame is supplied to data argument. If .fasta file path, or list with elements of class "SeqFastaAA" provided to data, this should be left blank. |
https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi
A data frame with columns:
Character, as from input
Character, CD-Search results can include hit types that represent various confidence levels (specific hits, non-specific hits) and domain model scope (superfamilies, multi-domains).
Character, unique identifier for a domain models position-specific scoring matrix (PSSM).
Integer, start of the alignement in the query protein sequence.
Integer, end of the alignement in the query protein sequence.
Numeric, the expect value, or E-value, indicates the statistical significance of the hit as the likelihood the hit was found by chance.
Numeric, this values is derived from the raw alignment score in which the statistical properties of the scoring system used have been taken into account.
Character, the accession number of the hit, which can either be a domain model or a superfamily cluster.
Character, the short name of a conserved domain, which concisely defines the domain.
Character, if the hit to a conserved domain is partial (i.e., if the alignment found by RPS-BLAST omitted more than 20 percent of the CDs extent at either the n- or c-terminus or both), this column will be populated with one of the following values: N - incomplete at the N-terminus, C - incomplete at the C-terminus, NC - incomplete at both the N-terminus and C-terminus. If the hit to a conserved domain is complete, then this column will be populated with a dash (-).
Character, the short name of a conserved domain, which concisely defines the domain.
Character, this column is populated only for domain models that are specific or non-specific hits, and it lists the accession number of the superfamily to which the domain model belongs.
This function creates temporary files in the working directory.
Lu S, Wang J, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR, Gwadz M, Hurwitz DI, Marchler GH, Song JS, Thanki N, Yamashita RA, Yang M, Zhang D, Zheng C, Lanczycki CJ, Marchler-Bauer A (2020) CDD/SPARCLE: the conserved domain database in 2020, Nucleic Acids Res. 48(D1):D265-D268. doi: https://doi.org/10.1093/nar/gkz991
#> id hit.type pssm.id align_start align_end evalue bitscore #> 1 ATCG00660.1 specific 214352 1 117 6.15755e-60 179.2450 #> 2 AT2G43600.1 specific 381595 84 273 6.42133e-57 181.8590 #> 3 AT2G43600.1 specific 214593 29 57 1.27435e-06 44.2797 #> 4 AT2G22960.1 superfamily 415488 51 184 1.76577e-77 233.8450 #> 5 AT2G22960.1 superfamily 415488 18 58 2.46479e-11 61.2038 #> 6 AT2G19580.1 specific 395265 5 250 5.50271e-09 55.1239 #> 7 AT2G19690.2 specific 153095 25 139 1.46750e-48 152.2030 #> 8 AT2G19690.1 specific 153095 25 143 6.67046e-50 155.2840 #> 9 AT2G33130.1 specific 398902 45 100 9.12145e-08 44.9855 #> 10 AT2G05520.1 specific 254089 1 42 3.36629e-11 55.9193 #> 11 AT2G05520.2 specific 254089 1 42 2.80993e-11 55.9193 #> acc desc incomplete superfamily #> 1 CHL00068 rpl20 - cl00393 #> 2 cd00325 chitinase_GH19 - cl00222 #> 3 smart00270 ChtBD1 N cl16916 #> 4 cl08270 Peptidase_S10 superfamily N <NA> #> 5 cl08270 Peptidase_S10 superfamily C <NA> #> 6 pfam00335 Tetraspannin - cl28961 #> 7 cd04706 PLA2_plant - cl05417 #> 8 cd04706 PLA2_plant - cl05417 #> 9 pfam05498 RALF - cl23823 #> 10 pfam07172 GRP C cl06274 #> 11 pfam07172 GRP C cl06274


- canTeleport(Location) - Method in class PlayerWarpGUI.Handlers.WarpHandler
-
Checks if location is safe to teleport too.
- cc(String) - Method in class PlayerWarpGUI.config.Config
-
Translate color codes from config data
TODO change to StringUtils calls
- checkArgs(Player, String[], int, String) - Method in class PlayerWarpGUI.Utils.StringUtils
-
Checks if list is equale to the size of size.
- checkArgsString(Player, String[], int, String) - Method in class PlayerWarpGUI.Utils.StringUtils
-
Checks if list is less than the size of size.
- checkCreateWarpFolder() - Method in class PlayerWarpGUI.Utils.Warp.WarpFileUtils
-
Check to see if warp folder exists.
- checkPerm(Player, String, String) - Method in class PlayerWarpGUI.Utils.Perms.PermUtils
-
Check player has permission, else send a no permission message.
- checkPlayerWarpObject(UUID, String) - Method in class PlayerWarpGUI.Utils.Warp.ObjectUtils
-
return true or false if a warp object exists matching the player and warp name.
- checkTeleportQueue(Player) - Static method in class PlayerWarpGUI.Handlers.TeleportHandler
-
Check player is in Teleport queue
- checkWarpsExsits(UUID) - Method in class PlayerWarpGUI.Utils.Warp.WarpFileUtils
-
Check if a player warps file exists.
- ChestListener - Class in PlayerWarpGUI.Listeners
-
- ChestListener() - Constructor for class PlayerWarpGUI.Listeners.ChestListener
-
Constructor
- closeInv(Player) - Method in class PlayerWarpGUI.Listeners.ChestListener
-
Close the inventory for Player
- colorConvert(String) - Static method in class PlayerWarpGUI.Chat.MessageSender
-
- CommandManager - Class in PlayerWarpGUI.Commands
-
CommandManager
- CommandManager() - Constructor for class PlayerWarpGUI.Commands.CommandManager
-
- Config - Class in PlayerWarpGUI.config
-
Handles all calls to get config data.
- consoleMsgWarpCount(int, int) - Method in class PlayerWarpGUI.Utils.Warp.WarpFileUtils
-
Display console message with warp file count and total number of warps.
- copy(InputStream, File) - Method in class PlayerWarpGUI.Utils.StringUtils
-
Copy a file from resource to a file.
- createAllWarpsFromFile() - Method in class PlayerWarpGUI.Utils.Warp.WarpFileUtils
-
Loop through all warp file and through all warps in
each file and create warp object from that data.
- createGraph(String) - Method in class PlayerWarpGUI.Others.Metrics
-
Construct and create a Graph that can be used to separate specific plotters to their own graphs on the metrics
website.
- createPlayerWarpFile(UUID) - Method in class PlayerWarpGUI.Utils.Warp.WarpFileUtils
-
Create a new empty players warp file.
- createWarpFromFile(File, UUID) - Method in class PlayerWarpGUI.Utils.Warp.WarpFileUtils
-
public access to create warp from file.
- createWarpObjects(UUID, String, String, String, String, ArrayList<String>, ArrayList<String>) - Method in class PlayerWarpGUI.Utils.Warp.ObjectUtils
-
Call PlayerWarpObject constructor to create a new
warp object.


Rock Hawk: Live Map
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--- title: "Confidence intervals on predictions from mixed-effects models" author: "Remko Duursma" date: 2017-06-01 categories: ["R"] tags: ["statistics", "lme4"] description: "A light-weight implementation of confidence intervals for fitted linear-mixed effects models, by applying the semi-parametric bootstrap provided by bootMer." ---
With simple linear regression, standard errors and confidence intervals for fitted (and predicted) values are easily computed. In R, we can use the se.fit
argument in predict.lm
, which returns the standard error for the fitted values, and interval = "confidence"
to return confidence intervals. With linear mixed-effects models, however, it is not so easy. Neither predict.lme
(from nlme
) nor predict.merMod
(from lme4
) provide these methods, as confidence intervals on mixed-effects model predictions are harder to produce.
The solution is to use the parametric bootstrap, which is conveniently implemented in bootMer
to be applied to models fit with the lme4
package (lmer
, not glmer
). Here I describe a simple wrapper around bootMer
, providing an alternative for predict.merMod
that calculates standard errors (and confidence intervals) for predictions.
A side-effect of this implementation is that confidence intervals now appear in visreg
plots of mixed-effects models.
The code shown below is implemented as a very simple package, bootpredictlme4
, which can be installed with,
devtools::install_github("remkoduursma/bootpredictlme4")
Note that the package cannot be used in conjunction with the lmerTest
package, since both packages replace the predict.merMod
function from lme4
. For this reason I will probably not attempt to submit this package to CRAN.
Suppose we fit a linear mixed-effects model, using the built-in sleepstudy
dataset (in the lme4
package), which fits the reaction time of subjects as a function of the number of days since a sleep deprivation (3 hours per night) experiment.
library(lme4)
fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
The structure allows for a random intercept and slope of reaction vs. days by subject. A visreg
plot (Fig. 1) shows the fitted model (for the average subject). Note that I have not yet loaded the bootpredictlme4
package.
library(visreg)
visreg(fm1, "Days", ylab="Reaction time (ms)")
If we are interested in the fitted value at some specified time, let’s say 5 days, we can use predict
, setting re.form=NA
to yield predictions for the average subject (i.e. not include random effects in the predictions). Note that we actually invoke predict.merMod
, because fm1
is fitted with lmer
.
predict(fm1, newdata = data.frame(Days=5), re.form=NA)
## 1
## 303.7415
Now we would like to calculate a confidence interval on this prediction, using the bootstrap. We can generate 100 bootstrap resamples with the bootMer
function, as follows. In this case, we apply the predict.merMod
to each of the bootstrapped fits. I am just using 100 fits to speed up this code, but you probably want to use 1000 samples or more.
b <- bootMer(fm1, nsim=100,
FUN=function(x)predict(x, newdata=data.frame(Days=5), re.form=NA))
The resulting object b
contains lots of information, but most useful is the element b$t
, which lists the output of the function we applied to each of the bootstrap resamples, in this case the fitted value at Days=5
.
The following histogram shows the distribution of the fitted values, that is, the sampling distribution. Note that if you use more samples (which you should), the distribution will look more like a normal distribution.
hist(b$t, breaks=seq(250,350,by=5),
ylim=c(0,25),
main="", xlab="Reaction time at 5 Days (ms)",
col="cornflowerblue")
box()
The standard error of our predicted value can be estimated simply as the standard deviation of the sampling distribution, that is,
sd(b$t)
## [1] 9.184015
and the confidence interval as the quantiles of the distribution (in this case, a 95% confidence interval).
quantile(b$t, probs=c(0.025, 0.975))
## 2.5% 97.5%
## 286.5467 321.5505
The example above is implemented in the bootpredictlme4
package (as mentioned, install with devtools::install_github("remkoduursma/bootpredictlme4")
). When loading the package, the predict.merMod
function is replaced with a function that takes an se.fit
argument.
library(bootpredictlme4)
predict(fm1, newdata=data.frame(Days=5), re.form=NA, se.fit=TRUE, nsim=100)
## $fit
## 1
## 303.7415
##
## $se.fit
## 1
## 10.50841
##
## $ci.fit
## 1
## 2.5% 283.6878
## 97.5% 323.8666
Two standard errors are computed, the se.boot
is the one described above (the standard deviation of the sampling distribution), and se.fit
is an effective standard error that reconstructs the bootstrapped confidence interval if we were to assume asymptotic normality. In the case of normality, the half-width of the confidence interval (for 95% coverage) is of course 1.96 times the standard error. Thus se.fit
is calculated as the half-width of the bootstrapped confidence interval, divided by 1.96. It is this standard error that is used by visreg
(see below), making sure that the resulting confidence interval is actually equal to the bootstrapped confidence interval.
In most cases se.fit
and se.boot
will be very similar, unless you used very few bootstrap samples, or the sampling distribution is very non-normal (which is certainly possible).
A major advantage is that visreg
automatically recognizes that we can compute standard errors, and now a confidence interval appears on the standard effects plot. Note that bootpredictlme4
warns about using few bootstrap resamples. The default has a low number to allow rapid testing.
visreg(fm1, "Days", ylab="Reaction time (ms)")
## Number of bootstrap replicates very low.
## Set to higher value with e.g. options(bootnsim = 500)
The new predict method also allows more complicated visreg
plots, like the overlay plot (my personal favorite).
# Add a fake grouping variable to sleepstudy
high <- with(sleepstudy, levels(reorder(Subject,Reaction,mean)))[1:9]
sleepstudy$Group <- factor(ifelse(sleepstudy$Subject %in% high, "A", "B"))
fm2 <- lmer(Reaction ~ Days*Group + (Days | Subject), sleepstudy)
visreg(fm2, "Days", by="Group", overlay=TRUE, ylab="Reaction time (ms)")
## Number of bootstrap replicates very low.
## Set to higher value with e.g. options(bootnsim = 500)
## Number of bootstrap replicates very low.
## Set to higher value with e.g. options(bootnsim = 500)


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