I went through them all and spent more time on the Timebox/Pomodoro Technique, as I knew less about these methods. I have had more experience with mindfulness and meditation and am aware of the effects but it was still useful to understand the relationship between this and new methods I was reading.
I thought making time orientated commitments rather than allocating an indefinite amount of time to achieve a particular goal was interesting. A lot of what I’m learning at the moment is new to me so I think measuring time rather than tasks will be more effective for me until I have more experience and a better understanding of how long activities can take me personally.
Timbeox was great. I set aside 1 hour and it literally took me 1 hour to work my way through them all without me paying a great deal of attention of my time and progress as I was working through. I think this could be a very useful skill when it comes to me managing my workload.
Timebox, starting small and the intense immersive experience I can have within these timeframes.


{% extends 'base.html' %} {% load i18n widget_tweaks placeholder static %} {% block title %}{{ title }}{% endblock %} {% block header %} {% include "registration/header.html" %} {% endblock %} {% block content %}
{% trans "Please enter your new password twice so we can verify you typed it in correctly." %}
{% else %}{% trans "The password reset link was invalid, possibly because it has already been used. Please request a new password reset." %}
{% endif %}


A: Arch 5.1.8,A+: Arch Harden 5.1.11,F: Fedora 5.1.8,U: Ubuntu 5.0.0,U+: Ubuntu LTE 4.15.0
The JIT-ed memory is a common target for an attacker to place an arbitrary gadget (e.g., syscall in userspace). One popular technique is to encode a desirable sequence of instructions as part of immediate values, as x86-like CISC architectures provide a way to encode long bytes into one instruction. Constant blinding, as also known as constant folding, is a technique to break immediate values, avoiding the use of attacker-chosen constants in the executable region. It's worth noting that there are numerous other techniques (e.g., controlling the constant offset of direct branches) but most of well-known attacks in the user space might not be too effective in the kernel space as BPF provides only a smaller region with a smaller set of instructions available. The implementation of constant blinding is straightforward; xor the chosen immediate value with a random constant and before using it, xor with the mangled value again with the random constant.
syscall
int bpf_jit_blind_insn(const struct bpf_insn *from, const struct bpf_insn *aux, struct bpf_insn *to_buff) { u32 imm_rnd = get_random_int(); switch (from->code) { case BPF_ALU | BPF_ADD | BPF_K: case BPF_ALU | BPF_SUB | BPF_K: case BPF_ALU | BPF_AND | BPF_K: case BPF_ALU | BPF_OR | BPF_K: case BPF_ALU | BPF_XOR | BPF_K: case BPF_ALU | BPF_MUL | BPF_K: case BPF_ALU | BPF_MOV | BPF_K: case BPF_ALU | BPF_DIV | BPF_K: case BPF_ALU | BPF_MOD | BPF_K: // NB. no more attack controllable instructions inserted // in the jitted, executable space (e.g., jump in the middle // of the immediate value) // // MOV _, 0xdeadbeef // => MOV AX, [imm_rnd ^ 0xdeadbeef] // XOR AX, imm_rnd // MOV _, AX *to++ = BPF_ALU32_IMM(BPF_MOV, BPF_REG_AX, imm_rnd ^ from->imm); *to++ = BPF_ALU32_IMM(BPF_XOR, BPF_REG_AX, imm_rnd); *to++ = BPF_ALU32_REG(from->code, from->dst_reg, BPF_REG_AX); break; ... } ... }
For non-privileged BPF programs, the JIT engine applies mitigation schemes against microarchitectural side-channel attacks, such as Spectre.
Variant 1 (Bounds Check Bypass). To prevent a speculator from performing an out-of-bound array access, it restricts its uses of an index on arrays that are accessible by an unprivileged user. The Linux kernel places such an check for both its BPF interpreter and JIT code.
// NB. in JIT-ed code: // array[index] -> array[index & mask] u32 array_map_gen_lookup(struct bpf_map *map, struct bpf_insn *insn_buf) { ... if (map->unpriv_array) { *insn++ = BPF_JMP_IMM(BPF_JGE, ret, map->max_entries, 4); *insn++ = BPF_ALU32_IMM(BPF_AND, ret, array->index_mask); } else { *insn++ = BPF_JMP_IMM(BPF_JGE, ret, map->max_entries, 3); } ... } // NB. in an fuction called from an eBPF program static void *percpu_array_map_lookup_elem(struct bpf_map *map, void *key) { struct bpf_array *array = container_of(map, struct bpf_array, map); u32 index = *(u32 *)key; if (unlikely(index >= array->map.max_entries)) return NULL; // NB. even after a speculator reaches here, it won't access // beyond the region of array->pptrs return this_cpu_ptr(array->pptrs[index & array->index_mask]); }
Recently, more sophisticated mitigation to thwart generic gadgets for V1 is introduced, which simulates the behavior of a speculator and detects a potential out-of-bound memory access. Please refer to [2] for in-depth explanation.
Variant 2 (Branch Target Injection). For indirect jumps introduced during the jitting, BPF applies the Retpoline mitigation, like the Linux kernel code. For example, when the BPF_JMP instruction is a tail call, it invokes the same bpf program again, which is commonly implemented with an indirect jump (jumping right after the prologue). RETPOLINE_RAX_BPF_JIT is introduced to produce a retpoline-enabled jump gadget that can replace an indirect call with rax.
BPF_JMP
RETPOLINE_RAX_BPF_JIT
rax
// do_jit() { // ... // case BPF_JMP | BPF_TAIL_CALL: // emit_bpf_tail_call(&prog); // break; // } void emit_bpf_tail_call(u8 **pprog) { ... /* * Wow we're ready to jump into next BPF program * rdi == ctx (1st arg) * rax == prog->bpf_func + prologue_size */ RETPOLINE_RAX_BPF_JIT(); .. } # define RETPOLINE_RAX_BPF_JIT() \ do { \ EMIT1_off32(0xE8, 7); /* callq do_rop */ \ /* spec_trap: */ \ EMIT2(0xF3, 0x90); /* pause */ \ EMIT3(0x0F, 0xAE, 0xE8); /* lfence */ \ EMIT2(0xEB, 0xF9); /* jmp spec_trap */ \ /* do_rop: */ \ EMIT4(0x48, 0x89, 0x04, 0x24); /* mov %rax,(%rsp) */ \ EMIT1(0xC3); /* retq */ \ } while (0)
Variant 4 (Speculative Store Bypass). To prevent a speculative memory disambiguation from performing an arbitrary kernel memory read, BPF verifier detects the malicious patterns to trigger the speculation at the time of loading a BPF program, and sanitize the patterns.
// NB: Safe execution flow by sanitizing a pattern // Detect a case of reusing stack slot, and sanitize it. // (1) r8 = *(u64 *)(r7 +0) // slow read // (2) *(u64 *)(r10 -72) = 0 // instruction for sanitizing // - this store becomes fast due to no depency on (1) // (3) *(u64 *)(r8 +0) = r3 // this store becomes slow due to r8 // ---- at this time, (2) is likely to be completed before (3), // ---- so it can perfectly eliminate an arbitrary unsafe address. // (4) r1 = *(u64 *)(r6 +0) // loads from either sanitized or safe address // (5) r2 = *(u8 *)(r1 +0) // no leak happens struct bpf_insn_aux_data { .... int sanitize_stack_off; /* stack slot to be cleared */ .... } static int check_stack_write(struct bpf_verifier_env *env, .... { .... for (i = 0; i < BPF_REG_SIZE; i++) { if (state->stack[spi].slot_type[i] == STACK_MISC && !env->allow_ptr_leaks) { int *poff = &env->insn_aux_data[insn_idx].sanitize_stack_off; int soff = (-spi - 1) * BPF_REG_SIZE; .... .... // NB: examine a store instruction writing to a stack slot. // record this offset for detecting reused stack slot. *poff = soff; } state->stack[spi].slot_type[i] = STACK_SPILL; } .... } static int convert_ctx_accesses(struct bpf_verifier_env *env) { .... // NB: Is it a reused stack slot? if (type == BPF_WRITE && env->insn_aux_data[i + delta].sanitize_stack_off) { struct bpf_insn patch[] = { .... // NB: Sanitize it with 0. BPF_ST_MEM(BPF_DW, BPF_REG_FP, env->insn_aux_data[i + delta].sanitize_stack_off, 0), .... }; } }


cola.exe
spam.exe
justpost.exe
broken.exe
nightdrive.jpg
goodtimes.exe
ok
dragging windows doesn't raise them
taskbar borders look jank
add clock to taskbar
clicking on iframes doesn't raise windows
File 1
File 2
Test
This panel is only a test.
Test 2
This panel is also a test.


List of Infectious Diseases legally notifiable under the Infectious Diseases Act
- Diseases and Conditions
- Hand, Foot and Mouth Disease
- Zika
- Influenza
- Dengue
- AIDs/HIV
- Norovirus Gastroenteritis (Gastric Flu)
- Dengue
- Norovirus Gastroenteritis
- Tuberculosis


Tutorial¶
When you start OPEN you’re presented with the shell prompt:
$ python open.py
Welcome to OPEN v0.0.3
Created by João Faria |<EMAIL_ADDRESS>Type "listcommands" for a list of the available commands
For help on a specific command, type "command -h" or see http://j-faria.github.io/OPEN
OPEN [1]:
You can follow the instructions and type listcommands to see the available commands (this only lists the tested ones, everything else is still experimental). Whenever you type command -h you will see the usage pattern and options specific to that command. Each command’s documentation is also available here
Tip
Tab-completion will work on most OPEN commands, although it will automatically insert the leading percent sign (which is fine).
Let’s start by reading radial velocity measurements from a sample file.


Currently studying Computer Science, Applied Mathematics and Economics at Columbia University in the City of New York. Interested in applying technology to solve problems around the world
Developed a universal searching voice assistant for the mobile reader application. Invited to return and responsible for building from scratch an intelligent microservice, which consists of a pipeline incorporating Recommender Systems, Text Classification Models and Topic Modelling Algorithms
Bolstered the expansion of DeepXplore, the first automated white-box testing system for deep learning systems. Identified exact functions and adaptations to the DeepXplore library that could help find inputs that trigger differential behaviors for Generative Adversarial Networks (GANs). Currently developing unique software (for publication) that utilizes neuron coverage as a feature for significantly reducing the training time and increasing the efficiency of Deep Learning Systems
Conceptualized, developed and integrated an end-to-end micro service that incorporated an intelligent semantic understanding tool and a recommendation system into an existing learning platform. Generated Text Classification Models and Matrix Factorization Algorithms with 95% accuracy. Constructed a Neo4j Graph Database and implemented optimized, production level RESTful APIs in Flask and Node.js. Oversight of product deployment to an AWS EC2 instance and introduced methodologies and best practices to enhance release processes
Researched in the area of 'Identifying Typo-Squatted Domains through Natural Language Processing' under the mentorship of Kevin Borgolte, a Ph.D. Candidate. Hands-on experience as a research intern in the computer science lab. Presented a final research paper at a symposium and participated in the poster session. Earned 8 credits in INT93P - Presentation Techniques in Research and INT93R – Introduction to Research Techniques courses with a 4.0 GPA
Minor in Applied Mathematics
Final Score: 43/45 points (7 points in Math, Physics and Economics HL)
Axia is a web application that aims to make comparable analysis easier. Axia uses Natural Language Processing and Machine Learning methods to generate similarity relationships and stores them in a graph database to make it easier to perform competitive analysis, comparable valuations and benchmarking.
RESTful Api, React.js, Tensorflow, Natural Language Toolkit
HospiShare is an Android mobile application with a social objective that I launched in 2016. It seeks to connect the smart phone enabled users with other users with elderly parents. It enables users to avoid taking too many workdays off for hospital visits by connecting with users who offer to take their parents to the hospital instead. You can check the initiative out here
Android Studio, Firebase, Canvas
Galleons is an android application that scans your reciepts and classifies your expenses. It also helps you find affordable places near you based on your budget.
Android Studio, Tensorflow, Text Classification
Apart from building my programming and engineering skills, I enjoy reading, playing basketball and debating about international affairs
Otherwise, I follow many television shows, and I spend a large amount of my free time exploring the latest technology advancements in Machine Learning and Artificial Intelligence.


The Creators of The Monkeys Lovers Application
Angham Alshahoud
Angham is a student, and she loves monkeys.
Summary
I work hard to create websites.


Home
About
Projects
Resume
Hi I'm Sarah
A Web Designer
Contact Me
I'd love to help!
✉<EMAIL_ADDRESS>☏<PHONE_NUMBER>
Barrie, ON


Here are some projects from either my hobbies or job. FYI, there are some projects not listed because they are in early stage development, or not ready to showcase.
AAPI Business Collective
2021
AAPI Business Collective is a directory for businesses owned by Asian Americans and Pacific Islanders. Since the start of Covid-19 pandemic, businesses owned by AAPI have been heavily impacted due to economic hardships, fear and racism. My friend Ada and I created AAPI Business Collective to be a platform for promoting and supporting AAPI businesses, and to be a common space for customers looking to shop at AAPI businesses.
AAPI Business Collective Website
Stack: Python, Flask, Vue.js
Emotivo Health
2019
Find your therapist match with Emotivo Health. I have long been a mental health advocate, so along with two friends, we built Emotivo Health to help people find their therapists.
Stack: Django, Python, PostgreSQL, React
Where's My Car Android App
2013
Where’s My Car is an easy to use app with an intuitive interface that tracks where you parked, and helps you find your car. The app's features include: save your car’s location, view road and satellite maps and open saved locations in your phone’s navigation.
Where's My Car on Google Play
Stack: Android, Java, Google Maps API
Pilot Fish WordPress Theme
2012
Voted as one of the 40 Best Free Responsive WordPress Themes for 2012, Pilot Fish is a minimal and elegant WordPress portfolio theme. It is inspired by the novel 『パイロットフィッシュ』(by Osaki Yoshio) I read while living in Sendai, Japan. It is said that a pilot fish is the fish you keep in the fish tank before a tropical fish, so as to develop a sustainable environment for which to thrive later. I called my first WordPress theme Pilot Fish hoping it would help me learn more about WordPress, and contribute to better themes in the future.
Pilot Fish On WordPress
Stack: WordPress, PHP, HTML, CSS, jQuery


app.css.append_css({ "external_url": "https://codepen.io/chriddyp/pen/bWLwgP.css" })You can extract the stylesheet from the Codepen playground by appending ".css" to the end of any codepen URL (e.g. https://codepen.io/chriddyp/pen/bWLwgP.css. You can either use this Codepen directly or you can fork this Codepen and modify it and embed the forked URL.
The grid is a 12-column fluid grid with a max width of 960px, that shrinks with the browser/device at smaller sizes. The max width can be changed with one line of CSS and all columns will resize accordingly. The syntax is simple and it makes coding responsive much easier. Go ahead, resize the browser.
Type is all set with the rems
, so font-sizes and spacial relationships can be responsively sized based on a single
font-size property. Out of the box, Dash never changes the
font-size,
but it's there in case you need it for your project. All measurements are still base 10 though so, an

with 5.0rem
font-size just means 50px
.
The typography base is Open Sans served by Google, set at 15rem (15px) over a 1.6 line height (24px). Other type basics like anchors, strong, emphasis, and underline are all obviously included.
Don't forget blockquotes! Blockquotes have a simple left border and an indent, there is nothing too fancy here. These styles are meant to be familiar to GitHub markdown users.
Headings create a family of distinct sizes each with specific letter-spacing
, line-height
, and margins
.

4.5rem

3.6rem

3.0rem

2.6rem

2.2rem

2.0remForms are a huge pain, but hopefully these styles make it a bit easier. All inputs, select, and buttons are normalized for a common height cross-browser so inputs can be stacked or placed alongside each other.
Code styling is kept basic – just wrap anything in a
and it will appear like this
. For blocks of code, wrap a
with a

.
.some-class {
background-color: red;
}
Be sure to use properly formed table markup with

and

when building a table
.
| Name | Age | Sex | Location |
|---|---|---|---|
| Dave Gamache | 26 | Male | San Francisco |
| Dwayne Johnson | 42 | Male | Hayward |
Dash uses media queries to serve its scalable grid, but also has a list of queries for convenience of styling your site across devices. The queries are mobile-first, meaning they target min-width
. Mobile-first queries are how Dash's
grid is built and is the preferrable method of organizing CSS. It means all styles outside of a query apply to all devices, then larger devices are targeted for enhancement. This prevents small devices from having to parse tons of unused CSS. The
sizes for the queries are:


|
ovs all
|
Public Member Functions | |
| def | __init__ (self) |
| def | fd_wait (self, fd, events) |
| def | timer_wait (self, msec) |
| def | timer_wait_until (self, msec) |
| def | immediate_wake (self) |
| def | block (self) |
Data Fields | |
| timeout | |
| poll | |
High-level wrapper around the "poll" system call. Intended usage is for the program's main loop to go about its business servicing whatever events it needs to. Then, when it runs out of immediate tasks, it calls each subordinate module or object's "wait" function, which in turn calls one (or more) of the functions Poller.fd_wait(), Poller.immediate_wake(), and Poller.timer_wait() to register to be awakened when the appropriate event occurs. Then the main loop calls Poller.block(), which blocks until one of the registered events happens.
| def ovs.poller.Poller.block | ( | self | ) |
Blocks until one or more of the events registered with self.fd_wait() occurs, or until the minimum duration registered with self.timer_wait() elapses, or not at all if self.immediate_wake() has been called.
| def ovs.poller.Poller.fd_wait | ( | self, | |
| fd, | |||
| events | |||
| ) |
Registers 'fd' as waiting for the specified 'events' (which should be select.POLLIN or select.POLLOUT or their bitwise-OR). The following call to self.block() will wake up when 'fd' becomes ready for one or more of the requested events. The event registration is one-shot: only the following call to self.block() is affected. The event will need to be re-registered after self.block() is called if it is to persist. 'fd' may be an integer file descriptor or an object with a fileno() method that returns an integer file descriptor.
| def ovs.poller.Poller.immediate_wake | ( | self | ) |
| def ovs.poller.Poller.timer_wait | ( | self, | |
| msec | |||
| ) |
Causes the following call to self.block() to block for no more than 'msec' milliseconds. If 'msec' is nonpositive, the following call to self.block() will not block at all. The timer registration is one-shot: only the following call to self.block() is affected. The timer will need to be re-registered after self.block() is called if it is to persist.
| def ovs.poller.Poller.timer_wait_until | ( | self, | |
| msec | |||
| ) |
Causes the following call to self.block() to wake up when the current time, as returned by ovs.timeval.msec(), reaches 'msec' or later. If 'msec' is earlier than the current time, the following call to self.block() will not block at all. The timer registration is one-shot: only the following call to self.block() is affected. The timer will need to be re-registered after self.block() is called if it is to persist.
| ovs.poller.Poller.poll |
| ovs.poller.Poller.timeout |


{% include 'ico.html' %}
Please look at the camera
Recommend images: 5, Images captured:
0
Capture
forward


Videos
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
Fisheries
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
Fisheries
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}
{% include "templates/includes/_listing.html" %}


{{ lp.title }}
{{ lp.description }}
{{ lp.description }}
Add multiple authors by hitting enter. The preferred format is
FirstInitial. LastName
. Only the first author will always be shown and
the remaining authors will be wrapped into an expandable et al.
link.
If multiple first authors are needed, separate them by a slash (/
).
The email address for the owner/submitter is automatically pre-filled.
The first field in Project
is a short (3-30 characters) URL-safe
name. Please only use lower-case and alpha-numeric characters separated by
underscores. The other two fields in Project
are short title (5-30
characters) and long title (5-55 characters).
The Description
field contains a brief paragraph using 5-1500
characters to describe the project. The first sentence will always be shown and the
remaining sentences will be wrapped into an expandable More
link.
References
is a list of label/URL pairs to point to additional
resources for the project (papers, websites etc.). Labels are preferred to be short
form like journal abbreviations (e.g. PRL, Nature). Please try to use DOIs as URLs
whenever possible in the form of https://doi.org/...
. At least one
reference is required.


{{ content }}
About ORSO
This is an online home for the open reflectivity standards organisation (ORSO), a collaborative network of scientists interested in neutron and X-ray reflectometry.
It is intended that this website contains information relevant to all levels of interst in reflectometry.
Resources: This website has a number of educational resources for reflectometry and directories for where you can find more information
ORSO is divided into four working groups which cover different aspects of this collaboration.
Education and outreach: The education and outreach working group aims to develop understanding of reflectivity techniques and disseminate information about reflectivity analysis.
File formats: This working group aims to draft a spec for a standard file format to be used across X-ray and neutron reflectivity. This is an important goal to move towards interoperability across facilities.
Data Analysis: The working group focused on data analysis is targetting a universal descriptive model language for reflectometry analysis. Additionally, they hope to develop test cases for reflectometry calculations to ensure robustivity across analysis software.
Reproducibility: The reproducibility working group is focused on creating guidelines to ensure reproducibility of data reduction and analysis of neutron and X-ray reflectivity measurements.
The organisation has had two workshops to date and more are planned. Details can be found here
This organisation and working groups are open to all, to join a working group please just sign up on the message board or contact the group chair.
Additionally, there is a GitHub organisation that administers this webpage that you can become an owner of by contacting Andrew.


You can access every time and get update information your favorite teams
You have get benefit. Enjoy !


--- layout: default ---
This site uses Behaviour Bot Welcome to welcome users and track new contributors. Help encourage new contributors by adding Behavior Bot to your organization!


public abstract class LavaClient
extends java.lang.Object
LavaClientBuilder
.| Modifier and Type | Field and Description |
|---|---|
static long |
DEFAULT_BASE_INTERVAL
The default reconnect "base" interval to use.
|
static long |
DEFAULT_CACHE_EXPIRE_ACCESS
The default cache expire-after-access time, in milliseconds.
|
static long |
DEFAULT_CACHE_EXPIRE_WRITE
The default cache expire-after-write time, in milliseconds.
|
static ReconnectIntervalFunction |
DEFAULT_INTERVAL_EXPANDER
The default interval expander, equivalent to raising 2 to the amount of reconnect attempts.
|
static java.util.concurrent.TimeUnit |
DEFAULT_INTERVAL_UNIT
The default TimeUnit to wait for the provided interval in.
|
static long |
DEFAULT_MAX_INTERVAL
The value the reconnect interval is capped to.
|
static java.lang.String |
DEFAULT_PASSWORD
The default password to use for the Lavalink-Server.
|
static int |
DEFAULT_REST_PORT
The default port to use for the Lavalink-Server REST API.
|
static int |
DEFAULT_WS_PORT
The default port to use for the Lavalink-Server WebSocket.
|
| Modifier and Type | Method and Description |
|---|---|
abstract void |
addEntry(AudioNodeEntry entry)
Adds a not-null
AudioNode and opens a connection to it based on the information provided by the AudioNodeEntry . |
abstract void |
addNode(AudioNode node)
Adds a not-null
AudioNode and opens a connection to it (if it isn't already open). |
abstract java.util.List<AudioNode> |
getAudioNodes()
Used to fetch an unmodifiable list of all the
AudioNodes this client can connect to. |
abstract AudioNode |
getBestNode()
Fetches the
AudioNode with the least amount of load on it, used to balance the load of LavaPlayers on different nodes. |
abstract long |
getCacheExpireAfterAccessMs()
Fetches the amount of time from which track data will removed from the cache after being accessed (after being written).
|
abstract long |
getCacheExpireAfterWriteMs()
Fetches the amount of time from which track data will be removed from the cache after being written without being accessed.
|
abstract long |
getGlobalBaseReconnectInterval()
Fetches the default "base" interval for reconnecting purposes, used for default values and "expansion".
|
abstract ReconnectIntervalFunction |
getGlobalIntervalExpander()
Fetches the default interval "expander", used to change the reconnect interval for the next reconnect attempt.
|
abstract java.util.concurrent.TimeUnit |
getGlobalIntervalTimeUnit()
Fetches the default TimeUnit which is used to actually wait for the intervals in a good unit, such as MILLISECONDS, HOURS, etc.
|
abstract long |
getGlobalMaximumReconnectInterval()
Fetches the default maximum interval for reconnecting purposes, used to cap the provided reconnect interval
so that it never gets too high.
|
abstract int |
getGlobalRestPort()
Fetches the default REST API port for all
AudioNodes the client has access to. |
abstract java.lang.String |
getGlobalServerPassword()
Fetches the default password for all
AudioNodes the client has access to. |
abstract int |
getGlobalWebSocketPort()
Fetches the default WebSocket port for all
AudioNodes the client has access to. |
abstract LavaHttpManager |
getHttpManager()
Used to fetch the
LavaHttpManager associated with this client, which is used to get track data from an identifier. |
abstract com.github.benmanes.caffeine.cache.Cache<java.lang.String,TrackDataPair> |
getIdentifierCache()
Fetches the internal identifier cache used by LavaClient to cut down the impact of loading the same sources in quick succession.
|
abstract AudioNode |
getNodeByIdentifier(java.lang.String address,
int websocketPort)
Fetches an
AudioNode by address and port. |
abstract LavaPlayer |
getPlayerByGuildId(long guild_id)
Fetches a
LavaPlayer instance by Guild ID. |
abstract it.unimi.dsi.fastutil.longs.Long2ObjectMap<LavaPlayer> |
getPlayerMap()
Fetches an unmodifiable view of the internal player map.
|
abstract java.util.List<LavaPlayer> |
getPlayers()
Used to fetch an unmodifiable list of all the
LavaPlayers associated with this client. |
abstract int |
getShardCount()
Fetches the amount of shards specified during the construction of the LavaClient instance.
|
abstract long |
getUserId()
Fetches the User ID of the Bot User specified during the construction of the LavaClient instance.
|
abstract LavaPlayer |
newPlayer(AudioNode node,
long guild_id)
Fetches a not-null
LavaPlayer instance associated with a positive Guild ID. |
abstract LavaPlayer |
newPlayer(long guild_id)
Fetches a not-null
LavaPlayer instance associated with a positive Guild ID. |
abstract void |
removeEntry(AudioNodeEntry entry)
Attempts to remove the
AudioNode associated with the provided, not-null AudioNodeEntry . |
abstract void |
removeEntry(java.lang.String serverAddress,
int websocketPort)
Attempts to remove the
AudioNode associated with a provided server address and port. |
abstract void |
removeNode(AudioNode node)
Attempts to remove a not-null
AudioNode . |
abstract LavaPlayer |
removePlayer(long guild_id)
Attempts to remove a
LavaPlayer instance associated with a positive Guild ID. |
abstract LavaPlayer |
removePlayer(long guild_id,
boolean shouldDestroy)
Attempts to remove a
LavaPlayer instance associated with a positive Guild ID. |
abstract void |
shutdown()
Shuts down LavaClient (also resetting the state).
|
public static final int DEFAULT_REST_PORT
public static final int DEFAULT_WS_PORT
public static final java.lang.String DEFAULT_PASSWORD
public static final long DEFAULT_CACHE_EXPIRE_WRITE
public static final long DEFAULT_CACHE_EXPIRE_ACCESS
public static final long DEFAULT_BASE_INTERVAL
public static final long DEFAULT_MAX_INTERVAL
public static final java.util.concurrent.TimeUnit DEFAULT_INTERVAL_UNIT
public static final ReconnectIntervalFunction DEFAULT_INTERVAL_EXPANDER
@Nonnull public abstract java.util.List<LavaPlayer> getPlayers()
LavaPlayers
associated with this client.LavaPlayers
this client contains.@Nonnull public abstract java.util.List<AudioNode> getAudioNodes()
AudioNodes
this client can connect to.AudioNodes
this client can connect to.@Nonnull public abstract LavaHttpManager getHttpManager()
LavaHttpManager
associated with this client, which is used to get track data from an identifier.LavaHttpManager
used to grab track data from an identifier.@Nullable public abstract AudioNode getNodeByIdentifier(@Nonnull java.lang.String address, @Nonnegative int websocketPort)
AudioNode
by address and port. This operation is extremely fast as it only looks up the entry in a HashMap.address
- The not-null server address specified in the node's AudioNodeEntry
.websocketPort
- The positive server WebSocket port specified in the node's AudioNodeEntry
.AudioNode
associated with the provided server address and WebSocket port.java.lang.NullPointerException
- If the provided address was null
.java.lang.IllegalArgumentException
- If the provided WebSocket Port was negative.@Nullable public abstract LavaPlayer getPlayerByGuildId(@Nonnegative long guild_id)
LavaPlayer
instance by Guild ID.
This method will return null
if a player for the provided Guild ID doesn't exist, unlike previous versions of LavaClient.
guild_id
- The positive ID of the Guild.LavaPlayer
instance associated with the Guild ID.@Nonnull public abstract java.lang.String getGlobalServerPassword()
AudioNodes
the client has access to.
This value equates to "youshallnotpass" if it's not specified during the construction of the LavaClient instance.
@Nonnegative public abstract long getCacheExpireAfterWriteMs()
When a song loads, LavaClient caches the initial loading data temporarily so that the server nor the client have to re-load it for a certain period of time.
This value tells LavaClient how long to wait after data is written before it is removed, ignoring the access of the data.
If the data is not removed, memory usage will keep on going up which is bad for big bots or small bots on limited hardware.
This value equates to 1200000L milliseconds if it isn't manually specified during construction of the client.
getCacheExpireAfterAccessMs()
@Nonnegative public abstract long getCacheExpireAfterAccessMs()
When a song loads, LavaClient caches the initial loading data temporarily so that the server nor the client have to re-load it for a certain period of time.
This value tells LavaClient how long to wait after data is accessed before it is removed, ignoring the writing of the data.
If the data is not removed, memory usage will slowly creep up which is bad for big bots or small bots on limited hardware.
This value equates to 900000L milliseconds if it isn't manually specified during construction of the client.
getCacheExpireAfterWriteMs()
@Nonnegative public abstract int getGlobalWebSocketPort()
AudioNodes
the client has access to.
This value equates to 80 if it's not specified during the construction of the LavaClient instance.
public abstract long getGlobalBaseReconnectInterval()
As with almost all default values, this value can be overridden on a per-node basis. This value equates to 0L if it's not specified during construction of this client.
@Nonnegative public abstract long getGlobalMaximumReconnectInterval()
As with almost all default values, this value can be overridden on a per-node basis. This value equates to 15L if it's not specified during construction of this client.
@Nonnull public abstract ReconnectIntervalFunction getGlobalIntervalExpander()
As of v3.0.0, this expander returns 2 raised to the number of reconnect attempts. As with almost all default values, this value can be overridden on a per-node basis.
ReconnectIntervalFunction
used to change intervals.@Nonnull public abstract java.util.concurrent.TimeUnit getGlobalIntervalTimeUnit()
As of v3.0.0, the returned unit is TimeUnit#SECONDS, however as with almost all default values, this value can be overridden on a per-node basis.
@Nonnegative public abstract int getGlobalRestPort()
AudioNodes
the client has access to.
This value equates to 2333 if it's not specified during the construction of the LavaClient instance.
@Nonnegative public abstract int getShardCount()
AudioNodes
when connecting.@Nonnegative public abstract long getUserId()
AudioNodes
when connecting.public abstract void addNode(@Nonnull AudioNode node)
AudioNode
and opens a connection to it (if it isn't already open).
Note: This will overwrite and disconnect the client from the node if it pre-exists with the same information.
public abstract void removeNode(@Nonnull AudioNode node)
AudioNode
.
If no node was found with the attached information, no action will be performed. Additionally, if one was found the client will disconnect from it and then remove it from the global map.
public abstract void addEntry(@Nonnull AudioNodeEntry entry)
AudioNode
and opens a connection to it based on the information provided by the AudioNodeEntry
.entry
- The AudioNodeEntry
containing the address, the port, etc. of the AudioNode
.java.lang.NullPointerException
- If the provided entry
was null
.public abstract void removeEntry(@Nonnull AudioNodeEntry entry)
AudioNode
associated with the provided, not-null AudioNodeEntry
.
This will do nothing if no node was found, and it'll disconnect the client from the node and remove it if it was found.
entry
- The not-null AudioNodeEntry
used to identify and remove the associated AudioNode
.java.lang.NullPointerException
- If the provided AudioNodeEntry
was null
.public abstract void removeEntry(@Nonnull java.lang.String serverAddress, @Nonnegative int websocketPort)
AudioNode
associated with a provided server address and port.
This will do nothing if no node was found, and it'll disconnect the client from the node and remove it if it was found.
serverAddress
- The not-null raw address of the server without any scheme behind it.websocketPort
- The not-negative WebSocket port of the Lavalink Server.java.lang.NullPointerException
- If the provided server address was null
.java.lang.IllegalArgumentException
- If the provided WebSocket port was negative.@Nonnull public abstract com.github.benmanes.caffeine.cache.Cache<java.lang.String,TrackDataPair> getIdentifierCache()
Note: Editing this cache might cause some delay and bugs. Modifying it is your choice.
@Nonnull public abstract it.unimi.dsi.fastutil.longs.Long2ObjectMap<LavaPlayer> getPlayerMap()
Note: This returns an unmodifiable map, meaning any attempts to modify it will throw exceptions.
@Nonnull public abstract LavaPlayer newPlayer(@Nullable AudioNode node, @Nonnegative long guild_id)
LavaPlayer
instance associated with a positive Guild ID.
If a player is already found, it'll simply be returned. If one doesn't exist, it'll be created but NOT connected.
In this sense, a new player doesn't submit a Voice Update to an AudioNode
manually. Use an EventWaiter
wherever you can instead of manually creating new players.
node
- The possibly-null AudioNode
to set. Replaced with the best available node if this is null
.guild_id
- The positive ID of the Guild to connect to.LavaPlayer
instance.@Nonnull public abstract LavaPlayer newPlayer(@Nonnegative long guild_id)
LavaPlayer
instance associated with a positive Guild ID.
If a player is already found, it'll simply be returned. If one doesn't exist, it'll be created but NOT connected.
In this sense, a new player doesn't submit a Voice Update to an AudioNode
manually. Use an EventWaiter
wherever you can instead of manually creating new players.
guild_id
- The positive ID of the Guild to connect to.LavaPlayer
instance.@Nullable public abstract LavaPlayer removePlayer(@Nonnegative long guild_id, boolean shouldDestroy)
LavaPlayer
instance associated with a positive Guild ID.
If a player is found, it'll be destroyed only if it's connected and if shouldDestroy
is set to true.
If it isn't found, nothing will happen and null
will be returned.
guild_id
- The positive Guild ID associated with the LavaPlayer
instance.shouldDestroy
- If LavaClient should destroy the player before removing it.LavaPlayer
instance.java.lang.IllegalArgumentException
- If the provided Guild ID was negative.public abstract LavaPlayer removePlayer(@Nonnegative long guild_id)
LavaPlayer
instance associated with a positive Guild ID.
If a player is found, it'll simply be removed without anything else happening.
If it isn't found, nothing will happen and null
will be returned.
guild_id
- The positive Guild ID associated with the LavaPlayer
instance.LavaPlayer
instance.java.lang.IllegalArgumentException
- If the provided Guild ID was negative.public abstract void shutdown()
This method removes and disconnects from all AudioNodes
and LavaPlayers
and additionally shuts down the attached LavaHttpManager
.
java.lang.IllegalStateException
- If this client has already been shutdown.@Nullable public abstract AudioNode getBestNode()
AudioNode
with the least amount of load on it, used to balance the load of LavaPlayers
on different nodes.AudioNode
to connect to, returns null
if no node exists.


Hot-keys on this page
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| Module | statements | missing | excluded | coverage |
|---|---|---|---|---|
| Total | 92 | 27 | 0 | 71% |
| links\__init__.py | 0 | 0 | 0 | 100% |
| links\admin.py | 10 | 0 | 0 | 100% |
| links\apps.py | 3 | 3 | 0 | 0% |
| links\constant.py | 1 | 0 | 0 | 100% |
| links\models.py | 35 | 5 | 0 | 86% |
| links\tests.py | 1 | 1 | 0 | 0% |
| links\urls.py | 3 | 3 | 0 | 0% |
| links\utils.py | 6 | 3 | 0 | 50% |
| links\views.py | 1 | 1 | 0 | 0% |
| workshop\__init__.py | 0 | 0 | 0 | 100% |
| workshop\asgi.py | 4 | 4 | 0 | 0% |
| workshop\settings.py | 21 | 0 | 0 | 100% |
| workshop\urls.py | 3 | 3 | 0 | 0% |
| workshop\wsgi.py | 4 | 4 | 0 | 0% |
No items found using the specified filter.


{% extends "sentry/bases/modal.html" %} {% load i18n %} {% block title %}{% trans "No Organization Access" %} | {{ block.super }}{% endblock %} {% block wrapperclass %}windowed-small{% endblock %} {% block main %} {% trans "No Organization Access" %} {% trans "You don't have access to any organizations within Sentry. Talk to a Sentry administrator about getting access." %} {% endblock %}
{% trans "You don't have access to any organizations within Sentry. Talk to a Sentry administrator about getting access." %}


Aztecs
Berbers
Britons
Bulgarians
Burmese
Byzantines
Celts
Chinese
Cumans
Ethiopians
Franks
Goths
Huns
Incas
Indians
Italians
Japanese
Khmer
Koreans
Lithuanians
Magyars
Malay
Malians
Mayans
Mongols
Persians
Portuguese
Saracens
Slavs
Spanish
Tatars
Teutons
Turks
Vietnamese
Vikings
Version: Age of Empires II DE Update 34699 |
GitHub
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Made by hszemi
,
with huge thanks to Jineapple, TriRem, pip, and NkoDragaš
Item Metadata (cost, HP etc.) taken from
aoe2dat


| Name: MRS. MEENA | Reg No: 01-1SMMHC18 |
|---|---|
| Age / Sex:39/F | Contact No:<PHONE_NUMBER> |
| Marital Status:ML- 15 YEARS | Date:6/1/18 |
| Occupation:HOUSEWIFE (BED HISTORY) | Dr. PJFP |
Address: NATIVE GULBARGA INBLORE SINCE 14 YEARS. |
DIAGNOSIS- |
FROM 4 MONTHS HAING CONT BLEEDING FOR 20 DAYS . TOOK ALLO RX HORMONE.
LMP: 15TH DEC 2017.
KCO THYROID HYPO.
HAS GOT ALLERGY FROM 1 YEAR < SNEEZING ON RISING MNG, DUST LACHRYMATION ITCHING IN EYES AND IRRITTION IN EARS AND THROAT. TOO MUCH ALLERGY.
HEADACHE IS MORE. WHOLE HEAD AND BACK REGION. FEELS NAUSEATED. > VOMITING. TAKES TABLET.
FEELS LIKE EATING SWEET DURING HEADAHCE. TOOK MIGRAINE RX ALSO FR THT.
MNG MUS GO 3-4 TIMES FR MOTION LOOSE . IMM AFTER EATING N SMTIMES BEFORE EATING ALSO. HAPPENS 4-5 TIMES.
EARS PAIN < COLD, ITCHING
IF EATS ANY SOUR FOOD LIKE LEMON ORANGES BANANA IMM GETS ITCHING N ERUPTIONS ANYWHERE ON THE BODY.
RX:
SANGUINARIA 200 – MNG 3 PILLS B/FOOD.
WYETHIA 200 – AFTERNOON 3 PILLS B/FOOD.
SPONGIA 200 – NIGHT B/FOOD 3 PILLS
AMN 6C DISC 4-0-4
RUB 15 – NIGHT 1 B/FOOD.
20/1/18: lmp: 16/1/18. Bleeding scanty for 3 days today is 4th day. Not much change with medicines. No h/o of any disturbances mentally 4 months back. Travels more also gets headache. Vomiting feels better after vomiting. Sleep in the afternoon feels a bit better. Headache if she lacks sleep. Even if applies oil also imm affects sneezing and all. hairfall. beating type of pain feels like pressing with fingers feels better. Before marriage dysmen but now no pain. but after med feels painful. Father SI. If sees death will get dreams and fear of deaths. Children. Saw many deaths in childhood her grandmother her aunt younger and elder and elder uncle. Said all died of heart attack. If gets headache blurred vision forst and then increase in headache. Took postpone tablets for some puja.
Rx:
Sep 200 – 7 doses – alt.days. b/brush water mng
Iris v 200 – 1 dram pills.
Carc1m -2 doses. b/brush weekly once water.
Bryonia 1m+iris 1m – 4 pills sos headache. 2 darm pills.
Rub tablets 30 – 1-0-1 b/food.
10/2/18: LMP: 30/1/18. 15 DAYS ONLY GOT PERIOD. BLEEDIGN 3 DAYS . headache no change. cold running nose on waking in the morning. Gastric pbm left pain in the arm. After eno felt better. Cant take cold can bear heat.
Rx:
Thuja 200 – 1 dose water b.bbrush 11th feb
Ignatia 200 – 1 dose b.brush water 12 th feb
Sepia1m – 1 dose 15th feb 2018 b.brush
Iris v. 1m 1 dram pills 4-4-4-4 for 3 days.
Rub 15 – 1 dose night b/bfood.
3/3/18: this time 15 days bleeding didn’t come. Lmp: 30 / 1/ 18. Cold is there. Feels inc. headache better. Got once only and the intensity also was low. Dry tongue. Itching in the throat and tonsils hypertrophied and inflamed mildly. Feeling trobulsome with it. WT: 70KG.
Ignatia 200 – 1 dose b.brush water 11th march 2018
Sepia1m – 1 dose 15th march b.brush
Bell 200+amm carb 200 – 1 dram pills 4-4-4-4.
Rub 15 – 1 dose night b/bfood.
5/4/18: LMP: 30/1/18. HEADACHE REDUCED. ALLERGY IS SO MUCH. WHEN AKING TABS SHE IS FINE. IF STOPPED IT IS RECURING. EYES ITCHING, EAR PAIN AND ITCHING AND THROAT ITCHING. SNEEZING MORE ON WAKING. FEELING VERY WEAK FR SLIGHTEST WEIGHT OR WORK ALSO. ABD FEELS BLOATED. BODY PAIN. wt. 66.5 kg
RX:
Sepia 1m – 5 doses – 3 days once.
PULS 200– 2 DRAM PILLS 3-3-3.
APOCYANUM 200- 1 DRAM PILLS 3-3-3
RUB 15 DOSES – 1 DOSE NT B/FOOD.
PHYTOLACCA q +FUCUS Vesic Q 10-10-10 drops a/food water.
3/5/18: inabsentia. On phone. Frm mrning had some pain in abd took some hormone postponement pills scared tht she would get the period n this Sunday is the programme. Headache not much got 2 times took allo rx din reduce with homoeo sos. Allergy better. Weight feels same. Feeling a bit active than before by 50%.
Sepia 1m – 5 doses – 3 days once.
PULS 200– 2 DRAM PILLS 3-3-3.
Plain pills- 1 DRAM PILLS 3-3-3
RUB 15 DOSES – 1 DOSE NT B/FOOD.
PHYTOLACCA q +FUCUS Vesic Q 10-10-10 drops a/food water.
9/6/18: lmp: 11/5/18. 4/6/18. Normal flow. Cold and allergic symptoms. Headache was severe couldn’t control took allo rx 2-3 times. Before periods had headache and after too. Back of head and sides. and frontal started recently.almost whole head. Cant open eyes. Nauseaous. >vomiting. Tight bandaging amel. Allergic symptoms also there bt better than before. Frequency of the headache is dec but intensity is same. Eyes all itch terribly. Little cold also affects her. Sour food affects her. Gets headache. Food isn’t on time imm headache starts.
Rx:
Puls 1m – 2 doses.
Puls 0/1 4 pills sos – headache.
Rub 60 1-0-1 b/food.
Pentaphos 2-0-2
Thuja 1m – 1 dose.
4/8/18: LMP: 20/7/18. NORMAL BLEEDING. ALLERGY , EAR ITCHING. HEADACHE SEVERE. SNEEZIN MORE. 10 YEARS HAVING THIS HEADACHE. BP: 120/80MMHG. GASTRITIS.BACK PAIN. CANT SIT CANT STAND. AFTER ENO GOT BURPS AND FELT BETTER.
RX:
CARCINOSIN 7 DOSES 4 DAY S ONCE B/FOOD. MNG.
SEPIA1M – 4-4-4-4 2 DRAM PILLS
NICCOLUM MET 200 – 4 -4-4-4 – 1 DRAM.
KALI BI 200 – 4-4-4-4 2 DRAM PILLS
NAT PHOS 12X 4-4-4-4.
RUB 30 – 15 1 DOSE NIGHT B.FOOD.
3/9/18:
CARCINOSIN 7 DOSES 4 DAY S ONCE B/FOOD. MNG.
SEPIA1M – 4-4-4-4 2 DRAM PILLS
NICCOLUM MET 200 – 4 -4-4-4 – 1 DRAM.
KALI BI 200 – 4-4-4-4 2 DRAM PILLS
NAT PHOS 12X 4-4-4-4.
RUB 30 – 15 1 DOSE NIGHT B.FOOD.
FOR 1ST 3 DAYS:
CYCLAMEN/AMM CARB/WYETHIA 1M – 4-4-4-4.
24/10/18: cold is same. Lmp: 10/10/18. Eyes itching. Teeth pain . 2-3 days before periods gets nausea and headache. Feeling difficulty in breathing. Hairfall from 15 days.
Rx:
Arum d1m/spongia30/arundo200 – 4-4-4-4 for 4 days. Alternate weeks
Lachesis 200/thyroidinum1m – 4-4-4-4 for 4 days. Alternate weeks.
Psorinum200 7+7pl doses.– 1 dose night b/food.
24/11/18: feeling better. Lmp: 23/11/18.
Rx:
Arum d1m/spongia30/arundo200 – 4-4-4-4 for 4 days. Alternate weeks
Lachesis 1m/thyroidinum200 – 4-4-4-4 for 4 days. Alternate weeks.
Psorinum200 7+7pl doses.– 1 dose night b/food.
8/12/18: LMP: 24/11/18. ALLERGY ALSO BETTER THAN BEFORE. MNG TIMES THER BUT NOT THT SEVERE. HAIRFALL ALSO BETTER. 2-3 DAYS FELING TIRED. WT 72.4KG. BP: 100/80 MMHG.
RX:
Arum d1m/spongia30/arundo200 – 4-4-4-4 for 4 days. Alternate weeks 2 DRAM
Lachesis 1m/thyroidinum200 – 4-4-4-4 for 4 days. Alternate weeks. 2 DRAM
Psorinum200 7+7pl doses.– 1 dose ALTERNATE night b/food.
RUBRUM 30 – 1 DOSE NIGHT B/FOOD.
THYR 3X 2-0-2 A/FOOD.
9/2/19: LMP: 15/12/18, 14/1/19; 3/2/19. FM 5 DAYS COLD AND COUGH.
Arum d1m/spongia30/arundo200 – 4-4-4-4 for 4 days. Alternate weeks 2 DRAM
Lachesis 1m/thyroidinum1M – 4-4-4-4 for 4 days. Alternate weeks. 2 DRAM
Psorinum1M 7+7pl doses.– 1 dose ALTERNATE night b/food.
RUBRUM 30 – 1 DOSE NIGHT B/FOOD.
THYR 3X 2-0-2 A/FOOD.
FIRST 3 DAYS:
ARS ALB1M/GELS1M/BRY1M – 4-4-4-4-4.
NAT SULPH 4-4-4-4
18/5/19: lmp: 5/5/19.allergy in the morning. But better than before. Intramural fibroids. Teeth pain. headache there on n off. Periods before gets pain more. Nausea and headache. 3-4 day back had pain in the right leg completely. Eltroxin 50mg. wt: 70.8kg
Rx:
Arum d1m/spongia30/arundo200 – 4-4-4-4 for 4 days. Alternate weeks 2 DRAM
Calc carb200/thuja200/lapis alb200 – 4-4-4-4 for 4 days. Alternate weeks. 2 DRAM
Medorhinum1m – 4 doses – weekly. b/brush water.
RUBRUM 30 – 1 DOSE NIGHT B/FOOD.
Amn 30/frax 6c 4-4-4.b/food.


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# File vendor/plugins/rspec_on_rails/spec_resources/controllers/redirect_spec_controller.rb, line 38 def action_with_redirect_which_creates_query_string redirect_to :action => "somewhere", :id => 1111, :param1 => "value1", :param2 => "value2" end


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AMERICAN PIE 2 (2001) / ** 1/2
Directed by JB Rogers. Screenplay by Adam Herz, based on a story by David H Steinberg and Herz, and characters created by Herz. Starring Jason Biggs, Alyson Hannigan, Thomas Ian Nicholas. Running time: 107 minutes. Rated AA for mature subject matter and sexual content by the MFCB. Reviewed on August 29th, 2001.
By SHANNON PATRICK SULLIVAN
Synopsis: Home from college, Jim (Biggs), Kevin (Nicholas), Oz (Chris Klein), Finch (Eddie Kaye Thomas) and Stifler (Seann William Scott) rent a beach house for the summer. Jim gets sex lessons from Michelle (Hannigan) while awaiting Nadia (Shannon Elizabeth); Kevin pines after ex-girlfriend Vicky (Tara Reid), and Finch for Stifler's Mom; and Oz is reduced to phone sex with Heather (Mena Suvari). Will their friendship survive the summer?
Review: Despite a cast of unknowns, 1999's "American Pie" was a hilarious hit, paving the way for many lesser imitators. And although the first "Pie" wasn't exactly screaming out for a sequel, its box office success made one virtually inevitable. The result is not as good as its precursor -- unsurprising, given that the sheer freshness of "American Pie" was part of its appeal -- but "Pie 2" is nonetheless an enjoyable romp. To a large extent, the best ingredients of the original "Pie" shine here as well: Biggs is fine as hapless Jim, Eugene Levy is terrific as his well-intentioned father, and Hannigan sparkles as sexually deviant flutist Michelle. And, once again, Nicholas and Reid are forgettable as former couple Kevin and Vicky, and Natasha Lyonne's Jessica is given nothing to do. There are a few additional missteps this time: Stifler, entertaining in small doses in the first film, grows wearisome in the expanded role he's given here. And Finch, so enjoyable last time around, is trapped in basically the same joke throughout "Pie 2". There is also a sketchier feel to the script, like a tacit admission that it has little reason to exist. Although a few sequences stand out -- including phone sex between Klein and Suvari, and hilarious lessons in sex from Hannigan -- it would not come as a complete disappointment if this was the final slice of pie.
Copyright © 2001 Shannon Patrick Sullivan. Archived at The Popcorn Gallery, http://www.physics.mun.ca/~sps/movies.html
| Shannon Patrick Sullivan |<EMAIL_ADDRESS>| +---------------------------------+---------------------------------+ / Doctor Who: A Brief History of Time (Travel) go.to/drwho-history \ \__ We are all in the gutter but some of us are looking at the stars __/
========== X-RAMR-ID: 29368 X-Language: en X-RT-ReviewID: 247017 X-RT-TitleID: 1109236 X-RT-SourceID: 886 X-RT-AuthorID: 1699 X-RT-RatingText: 2.5/4
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Tutorial: Accessing GMAT Propagation and Navigation Features¶
The use case demonstration for the first GMAT API Beta build focuses on using the API for models that exercise core GMAT functions. For the purposes of this release of the API, the target use case suite shows how to setup and use force models, propagators, and measurement models. The implemented functionality in the Beta release includes the ability to drive GMAT scripts as well. That capability is described separately in Script Usage.
The goal of the use cases described here is to build a GMAT measurement model from core components, using the API functions. GMAT’s measurement models require a propagation component in order to solve the light transit time portion of the modeling. Propagation requires configuration of both a numerical integrator and of a force model, along with a spacecraft that supplies model parameters. This guide will walk Python and MATLAB users through the process of configuring these components in order to assemble a range measurement.
The problem demonstrated in the example code here provides modeling for an Earth orbiting spacecraft, “EarthOrbiter.” The spacecraft is an 80 kg vehicle modeled in a polar orbit with a 6600 km semimajor axis. That ensures that we need to configure a fair number of system parameters in order to build the simulation.
Verifying Setup¶
The GMAT API is included in releases of GMAT beginning with the R2020a release of the system. Once GMAT is installed, the API can be accessed from inside of the folder containing the GMAT application.
For Python, change directories to the GMAT bin folder and access the API help system:
>>> import gmatpy as gmat >>> gmat.Help() --------------------------------------- GMAT Application Programmer's Interface --------------------------------------- ...
For MATLAB users
Start MATLAB
Change directories to the installed GMAT bin directory
Load the API and access the help system:
>> load_gmat() No script provided to load. ans = Instance of GMAT Moderator is initialized. No script ready to run. >> gmat.gmat.Help() ans = --------------------------------------- GMAT Application Programmer's Interface --------------------------------------- ...
Getting Started with the API¶
Note
This section introduces several API functions and tools for users new to GMAT’s API by experimenting interactively with the system in Python. This section introduces interaction with the GMAT API, but is not necessary for the force model, propagation, and measurement configuration described below.
The modeling for this use case uses an Earth centered coordinate system with axes oriented in the mean of J2000 Equatorial frame. The coordinate system can be built using the Construct function of the API. The Python code for this object creation is:
import gmatpy as gmat
eartheq = gmat.Construct("CoordinateSystem", "EarthMJ2000Eq", "Earth", "MJ2000Eq")
Users can view the list of objects that have been built during a run using the ShowObjects() function:
>>> gmat.ShowObjects()
Current GMAT Objects
EarthMJ2000Eq
>>>
The code above created a coordinate system object, an axis system object, and connected those objects together for later use. The object cannot be fully exercised at this point because it is missing some key connections to the modeled space environment, consisting of a solar system model, member planets and the Sun and Moon, along with other internal objects used to tie a user’s components together.
For this example, the solar system is not yet connected to the new coordinate system, and the bodies needed for use - the Earth, for example - are also not yet connected. The coordinate system object’s state can be checked using its “IsInitialized()” method:
>>> eartheq.IsInitialized()
False
Objects that are ready for use return True from this call. The API prepares the objects for use with the Initialize() function:
>>> gmat.Initialize()
>>> eartheq.IsInitialized()
True
The Initialize() function prepares all of the objects that the user has created for use, and reports any objects that could not be prepared because of missing settings.
Objects can be removed individually from GMAT using the Clear(ObjectName) function, or all once using the Clear() function without specifying an object:
>>> gmat.ShowObjects()
Current GMAT Objects
EarthMJ2000Eq
>>> gmat.Clear("EarthMJ2000Eq")
'The object EarthMJ2000Eq has been removed from GMAT.'
>>> gmat.ShowObjects()
Current GMAT Objects
>>> eartheq = gmat.Construct("CoordinateSystem", "EMJ2k", "Earth", "MJ2000Eq")
>>> gmat.ShowObjects()
Current GMAT Objects
EMJ2k
>>> gmat.Clear()
'All configured objects have been removed from GMAT.'
>>> gmat.ShowObjects()
Current GMAT Objects
>>>
The full set of GMAT API commands are described in Functions Used in the GMAT API.
The functions used above are presented working interactively in the GMAT API. In the remainder of this section, the configuration is built in a Python script included with the GMAT release in the API folder. Matching MATLAB .m scripts are included in the API folder for users more comfortable working in that environment.
Spacecraft Configuration¶
Note
The Spacecraft Configuration and Force Model Setup examples are located in the Ex_R2020a_BasicForceModel.py file. An example of the full configuration, showing one configuration for the exercises, is in the Ex_R2020a_CompleteForceModel file.
To use one of these files, copy the file you plan to use into GMAT’s bin folder.
Spacecraft configuration requires that we define the initial spacecraft state data for the orbiter, and then configure the spacecraft properties needed for the force modeling.
Construction and The Initial State¶
Using this coordinate system, the spacecraft state can be configured. For this example, the spacecraft is in a circular polar orbit at the moon on July 20, 2020. The orbital state is set using the scripting
# Load GMAT into memory
import gmatpy as gmat
# Spacecraft configuration preliminaries
earthorb = gmat.Construct("Spacecraft", "EarthOrbiter")
earthorb.SetField("DateFormat", "UTCGregorian")
earthorb.SetField("Epoch", "20 Jul 2020 12:00:00.000")
earthorb.SetField("CoordinateSystem", "EarthMJ2000Eq")
earthorb.SetField("DisplayStateType", "Keplerian")
# Orbital state
earthorb.SetField("SMA", 6600)
earthorb.SetField("ECC", 0.05)
earthorb.SetField("INC", 78)
earthorb.SetField("RAAN", 45)
earthorb.SetField("AOP", 90)
earthorb.SetField("TA", 180)
Additional Spacecraft Parameters¶
The force model used for this example may include full field Earth gravity, point mass effects from the Sun and Moon (“Luna” for GMAT), Jacchia-Roberts drag, and solar radiation pressure. The latter forces require settings for the reflectivity and drag coefficients of the spacecraft, its surface areas for those forces, and the spacecraft mass. These settings are made using the SetField method, and resemble the corresponding GMAT scripting:
# Spacecraft ballistic properties for the SRP and Drag models
earthorb.SetField("SRPArea", 2.5)
earthorb.SetField("Cr", 1.75)
earthorb.SetField("DragArea", 1.8)
earthorb.SetField("Cd", 2.1)
earthorb.SetField("DryMass", 80)
For reference, the GMAT scripting for this configuration is
Create Spacecraft EarthOrbiter;
GMAT EarthOrbiter.DateFormat = UTCGregorian;
GMAT EarthOrbiter.Epoch = '20 Jul 2020 12:00:00.000';
GMAT EarthOrbiter.CoordinateSystem = MoonEc;
GMAT EarthOrbiter.DisplayStateType = Keplerian;
GMAT EarthOrbiter.SMA = 4000;
GMAT EarthOrbiter.ECC = 0.05;
GMAT EarthOrbiter.INC = 78;
GMAT EarthOrbiter.RAAN = 45;
GMAT EarthOrbiter.AOP = 90;
GMAT EarthOrbiter.TA = 180;
GMAT EarthOrbiter.DryMass = 80;
GMAT EarthOrbiter.Cd = 2.1;
GMAT EarthOrbiter.Cr = 1.75;
GMAT EarthOrbiter.DragArea = 1.8;
GMAT EarthOrbiter.SRPArea = 2.5;
Note
Differences between Python and MATLAB code
The code shown above and throughout this section is Python code. In the MATLAB version of this example, there are several differences worth noting because of the platform differences:
GMAT is loaded using the MATLAB load_gmat.m script. This script loads the GMAT libraries into MATLAB, initializes the GMAT system by reading a startup file and loading plugins and configuration data identified in that file, and optionally loads a GMAT script into memory.
Access to the GMAT functions is made using a call into a nested “gmat” class built for the underlying Java code. In general, where Python users type
sat = gmat.Construct("Spacecraft","Sat")
MATLAB users enter
sat = gmat.gmat.Construct('Spacecraft','Sat');
Type identification requires a call that sets the object type. In the Python implementation of the API, changes from the base GmatBase type to the derived type is automatic. In MATLAB/Java, the user needs to perform the cast. Where Python users type
sat = gmat.Construct("Spacecraft","Sat")
to work with a Spacecraft object, MATLAB users that need to interact with the object as a Spacecraft need to enter
sat = gmat.gmat.Construct('Spacecraft','Sat'); sat = gmat.Spacecraft.SetClass(sat);
A MATLAB class, GMATAPI, is provided in the bin folder which contains static functions that automatically handle the change from the base GmatBase type to the derived type just like in the Python API. MATLAB users can now type
sat = GMATAPI.Construct('Spacecraft','Sat');
This type setting becomes important when objects are passed to other objects using methods that require specific object type, as is the case when setting forces on a dynamics model or spacecraft on a propagation state manager (examples below).
Force Model Setup¶
GMAT hides the complexity of force modeling in the internal ODEModel class, which is aliased to the label “ForceModel” in GMAT scripting. The GMAT scripting for the force model used here is
Create ForceModel FM;
GMAT FM.CentralBody = Earth;
GMAT FM.PrimaryBodies = {Earth};
GMAT FM.GravityField.Earth.Degree = 8;
GMAT FM.GravityField.Earth.Order = 8;
GMAT FM.GravityField.Earth.PotentialFile = 'JGM3.cof';
Basic Force Model Configuration¶
Using the API is similar for force configuration, but not identical. The GMAT scripting hides the creation of individual forces and their collection into the ODEModel force container. Settings on the forces in an ODEModel are made by passing those settings from the force container to the corresponding force. API users access the forces directly, setting their parameters and force by force and passing the configured forces into the ODEModel container. The model scripted above is configured using the scripting
# Force model settings
fm = gmat.Construct("ForceModel", "FM")
fm.SetField("CentralBody", "Earth")
# An 8x8 JGM-3 Gravity Model
earthgrav = gmat.Construct("GravityField")
earthgrav.SetField("BodyName","Earth")
earthgrav.SetField("PotentialFile","../data/gravity/earth/JGM3.cof")
earthgrav.SetField("Degree",8)
earthgrav.SetField("Order",8)
# Add force to the dynamics model
fm.AddForce(earthgrav)
Note the difference in the calls to Construct in this example. The dynamics model is created using the line
fm = gmat.Construct("ForceModel", "FM")
and the gravity model component, with the code
earthgrav = gmat.Construct("GravityField")
The dynamics model has a name, “FM.” The gravity field does not have a name. Objects constructed with names are managed by the GMAT code running inside of the API library. Objects that do not have names are not managed by the library. The object ownership for those objects is the responsibility of the code that creates the object. For the dynamics model under construction here, the user has responsibility for the gravity field in this call:
# Unnamed: The user is responsible for this object
earthgrav = gmat.Construct("GravityField")
and then passes that responsibility to the dynamics model with this call:
# Add force to the dynamics model, passing ownership to the dynamics
fm.AddForce(earthgrav)
Connecting the Spacecraft¶
Before the force model can be used, it needs to be connected to the spacecraft that provides state data and force model parameters. GMAT does this using a component called a Propagation State Manager (PSM). The PSM component is not exposed to script users. It is built inside of the scripted Propagator object that connects together integrators and force models.
Users that want to work directly with a force model can do so by creating a Propagation State Manager object and working directly with it. The force model built above can be tested using this approach:
psm = gmat.PropagationStateManager()
psm.SetObject(earthorb)
psm.BuildState()
The last line here, “psm.BuildState()”, creates an internal state object that connects spacecraft properties to a vector of data used by the force model. The propagation state manager is connected to the force model, and its state set as the force model’s state, using the scripting
fm.SetPropStateManager(psm)
fm.SetState(psm.GetState())
Testing the Model¶
The steps above produce a GMAT force model configuration that can be used from the user’s application framework. All that remains is initialization of the objects, post initialization preparation, and then calls that exercise the model. Initialization connects the force model to GMAT’s underlying resources, including the solar system objects and core elements of the system infrastructure:
# Assemble all of the objects together
gmat.Initialize()
GMAT’s propagation subsystem, which includes the force model components, requires two additional steps before it can be used. First the state vector needs to be set up for the force and propagation modeling. This step determines and sets the size of the state and derivative vectors, and sets up mappings between the spacecraft that are modeled and that state vector. The second step passes the parameters needed for modeling into the force model and propagator objects that are used.
For direct access to the force modeling, the user needs to execute these steps directly:
# Finish force model setup:
## Map spacecraft state into the model
fm.BuildModelFromMap()
## Load physical parameters needed for the forces
fm.UpdateInitialData()
Users can display the Cartesian form of the state vector used in the modeling by accessing the state vector from the spacecraft:
# Now access state and get derivative data
pstate = earthorb.GetState().GetState()
print("State Vector: ", pstate)
Finally, the force model can be exercised either in its raw form as used by the integrators by calling the GetDerivatives() method:
fm.GetDerivatives(pstate)
dv = fm.GetDerivativeArray()
print("Derivative: ", dv)
or by calling it for a specific spacecraft object through the GetDerivativesForSpacecraft() method:
vec = fm.GetDerivativesForSpacecraft(earthorb)
print("SCDerivative: ", vec)
When these pieces are assembled together, a run of the Ex_R2020a_BasicForceModel script shows the input state and derivative outputs to the user:
Note: numbers have been truncated for display purposes
$ python3 Ex_R2020a_BasicForceModel.py
State Vector: [1018.819261, -1018.819261, -6778.562873, 5.226958, 5.226958, -1.374825e-15]
Derivative: [5.226958, 5.226958, -1.374825e-15, -0.00121383, 0.00121392, 0.00809840]
SCDerivative: 5.226958 5.226958 -1.374825e-15 -0.00121383 0.00121392 0.00809840
Exercises¶
Add point mass forces for the Sun and Moon to the force model. The GMAT class for point mass forces is named “PointMassForce”.
Use the propagation state manager to turn on the A-Matrix computation for the force model by passing the “AMatrix” setting to the propagation state manager using its SetProperty method.
Add a Jacchia-Roberts drag model and a solar radiation pressure model to the force model.
Propagator Setup¶
Note
The Propagator Setup example shown here is located in Ex_R2020a_PropagationStep.m file. It uses a basic force model by importing from the Ex_R2020a_BasicFM file, a stripped down version of the force model used in the previous section. An example of the full configuration, showing one solution for the exercises, is in the PropagateLoop file.
To use one of the propagation files, copy the file you plan to use into GMAT’s bin folder. Also copy the Ex_R2020a_BasicFM file.
In GMAT scripting the lines of script for a propagator,
Create Propagator PDProp
GMAT PDProp.FM = FM;
GMAT PDProp.Type = PrinceDormand78;
GMAT PDProp.InitialStepSize = 60;
GMAT PDProp.Accuracy = 1.0e-12;
GMAT PDProp.MinStep = 0.0;
create an object from the GMAT class PropSetup. This object is a container for an object that performs propagation either numerically through an Integrator object or analytically through an object implementing an analytic algorithm. The latter objects are used, in GMAT, for ephemeris propagators. The former are used for Runge-Kutta integrators, predictor-correctors, and other numerical integration algorithms that require associated dynamics models. When the propagator requires a dynamics model, that model is also managed by a PropSetup object. The key feature to know for propagator configuration in the GMAT API is that a “Propagator” is actually a PropSetup object that contains the propagation component and, for numerical integrators, a dynamics model.
Working interactively, an API user can see this relationship in Python:
>>> import gmatpy as gmat
>>> pdprop = gmat.Construct("Propagator","PDProp")
>>> pdprop
<gmatpy.gmat_py.PropSetup; proxy of <Swig Object of type 'PropSetup *' at 0x7f26b76a57e0> >
Propagator Component Setup¶
When a Propagator is scripted, a PropSetup is created that the user then configures for use. Using the provided MATLAB example, the code that loads the force model and builds the PropSetup is
% Load GMAT into memory
[myMod, gmatStartupPath, result] = load_gmat();
Ex_R2020a_BasicFM;
% Build the propagation container class
pdprop = GMATAPI.Construct("Propagator","PDProp");
The PropSetup constructed here is a container for the objects used in propagation. The next step configuring this container is creation and assignment of an integrator, performed using the steps
% Create and assign a numerical integrator for use in the propagation
gator = GMATAPI.Construct("PrinceDormand78");
pdprop.SetReference(gator);
The dynamics model also needs to be set on the PropSetup:
% Assign the force model imported from Ex_R2020a_BasicFM
pdprop.SetReference(fm);
Once the local references are set, the integrator settings can be made similarly to the dynamics model setting in the previous section:
% Set some of the fields for the integration
pdprop.SetField("InitialStepSize", 60.0);
pdprop.SetField("Accuracy", 1.0e-12);
pdprop.SetField("MinStep", 0.0);
Spacecraft and Final Initialization¶
In the preceding section, the propagation state manager was built as a separate component and configured to connect the spacecraft to the dynamics model. When working with a PropSetup component, the propagation state manager is integrated into the component. As an alternative to the manual steps to configure the propagation state manager, the PropSetup provides a function, PrepareInternals(), that handles this configuration for each propagated object added through the AddPropObject() function, and completes the initialization of the component and its integrator:
% Setup the spacecraft that is propagated
pdprop.AddPropObject(earthorb);
pdprop.PrepareInternals();
GMAT’s PropSetup component works by creating copies of the propagator and dynamics models. Those copies need to be set for the application environment so that the user can use them after configuration. The PropSetup provides a simple mechanism for accessing its copies. The code that refreshes the local variables for them to be used, is
% Refresh the 'gator reference
gator = pdprop.GetPropagator();
Running the Propagator¶
The propagator can now be used. A 60-second propagation is performed, showing the state data before and after the step, using the code
% Take a 60 second step, showing the state before and after
gator.GetState()
gator.Step(60);
gator.GetState()
These calls produce this output from Ex_R2020a_PropagationStep.m:
>> Ex_R2020a_PropagationStep
Initialize Moderator Status: 1
No script provided to load.
ans =
1.0e+03 *
1.018819261603825
-1.018819261603827
-6.778562873085272
0.005226958779502
0.005226958779502
-0.000000000000000
ans =
1.0e+03 *
1.330028382856595
-0.703241487939055
-6.763990149325915
0.005142965479731
0.005288543267909
0.000485610549370
>>
Exercises¶
Modify the Ex_R2020a_PropagationStep example to use a force model that includes the point mass Sun and Moon forces and solar radiation pressure.
Wrap the propagator in a loop so that propagation extends for a full day, displaying the epoch and position at each propagation step.
The GMAT API and Plug-in Modules¶
GMAT plug-in modules package new functionality into shared libraries that GMAT loads when it starts up. The API’s copy of GMAT loads these modules when they are identified in the GMAT startup file. Standard GMAT functions work on components from plugins, but the API calls have several restrictions.
Wrapped Plugins¶
The Station and Estimation plugin libraries in GMAT include SWIG wrapper code for the contained classes. This reduces the restrictions on those components.
As an example of the restrictions on wrapped plugin code, consider the Station plugin, which implements GMAT’s GroundStation class. Users of GMAT’s GroundStation class can access the full feature set for the class. The user is required in Python to cast constructed components to the derived class type by hand. The Python auto-cast feature in the GMAT core code is not accessible from the plugin component as seen below:
>>> import gmatpy as gmat
>>> station = gmat.Construct("GroundStation","Station")
>>> station
<gmatpy.gmat_py.GmatBase; proxy of <Swig Object of type 'GmatBase *' at 0x7fccdc983f60> >
>>> station=gmat.GroundStation.SetClass(station)
>>> station
<gmatpy.station_py.GroundStation; proxy of <Swig Object of type 'GroundStation *' at 0x7fccdc983fc0> >
>>>
Note that in this code, the station object returned from the call to the Construct() function is set as a GmatBase object. In order to treat it as a GroundStation object, the user needed to call the GroundStation.SetClass() method on the object in order for Python to identify the object’s subclass correctly.
MATLAB API users are not required to explicity cast the class, provided they use the GMATAPI MATLAB class, as shown below:
>> load_gmat();
No script provided to load.
>> station = GMATAPI.Construct("GroundStation","Station")
station =
Object of type GroundStation named Station
>> station.getClass()
ans =
class gmat.GroundStation
>>
Unwrapped Plugins¶
Plugin code that is not wrapped in SWIG can be accessed using the API, but only in a more restricted manner. As an example, at this writing the VF13ad optimizer is available as a GMAT component for users inside of Goddard Space Flight Center. The associated plugin builds a component with class name “VF13ad” that provides the optimization functionality. The VF13ad optimizer is derived from an Optimizer base class in the GMAT core code. API users can access that component as a GmatBase object, or as an Optimizer object, but not as a VF13ad object, as can be seen here:
>>> import gmatpy as gmat
>>> vf13 = gmat.Construct("VF13ad","VF13")
>>> vf13
<gmatpy.gmat_py.GmatBase; proxy of <Swig Object of type 'GmatBase *' at 0x7f615f50c2a0> >
>>> vf13 = gmat.VF13ad.SetClass(vf13)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: module 'gmatpy' has no attribute 'VF13ad'
>>> vf13 = gmat.Optimizer.SetClass(vf13)
>>> vf13
<gmatpy.gmat_py.Optimizer; proxy of <Swig Object of type 'Optimizer *' at 0x7f614d9cff90> >
>>> exit()
The underlying object remains a VF13ad component:
>>> vf13.Help()
VF13ad VF13
Field Type Value
--------------------------------------------------------
ShowProgress Boolean true
ReportStyle List Normal
ReportFile Filename <not set>
MaximumIterations Integer 200
Tolerance Real 1e-05
UseCentralDifferences Boolean false
FeasibilityTolerance Real 0.001
but, from the perspective of an API user, is manipulated as an Optimizer or GmatBase object.
Measurement Modeling¶
Note
The Measurement Modeling example shown here is located in Ex_R2020a_RangeMeasurement.m file (or the Ex_R2020a_RangeMeasurement.py file for Python users).
GMAT’s Measurement Models are driven through the TrackingFileSet class. A TrackingFileSet defines a measurement as a tracking configuration consisting of a signal path and measurement type. The signal path is defined by the nodes that a measurement signal traverses to create the measurement. For example, the path may be ground station -> spacecraft -> ground station for a range measurement.
The user configures the hardware for each node, assigning antennae, transmitters, receivers, and transponders as needed to the stations and spacecraft used in the measurement. Error models are configured and assigned to each measurement, media corrections are toggled, and ancillary components configured - like propagators is light time correction is applied - to complete the configuration the user needs. The system is complex because the processes involved have many options. This guide, and the sample script, step through the process element by element to build the model.
Spacecraft, Ground Stations, and Propagators¶
% Construct the PropSetup to control propagation (for light time)
prop = GMATAPI.Construct("PropSetup", "prop");
prop.GetODEModel().SetField("ErrorControl", "None");
prop.GetPropagator().SetNumber("MinStep", 0);
% Create objects for generating measurement
simsat = GMATAPI.Construct("Spacecraft", "SimSat");
gds = GMATAPI.Construct("GroundStation", "GDS");
% Configure Spacecraft initial conditions
simsat.SetField("DateFormat", "A1ModJulian");
simsat.SetField("Epoch", "21550");
% Configure GroundStation
gds.SetField("StateType", "Spherical");
gds.SetField("HorizonReference", "Ellipsoid");
gds.SetField("Location1", 0);
gds.SetField("Location2", 90.0);
gds.SetField("Location3", 0);
Hardware Components¶
% Create communication hardware
% Hardware for ground station
ant1 = GMATAPI.Construct("Antenna", "Antenna1");
tmit = GMATAPI.Construct("Transmitter", "Transmitter1");
tmit.SetField("Frequency", 2067.5);
rec = GMATAPI.Construct("Receiver", "Receiver1");
% Hardware for spacecraft
ant2 = GMATAPI.Construct("Antenna", "Antenna2");
tpond = GMATAPI.Construct("Transponder", "Transponder1");
tpond.SetField("TurnAroundRatio","240/221");
% Set fields
% Use Antenna1 for Transmitter1 and Receiver1
tmit.SetField("PrimaryAntenna","Antenna1");
rec.SetField("PrimaryAntenna","Antenna1");
% Use Antenna2 for Transponder1
tpond.SetField("PrimaryAntenna","Antenna2");
% Add Antenna2 and Transponder1 to spacecraft
simsat.SetField("AddHardware","{Antenna2, Transponder1}");
% Add Antenna1, Transmitter1, and Receiver1 to station
gds.SetField("AddHardware","{Antenna1, Transmitter1, Receiver1}");
Error Models¶
% Define range measurements and error model
tem = GMATAPI.Construct("ErrorModel", "TheErrorModel");
% Specify these measurements are range measurements in km
tem.SetField("Type","Range");
tem.SetField("NoiseSigma", 0.050); % Standard deviation of noise
tem.SetField("Bias",0); % Bias in measurement
% Define doppler range rate measurements and error model
tem2 = GMATAPI.Construct("ErrorModel", "TheErrorModel2");
% Specify these measurements are doppler range rate measurements
tem2.SetField("Type","RangeRate");
tem2.SetField("NoiseSigma", 5e-5); % Standard deviation of noise
tem2.SetField("Bias",0); % Bias in measurement
% Add ErrorModels to the ground station
gds.SetField("ErrorModels","{TheErrorModel, TheErrorModel2}");
The Measurement¶
% Create a TrackingFileSet to manage the observations
tfs = GMATAPI.Construct("TrackingFileSet", "SimData");
tfs.SetField("FileName","TrkFile_API_GN.gmd"); % Still needed even though it's' not written to
tfs.SetField("UseLightTime", false);
tfs.SetField("UseRelativityCorrection", false);
tfs.SetField("UseETminusTAI", false);
% Define signal paths and measurement type(s)
% 2-way measurements are used here along the path GDS -> SimSat -> GDS
% Add range measurements to TrackingFileSet
tfs.SetField("AddTrackingConfig", "{{GDS,SimSat,GDS}, Range}");
% Add doppler range rate measurements to TrackingFileSet
tfs.SetField("AddTrackingConfig", "{{GDS,SimSat,GDS}, RangeRate}");
tfs.SetPropagator(prop); % Tell TrackingFileSet the propagator to use
Exercising the Model¶
% Initialize the GMAT objects
gmat.gmat.Initialize()
% Calculate the measurement
tdas = tfs.GetAdapters();
numMeas = tdas.size();
tda = tdas.get(0);
md0 = tda.CalculateMeasurement();
disp("GMAT Range Measurement Value:")
disp(md0.getValue().get(0))
% Make sure this is correct
satState = simsat.GetState();
gsPos = gds.GetMJ2000Position(satState.GetEpochGT()).GetDataVector();
satPos = satState.GetState();
r = gsPos - satPos(1:3);
rNorm = norm(r);
disp("Numerical Range Measurement Value (no lighttime):")
disp(2*rNorm)
disp("")
xid = simsat.GetParameterID("CartesianX");
tda.CalculateMeasurementDerivatives(simsat,xid);
for ii = 0:5
deriv(ii+1) = tda.ApiGetDerivativeValue(0,ii);
end
disp("GMAT Range Measurement Derivatives:")
disp(deriv)
disp("")
tda = tdas.get(1);
md1 = tda.CalculateMeasurement();
disp("GMAT RangeRate Measurement Value:")
disp(md1.getValue().get(0))
Exercises¶
Modify the one day propagation script to report the range measurement at each step where a valid measurement can be computed.
Add a second ground station the Ex_R2020a_RangeMeasurement example and report its measurement data.


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Lions defense not pulling its weight
by APALLEN PARK, Mich. (AP) — As hard as this is to believe, Matthew Stafford’s injury may not be Detroit’s biggest problem.
The veteran quarterback missed a second straight game last weekend with back and hip problems, but unless he could have played defense, Stafford might not have been able to win that game. The Lions put up a decent amount of points but lost 35-27 to Dallas.
Detroit has allowed at least 20 points in nine of its 10 games this season. The Lions have allowed at least 31 points in four of their past seven.
“The way the whole season is turning out right now is definitely shocking to me,” defensive back Tracy Walker said.
Detroit’s postseason hopes are pretty much done, and it’s not clear when Stafford might play again. Coach Matt Patricia said Monday the team is “week to week” with that situation. Backup Jeff Driskel wasn’t bad against the Cowboys, though. The Lions scored enough to stay in the game.
It was the defense that didn’t pull its weight. Dak Prescott threw for 444 yards and three touchdowns.
“I would say on the defensive side of the ball, we know the Cowboys do a lot of shifts, a lot of motions, a lot of different formations, things like that,” Patricia said. “So there was going to be some communication out on the field that we had to get right, and I think we missed a couple of those, which was disappointing to see from that aspect of it and opened up some big plays.”
WHAT’S WORKING
Stafford hadn’t missed a start since the 2010 season, but the offense was reasonably productive without him last weekend. The Lions are also without injured running back Kerryon Johnson.
Driskel threw for 209 yards and two touchdowns against the Cowboys, and the Lions did not have a turnover.
WHAT NEEDS HELP
Pretty much everything on the defensive side of the ball is substandard, and that’s after the Lions made major additions on the defensive line before the season. Detroit is allowing 413 yards a game — only Arizona and Cincinnati have marks worse than that. The Lions are also near the bottom of the NFL against the pass, and they haven’t been great at stopping the run either.
Walker demurred after he was asked if players are being put in the proper positioning.
“When it comes to all that, dealing with the coaching and the play calling, I stay away from that,” he said. “When it comes to me, I just do my job, and when my job called, I handle my responsibilities.”
STOCK UP
Bo Scarbrough’s stock was nonexistent before last weekend. He’d never played in an NFL game before the Lions signed him off the practice squad and put him in against Dallas. He had 14 carries for 55 yards and a touchdown.
STOCK DOWN
Patricia is getting serious criticism in the Detroit area, and it’s understandable. It’s not just that the Lions are losing. The defensive struggles in particular seem like an indictment of the second-year coach, who was the defensive coordinator with New England before being hired by the Lions.
Patricia was evasive when asked Monday about whether he’s taken more control of the defensive play calling.
“My role, really, on game day it differs game by game,” he said. “So some games it’s been more, some games it’s been less, and that’s been consistent throughout the season.”
INJURED
Patricia said defensive end Trey Flowers and offensive lineman Frank Ragnow were still in concussion protocol.
KEY NUMBER
7 — The number of passes of at least 20 yards allowed by the Lions on Sunday.
NEXT STEPS
The Lions are favored this weekend, when they’re on the road against an awful Washington team. Then they return home for their Thanksgiving game against Chicago.


--- layout: post title: Other People's Words, April 8th date: 2008-04-08 19:52:36.000000000 -07:00 type: post published: true status: publish categories: - Other People's Words tags: [] meta: _publicize_pending: '1' _edit_last: '6192' original_post_id: '21' _wp_old_slug: '21' author: login: falsefridays email<EMAIL_ADDRESS>display_name: Jim Withington first_name: '' last_name: '' ---
With the Muxtape phenomenon spreading like viral wildfire, this was bound to happen sooner or later. [via]
An overly bitter, shockingly honest list of 5 Karaoke Songs that Ladies Should Never Sing as an Attempt at Getting Attention. [via]
Darnielle posted a bit more about his illness; get well soon, eh?
The Sound Opinions South By Southwest wrap-up is always enlightening, plus it includes their take on the new REM.
Even livejournal is good for questions like Can anyone...recommend some more good music on the minimalist/ambient front? Soon, Casey, soon.
Finally, my good friend Zach (aka Crazy Purple People) and I started a twitter site to track our daily earworm conversations. Coming to a sidebar near you!


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| DOSE: |
1 hit |
oral |
LSD |
(blotter / tab) |
Yet another weekend, yet another sojourn down the lsd-brick road. Again, we have a more introspective experience, but hopefully still interesting to anyone not burdened by the need for sensationalism.
The night began in extremely banal circumstances. My fellow trip buddies and I sat around for several hours trying to work out what to do on a Saturday night in a fairly dead city. No idea seemed to satisfy, however, and we had resigned ourselves to a night of boredom. After awhile, though, someone recalled a party that may have been occurring that very night. Through a bit of remotivation we ended up deciding to go. At this point, the thought of acid was not even remotely close to being on the fringe of any of our conciousnesses. We arrive at the party, soft drugs in hand and proceed to smoke ourselves silly in an alienated pocket of the event. The gracious host, however, asked us if we wished for something more substantial and immediately had a vendor on hand to satisfy us. We bought more than our share, so we could maintain an archive, and munched one tab each to attempt to bring the night to life.
Nothing that odd happened at the party. Despite, at one point, a baby being brought in the house and left right where we had been smoking cones not minutes before. After awhile we decided to leave and drive back to a place of residence...the problem was, the drugs were already starting to kick in. Our driver undertook a sheer effort of will and managed to get us across the city at a constant 40km/h to where we needed to get. From this point we enshrouded ourselves in warmth and music and let the drugs take hold.
Timeframes from this point on are a bit garbled, so i shall relate different segments of the experience individually.
The drugs lasted for *ages*.  In fact, quite the opposite, the familiar state of bliss was evident for most of the trip, just the overwhelming feeling of being 'at home'. It's like I was born in a lsd-candy land but can now only afford to take small journies back.  Mixing the two is a story for perhaps another time, though, since I didn't quite have that luxury on the eve in question.
Most visuals behind closed eyes were quite impressive. Impossible to describe except as high definition multi-coloured structures of patterns. I guess my vocation gives my brain alot of things to work with when things are slightly skew. One day I shall endeavour to draw some of these whilst under the influence, so to provide a much more vivid description. There wasn't very much in the way of open-eyed visuals, except in a couple of small cases as will be explained.
One particularly disturbing part of the evening was dealing with an overly affectionate cat. This cat had trouble breathing and thus made strange noises. In semi-darkness with this cat sitting on my lap staring up, it became quite disquieting. From my view, all I saw was a feline shaped object making 'snarling' noises at me. The trouble was the cat was completely harmless, and this I knew, but my brain couldn't communicate this and so I began to get quite skittish of this snarling beast. After having to move the cat to regain composure...it came up again and sat next to me. This time, though, it wasn't an aural illusion that made my uncomfortable, but a visual one. The cat appeared as normal, except as I gazed up its back towards its head, it became narrower and narrower till its head was extremely small compared to the rest of it. The best way to describe it was a furry pyramid with legs and a small head at the tip of the pyramid.
Outside in the garden, staring up at the sky, was an almost religious experience. Drifting clouds give the acid-addled imagination almost too much input to play with, especially with a starry backdrop. It was here I could feel many vivid realisations making themselves apparent. They were of quite a personal nature, but as an overview, revolved around people in my life and their positions. I almost called the people in question to tell them, but at 3am and undergoing acidic rigour, I doubted I could make much sense. I don't know whether to trust my instincts under the effects, but the ideas felt so poignant and real that it was very hard to ignore.
It was also outside; that the trip hit it's hardest off the evening. This was after several cones, quite late in the evening. I was leaning against a pole and had my eyes closed as the world felt like it was on an angle and I needed to lean on the pole to stay upright.
The rest of the evening was sitting in a chair in a darkened room, having my brain wracked by psychedelic assaults and having limited discourse and much laughter with my fellow triphounds. Noteworthy events included dealing with the concept of not being solid entities and trying to eat weird toasted sandwiches.   I reckon with the pension you could afford a couple of bags a week and a tab a day.
To sum up...a rocking good trip, but as always, to communicate the specifics is so very hard. Perhaps ill take notes next time. Next time....eheh
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Melbourne Winter Masterpieces
NAPOLEON: REVOLUTION TO EMPIRE
Ground Level
Temporary Exhibition Space 1,2 & 3
02 JUN –
07 OCT 12


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8:45am: Continental Breakfast –
Herrick Lobby
9:30am: So, You’re an SNU Parent, Now What? -
Herrick
10:15-11am: Straight from the Top Series: Life Inside the Classroom -
Herrick
11:15am: Lunch for Family Groups 1-15 –
Webster Commons
Break For Family Groups 16-29
12:15pm: Lunch for Family Groups 16-29 –
Webster Commons
Break for Family Groups 1-15
1:15pm-2:15pm: Straight from Top Series: Life Outside the Classroom -
Herrick
2pm-2:45pm: Parent Panel -
Herrick
3:00-3:45pm: Concurrent Workshops for Students and Parents -
Various Locations (Pick 1)
3:55pm-4:35pm: Concurrent Workshops for Students and Parents -
Various Location (Pick 1)
4:45-5:15: Parent Wrap Up Session –
Herrick
Dinner on Your Own
For the evening, feel free to take in any of the OKC area attractions or you are welcome to join the students at our Football Scrimmage at 7:30pm.


Pokémon Sword/Shield Damage Calculator v0.9 i guess
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