|
MOTS Finder
Find non-star-shaped MOTSs
|
Riemannian 3-metric of a slice read from simulation data. More...
Public Member Functions | |
| def | __init__ (self, hdf5_file, fix_origin=False) |
| Create a 3-metric from a simulation data file. More... | |
| def | fix_origin (self) |
Whether fix_origin was set to True during construction. More... | |
| def | load_data (self, project=None) |
| Load the data from the data file and store it in an instance variable. More... | |
| def | __getstate__ (self) |
| Return a picklable state object representing the whole metric. More... | |
| def | __setstate__ (self, state) |
| Restore the complete object from the given unpickled state. More... | |
| def | data_file (self) |
| Filename of the data file containing the numerical simulation data. More... | |
| def | time (self) |
| Simulation coordinate time of the slice. More... | |
| def | iteration (self) |
| Iteration number of the current slice. More... | |
| def | interpolate (self) |
| Read/write property indicating whether interpolation should be performed. More... | |
| def | interpolate (self, value) |
| def | constraints (self, point, norm=False) |
| Compute the Hamiltonian and momentum constraints. More... | |
| def | prepare_for_point (self, point) |
| Prepare object for evaluation at given point (called internally). More... | |
| def | reset_cache (self) |
| Reset cached values to force re-evaluation upon next request. More... | |
| def | grid (self, xz_plane=True, ghost=0, full_output=False) |
| Generator to iterate over all grid points in the domain. More... | |
| def | shape (self) |
| Shape of the domain, i.e. of individual component matrices. More... | |
| def | box (self) |
| Index bounding box of the full domain. More... | |
| def | snap_to_grid (self, point) |
| Return the coordinates of the grid point closest to a given point. More... | |
| def | get_curv (self) |
| Return the extrinsic curvature object belonging to this metric. More... | |
| def | diff (self, point, inverse=False, diff=1, kw) |
| Compute (derivatives of) the metric tensor at a given point. More... | |
| def | diff_lnsqrtg (self, point, kw) |
Compute the three derivatives of ln(sqrt(det(g))) . More... | |
| Public Member Functions inherited from _ThreeMetric | |
| def | __init__ (self, dx=1e-8, fd_order=3) |
| Base class init for metrics. More... | |
| def | at (self, point) |
| Return the metric tensor at a given point. More... | |
| def | get_curv (self) |
| Return the extrinsic curvature belonging to this 3-metric. More... | |
| def | diff (self, point, inverse=False, diff=1, kw) |
| Return derivatives in x,y,z directions at the given point. More... | |
| def | diff_lnsqrtg (self, point, kw) |
| Return x,y,z derivatives of ln(sqrt(det(g))). More... | |
| def | christoffel (self, point) |
| Compute the Christoffel symbols of this 3-metric. More... | |
| def | christoffel_deriv (self, point) |
| Compute the derivatives of the Christoffel symbols. More... | |
| def | ricci_tensor (self, point) |
| Compute the components of the Ricci tensor. More... | |
| def | ricci_scalar (self, point) |
| Compute the scalar curvature (Ricci scalar). More... | |
Private Member Functions | |
| def | _gij (self) |
| Full set of component matrices (lazily loaded). More... | |
| def | _mat_at (self, point) |
| def | _cached_gij (self, point, diff=0, inverse=False) |
| Return/compute cached interpolated metric tensors. More... | |
Private Attributes | |
| _fix_origin | |
| Whether origin location was modified, i.e. "fixed" (debugging only). More... | |
| _data_file | |
| The filename containing the simulation data. More... | |
| _interpolate | |
| Whether Lagrange interpolation should be done. More... | |
| _time | |
| Coordinate time of the slice. More... | |
| _iteration | |
| Iteration number of the slice. More... | |
| _curv | |
| SioCurv object containing the extrinsic curvature of the slice. More... | |
| _gij_data | |
| The lazily loaded data matrices (SioDataPatch objects). More... | |
| _prev_pt | |
| The point (as 3-tuple) for which the cached values are valid. More... | |
| _cache_gij | |
| Cached metric tensor at a point. More... | |
| _cache_gij_inv | |
| Cached inverse of the metric tensor at a point. More... | |
| _cache_gij_diff | |
| Cached first derivatives of the metric in x, y, z direction. More... | |
| _cache_gij_diff2 | |
| Cached second derivatives of the metric. More... | |
Additional Inherited Members | |
| Public Attributes inherited from _ThreeMetric | |
| dx | |
| Step length for numerical differentiation. More... | |
| fd_order | |
| Finite difference approximation order for numerical differentiation. More... | |
Riemannian 3-metric of a slice read from simulation data.
The filename of the data file is stored as instance variable. When storing this object to disk (or in general when pickling it), the actual data is skipped and only the configuration and file name is stored. Upon loading (unpickling), the data is not immediately read from disk. Instead, it is loaded lazily, i.e. when first needed. This allows efficient loading of, for example, curve objects for plotting as they store a reference to the metric.
| def __init__ | ( | self, | |
| hdf5_file, | |||
fix_origin = False |
|||
| ) |
Create a 3-metric from a simulation data file.
| hdf5_file | The filename to load. |
| fix_origin | (For debugging only) Whether to move the origin by a few grid points to compensate for ghost point removal. Not needed (i.e. produces wrong results) in most cases. |
| def __getstate__ | ( | self | ) |
Return a picklable state object representing the whole metric.
| def __setstate__ | ( | self, | |
| state | |||
| ) |
Restore the complete object from the given unpickled state.
|
private |
Return/compute cached interpolated metric tensors.
Computing a metric tensor (represented as 3x3 matrix) at a given point
requires interpolation. Furthermore, derivatives of these tensors requires computing FD derivatives on a patch around the closest grid point followed by interpolation. Since the metric and its derivatives are often needed for some calculation at a given point, and some of these objects are needed to compute others, we cache the results once computed. This method relies on the cache to be reset if the point
is not the same as the last one this function had been called with.
diff=0
, returns the 3x3 matrix representing the metric interpolated at point
or the inverse metric if inverse=True
. If diff=1
, returns dg[i,j,k]
, where the indices mean and if diff=2
, returns ddg[i,j,k,l]
with indices .| point | The point at which to compute. |
| diff | Derivative order to compute. Default is 0 . |
| inverse | Whether to compute the inverse tensor. Can only be True for diff==0 . Default is False . |
|
private |
Full set of component matrices (lazily loaded).
The returned elements are the xx
, xy
, xz
, yy
, yz
, and zz
components in that order. Each component is a SioDataPatch object.
| def box | ( | self | ) |
Index bounding box of the full domain.
| def constraints | ( | self, | |
| point, | |||
norm = False |
|||
| ) |
Compute the Hamiltonian and momentum constraints.
If the constraints are satisfied exactly, the returned values will be zero. However, for numerical simulation data this will rarely ever be the case. The returned values can then be used to determine the accuracy of the simulation, e.g. by comparing them at different spatial resolutions (grid densities).
Note that this function is not optimized in any way and thus will perform poorly when evaluated on a large number of points (especially when interpolate=True
and interpolation is performed).
(scal_constr, vec_constr)
, where scal_constr
is a float representing the Hamiltonian constraint and vec_constr
the momentum constraint . The latter is a (3-D) covector (indices downstairs). Here, D
is the Levi-Civita covariant derivative compatible with g
, the slice's Riemannian 3-metric, K
is the extrinsic curvature of the slice and R
the scalar curvature of the slice. If norm=True
, the second element is a float, the g
-norm of the momentum constraint.| point | The point at which to compute the constraints. |
| norm | If True , compute the g -norm of the momentum constraint instead of the covector. Default is False . |
| def data_file | ( | self | ) |
Filename of the data file containing the numerical simulation data.
| def diff | ( | self, | |
| point, | |||
inverse = False , |
|||
diff = 1 , |
|||
| kw | |||
| ) |
Compute (derivatives of) the metric tensor at a given point.
diff=0
, returns the 3x3 matrix representing the metric interpolated at point
, i.e. . If diff=1
, returns dg[i,j,k]
, where the indices mean and if diff=2
, returns ddg[i,j,k,l]
with indices . In each case, if inverse=True
the inverse metric is used with indices upstairs.| point | The point at which to compute. |
| inverse | Whether to compute (derivatives of) the inverse metric. Default is False . |
| diff | Derivative order to compute. Default is 1 . |
| def diff_lnsqrtg | ( | self, | |
| point, | |||
| kw | |||
| ) |
Compute the three derivatives of ln(sqrt(det(g)))
.
| def fix_origin | ( | self | ) |
Whether fix_origin
was set to True
during construction.
| def get_curv | ( | self | ) |
Return the extrinsic curvature object belonging to this metric.
| def grid | ( | self, | |
xz_plane = True , |
|||
ghost = 0 , |
|||
full_output = False |
|||
| ) |
Generator to iterate over all grid points in the domain.
It is more efficient to avoid iterating over the whole grid in Python. Instead, many operations can be performed by utilizing numpy's ability to operate on whole matrices. This method should only be used if efficiency is not of highest concern.
| xz_plane | Whether to only output grid points on the xz-plane (i.e. for y=0 ). If the data contain ghost points in y-direction, this will pick out only those in the xz-plane. Default is True . |
| ghost | Number of ghost points to skip at the boundaries. Default is 0 . |
| full_output | If True , the yielded elements will consist of the matrix indices (i,j,k) and the physical coordinates (x,y,z) . Otherwise, only the matrix indices are yielded. Default is False . |
| def interpolate | ( | self | ) |
Read/write property indicating whether interpolation should be performed.
This is True
by default. If set to False
, each evaluation will first find the closest grid point to evaluate at and then compute all requested values at that grid point without need of interpolation.
| def iteration | ( | self | ) |
Iteration number of the current slice.
Note that requesting this attribute will not trigger the data to be loaded.
| def load_data | ( | self, | |
project = None |
|||
| ) |
Load the data from the data file and store it in an instance variable.
| project | The SioProject object. If not given, a new project object is created from the data file. |
| def prepare_for_point | ( | self, | |
| point | |||
| ) |
Prepare object for evaluation at given point (called internally).
This is called internally e.g. by diff(); users of this class usually don't have to call this directly. Its responsibility is to check whether the internal cache has to be updated. In case the interpolate
property is set to False
, the point will be snapped to the nearest grid point and returned. Otherwise, the point is returned unchanged.
| def reset_cache | ( | self | ) |
Reset cached values to force re-evaluation upon next request.
Users of this class usually don't call this; it is called by prepare_for_point() when the point at which to evaluate/interpolate is different from the last point at which evaluation was done.
| def shape | ( | self | ) |
Shape of the domain, i.e. of individual component matrices.
| def snap_to_grid | ( | self, | |
| point | |||
| ) |
Return the coordinates of the grid point closest to a given point.
| def time | ( | self | ) |
Simulation coordinate time of the slice.
Note that requesting this attribute will not trigger the data to be loaded.
|
private |
Cached metric tensor at a point.
|
private |
Cached first derivatives of the metric in x, y, z direction.
|
private |
Cached second derivatives of the metric.
|
private |
Cached inverse of the metric tensor at a point.
|
private |
SioCurv object containing the extrinsic curvature of the slice.
|
private |
The filename containing the simulation data.
|
private |
Whether origin location was modified, i.e. "fixed" (debugging only).
|
private |
The lazily loaded data matrices (SioDataPatch objects).
|
private |
Whether Lagrange interpolation should be done.
|
private |
Iteration number of the slice.
|
private |
The point (as 3-tuple) for which the cached values are valid.
|
private |
Coordinate time of the slice.


Flight Details
#{searchFlightsController.error}
Flight number
Date
Departure time (HH:MM)
Flight duration (minutes)
Total seats
Reserved seats
Pending seats
Price per person
#{util.getOnlyDate(searchFlightsController.detailedFlight.departureDate)}
Search for another flight


Welcome to the website!
On this website you can find all the information about our studio. See what projects we are working on. You can also order any service.
Projects
Since we are not a big studio, we do not work on many projects. But you can follow some projects on the website "itch.io" by clicking on the icon in the header of the site.
Services
Our Studio offers the following services:
Creating project on both PC and phone.
Creating 3D models.
To order or find out the cost of the service, contact us from the social network that is convenient for you by clicking on one of the buttons in the header of the site.
Info
Times New Roman Game Studio was created in 2020 by Russian student. To contact us, please write to the following email address<EMAIL_ADDRESS>Follow us on other social networks on the site header.


Here are a few sample accounts you can use to start playing:
Please, choose where you want to sign in:


%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff." />
Data scientists, according to interviews and expert estimates, spend from 50 percent to 80 percent of their time mired in this more mundane labor of collecting and preparing unruly digital data, before it can be explored for useful nuggets.
– “For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insight” - The New York Times, 2014
janitor has simple functions for examining and cleaning dirty data. It was built with beginning and intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff.
The main janitor functions:
table()
; andThe tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel.
janitor is a #tidyverse-oriented package. Specifically, it plays nicely with the %>%
pipe and is optimized for cleaning data brought in with the readr and readxl packages.
You can install:
the most recent officially-released version from CRAN with
install.packages("janitor")
the latest development version from GitHub with
install.packages("devtools")
devtools::install_github("sfirke/janitor")
A full description of each function, organized by topic, can be found in janitor’s catalog of functions vignette. There you will find functions not mentioned in this README, like compare_df_cols()
which provides a summary of differences in column names and types when given a set of data.frames.
Below are quick examples of how janitor tools are commonly used.
Take this roster of teachers at a fictional American high school, stored in the Microsoft Excel file dirty_data.xlsx:
Dirtiness includes:
Here’s that data after being read in to R:
library(pacman) # for loading packages
p_load(readxl, janitor, dplyr, here)
roster_raw <- read_excel(here("dirty_data.xlsx")) # available at http://github.com/sfirke/janitor
glimpse(roster_raw)
#> Observations: 13
#> Variables: 11
#> $ `First Name` <chr> "Jason", "Jason", "Alicia", "Ada", "Desus", "Chien-Shiung", "Chien-Shiung", NA,…
#> $ `Last Name` <chr> "Bourne", "Bourne", "Keys", "Lovelace", "Nice", "Wu", "Wu", NA, "Joyce", "Lamar…
#> $ `Employee Status` <chr> "Teacher", "Teacher", "Teacher", "Teacher", "Administration", "Teacher", "Teach…
#> $ Subject <chr> "PE", "Drafting", "Music", NA, "Dean", "Physics", "Chemistry", NA, "English", "…
#> $ `Hire Date` <dbl> 39690, 39690, 37118, 27515, 41431, 11037, 11037, NA, 32994, 27919, 42221, 34700…
#> $ `% Allocated` <dbl> 0.75, 0.25, 1.00, 1.00, 1.00, 0.50, 0.50, NA, 0.50, 0.50, NA, NA, 0.80
#> $ `Full time?` <chr> "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", NA, "No", "No", "No", "No", "N…
#> $ `do not edit! --->` <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ Certification <chr> "Physical ed", "Physical ed", "Instr. music", "PENDING", "PENDING", "Science 6-…
#> $ Certification__1 <chr> "Theater", "Theater", "Vocal music", "Computers", NA, "Physics", "Physics", NA,…
#> $ Certification__2 <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
Excel formatting led to an untitled empty column and 5 empty rows at the bottom of the table (only 12 records have any actual data). Bad column names are preserved.
Clean it with janitor functions:
roster <- roster_raw %>%
clean_names() %>%
remove_empty(c("rows", "cols")) %>%
mutate(hire_date = excel_numeric_to_date(hire_date),
cert = coalesce(certification, certification_1)) %>% # from dplyr
select(-certification, -certification_1) # drop unwanted columns
roster
#> # A tibble: 12 x 8
#> first_name last_name employee_status subject hire_date percent_allocated full_time cert
#> <chr> <chr> <chr> <chr> <date> <dbl> <chr> <chr>
#> 1 Jason Bourne Teacher PE 2008-08-30 0.75 Yes Physical ed
#> 2 Jason Bourne Teacher Drafting 2008-08-30 0.25 Yes Physical ed
#> 3 Alicia Keys Teacher Music 2001-08-15 1 Yes Instr. music
#> 4 Ada Lovelace Teacher <NA> 1975-05-01 1 Yes PENDING
#> 5 Desus Nice Administration Dean 2013-06-06 1 Yes PENDING
#> 6 Chien-Shiung Wu Teacher Physics 1930-03-20 0.5 Yes Science 6-12
#> 7 Chien-Shiung Wu Teacher Chemistry 1930-03-20 0.5 Yes Science 6-12
#> 8 James Joyce Teacher English 1990-05-01 0.5 No English 6-12
#> 9 Hedy Lamarr Teacher Science 1976-06-08 0.5 No PENDING
#> 10 Carlos Boozer Coach Basketball 2015-08-05 NA No Physical ed
#> 11 Young Boozer Coach <NA> 1995-01-01 NA No Political sci.
#> 12 Micheal Larsen Teacher English 2009-09-15 0.8 No Vocal music
The core janitor cleaning function is clean_names()
- call it whenever you load data into R. You can similarly clean any vector of names with make_clean_names()
.
Use get_dupes()
to identify and examine duplicate records during data cleaning. Let’s see if any teachers are listed more than once:
roster %>% get_dupes(first_name, last_name)
#> # A tibble: 4 x 9
#> first_name last_name dupe_count employee_status subject hire_date percent_allocat… full_time cert
#> <chr> <chr> <int> <chr> <chr> <date> <dbl> <chr> <chr>
#> 1 Chien-Shiung Wu 2 Teacher Physics 1930-03-20 0.5 Yes Science 6…
#> 2 Chien-Shiung Wu 2 Teacher Chemistry 1930-03-20 0.5 Yes Science 6…
#> 3 Jason Bourne 2 Teacher PE 2008-08-30 0.75 Yes Physical …
#> 4 Jason Bourne 2 Teacher Drafting 2008-08-30 0.25 Yes Physical …
Yes, some teachers appear twice. We ought to address this before counting employees.
A variable (or combinations of two or three variables) can be tabulated with tabyl()
. The resulting data.frame can be tweaked and formatted with the suite of adorn_
functions for quick analysis and printing of pretty results in a report. adorn_
functions can be helpful with non-tabyls, too.
tabyl
can be called two ways:
tabyl(roster$subject)
roster %>% tabyl(subject, employee_status)
.
%>%
pipe; this allows tabyl
to be used in an analysis pipelineLike table()
, but pipe-able, data.frame-based, and fully featured.
One variable:
roster %>%
tabyl(subject)
#> subject n percent valid_percent
#> Basketball 1 0.08333333 0.1
#> Chemistry 1 0.08333333 0.1
#> Dean 1 0.08333333 0.1
#> Drafting 1 0.08333333 0.1
#> English 2 0.16666667 0.2
#> Music 1 0.08333333 0.1
#> PE 1 0.08333333 0.1
#> Physics 1 0.08333333 0.1
#> Science 1 0.08333333 0.1
#> <NA> 2 0.16666667 NA
Two variables:
roster %>%
filter(hire_date > as.Date("1950-01-01")) %>%
tabyl(employee_status, full_time)
#> employee_status No Yes
#> Administration 0 1
#> Coach 2 0
#> Teacher 3 4
Three variables:
roster %>%
tabyl(full_time, subject, employee_status, show_missing_levels = FALSE)
#> $Administration
#> full_time Dean
#> Yes 1
#>
#> $Coach
#> full_time Basketball NA_
#> No 1 1
#>
#> $Teacher
#> full_time Chemistry Drafting English Music PE Physics Science NA_
#> No 0 0 2 0 0 0 1 0
#> Yes 1 1 0 1 1 1 0 1
Adorning tabyls
The adorn_
functions dress up the results of these tabulation calls for fast, basic reporting. Here are some of the functions that augment a summary table for reporting:
roster %>%
tabyl(employee_status, full_time) %>%
adorn_totals("row") %>%
adorn_percentages("row") %>%
adorn_pct_formatting() %>%
adorn_ns() %>%
adorn_title("combined")
#> employee_status/full_time No Yes
#> Administration 0.0% (0) 100.0% (1)
#> Coach 100.0% (2) 0.0% (0)
#> Teacher 33.3% (3) 66.7% (6)
#> Total 41.7% (5) 58.3% (7)
Pipe that right into knitr::kable()
in your RMarkdown report.
These modular adornments can be layered to reduce R’s deficit against Excel and SPSS when it comes to quick, informative counts.
You are welcome to:


Subscribe Widget for WordPress Sidebar
The following is a simple Subscribe widget for your WordPress sidebar that uses Feedburner's e-mail subscribe form and pretty straightforward HTML/CSS.
The following is a simple Subscribe widget for your WordPress sidebar that uses Feedburner's e-mail subscribe form and pretty straightforward HTML/CSS.


Compute partial dependence functions (i.e., marginal effects) for the
predictors in a model. Note that get_pd
is based on
pdp::partial
and adds observation weights.
get_pd(mfit, var, grid, data, subsample = nrow(data), fun = NULL, ...)
| mfit | Fitted model object (e.g., a "gbm" or "randomForest" object). |
|---|---|
| var | Character string giving the name of the predictor variable of
interest. For an interaction effect, specify as |
| grid | Data frame containing the (joint) values of interest for the
feature(s) listed in |
| data | Data frame containing the original training data. |
| subsample | Optional integer specifying the number of observations to
use for the computation of the partial dependencies. Defaults to the number
of observations in |
| ... | Additional optional arguments to be passed onto
|
| pred_fun | Optional prediction function to calculate feature effects for
the model in |
Tidy data frame (i.e., a "tibble" object) with three (x, y, w) or
four (x1, x2, y, w) columns for respectively a main and two-way interaction
effect. Column(s) x
contain variable values, column y
the
partial dependence effect and w
the observation counts in
data
. The data frame attribute comment
contains the variable
name, as specified in the var
argument.
if (FALSE) { data('mtpl_be') features <- setdiff(names(mtpl_be), c('id', 'nclaims', 'expo', 'long', 'lat')) set.seed(12345) gbm_fit <- gbm::gbm(as.formula(paste('nclaims ~', paste(features, collapse = ' + '))), distribution = 'poisson', data = mtpl_be, n.trees = 50, interaction.depth = 3, shrinkage = 0.1) gbm_fun <- function(object, newdata) mean(predict(object, newdata, n.trees = object$n.trees, type = 'response')) gbm_fit %>% get_pd(var = 'ageph', grid = 'ageph' %>% get_grid(data = mtpl_be), data = mtpl_be, subsample = 10000, fun = gbm_fun) gbm_fit %>% get_pd(var = 'power_coverage', grid = tidyr::expand_grid('ageph' %>% get_grid(data = mtpl_be), 'coverage' %>% get_grid(data = mtpl_be)), data = mtpl_be, subsample = 10000, fun = gbm_fun) }


Note
Click here to download the full example code
Failed Model Fits¶
Example of model fit failures and how to debug them.
# Import the FOOOFGroup object
from fooof import FOOOFGroup
# Import simulation code to create test power spectra
from fooof.sim.gen import gen_group_power_spectra
# Import FitError, which we will use to help debug model fit errors
from fooof.core.errors import FitError
Model Fit Failures¶
The power spectrum model is not guaranteed to fit - sometimes the fit procedure can fail.
Model fit failures are rare, and they typically only happen on spectra that are particular noisy, and/or are some kind of outlier for which the fitting procedure fails to find a good model solution.
In general, model fit failures should lead to a clean exit, meaning that a failed model fit does not lead to a code error. The failed fit will be encoded in the results as a null model, and the code can continue onwards.
In this example, we will look through what it looks like when model fits fail.
# Simulate some example power spectra to use for the example
freqs, powers = gen_group_power_spectra(25, [1, 50], [1, 1], [10, 0.25, 3],
nlvs=0.1, freq_res=0.25)
# Initialize a FOOOFGroup object, with some desired settings
fg = FOOOFGroup(min_peak_height=0.1, max_n_peaks=6)
# Fit power spectra
fg.fit(freqs, powers)
Out:
Running FOOOFGroup across 25 power spectra.
If there are failed fits, these are stored as null models.
Let’s check if there were any null models, from model failures, in the models
that we have fit so far. To do so, the FOOOFGroup
object has some
attributes that provide information on any null model fits.
These attributes are:
n_null_
: the number of model results that are nullnull_inds_
: the indices of any null model results
# Check for failed model fits
print('Number of Null models : \t', fg.n_null_)
print('Indices of Null models : \t', fg.null_inds_)
Out:
Number of Null models : 0
Indices of Null models : []
Inducing Model Fit Failures¶
So far, we have no model failures (as is typical).
For this example, to induce some model fits, we will use a trick to change the number of iterations the model uses to fit parameters (_maxfev), making it much more likely to fail.
Note that in normal usage, you would likely never want to change the value of _maxfev, and this here is a ‘hack’ of the code in order to induce reproducible failure modes in simulated data.
# Hack the object to induce model failures
fg._maxfev = 50
# Try fitting again
fg.fit(freqs, powers)
Out:
Running FOOOFGroup across 25 power spectra.
Model fitting was unsuccessful.
Model fitting was unsuccessful.
Model fitting was unsuccessful.
Model fitting was unsuccessful.
Model fitting was unsuccessful.
As we can see, there are now some model fit failures! Note that, as above, it will be printed out if there is as model fit failure when in verbose mode.
# Check how many model fit failures we have failed model fits
print('Number of Null models : \t', fg.n_null_)
print('Indices of Null models : \t', fg.null_inds_)
Out:
Number of Null models : 5
Indices of Null models : [3, 15, 17, 18, 19]
Debug Mode¶
There are multiple possible reasons why a model fit failure can occur, or at least multiple possible steps in the algorithm at which the fit failure can occur.
If you have a small number of fit failures, you can likely just exclude them.
However, if you have multiple fit failures, and/or you want to investigate why the model is failing, you can use the debug mode to get a bit more information about where the model is failing.
The debug mode will stop the FOOOF object catching and continuing any model fit errors, allowing you to see where the error is happening, and get more information about where it is failing.
Note that here we will run the fitting in a try / except to catch the error and print it out, without the error actually being raised (for website purposes). If you just want to see the error, you can run the fit call without the try/except.
# Set FOOOFGroup into debug mode
fg.set_debug_mode(True)
# Refit in debug mode, in which failed fits will raise an error
try:
fg.fit(freqs, powers)
except FitError as fooof_error:
print(fooof_error)
Out:
Running FOOOFGroup across 25 power spectra.
Model fitting failed due to not finding parameters in the peak component fit.
Debugging Model Fit Errors¶
This debug mode should indicate in which step the model is failing, which might indicate what aspects of the data to look into, and/or which settings to try and tweak.
Also, all known model fit failures should be caught by the object, and not raise an error (when not in debug mode). If you are finding examples in which the model is failing to fit, and raising an error (outside of debug mode), then this might be an unanticipated issue with the model fit.
If you are unsure about why or how the model is failing to fit, consider opening an issue on the project repository, and we will try to look into what seems to be happening.
Total running time of the script: ( 0 minutes 15.288 seconds)


Reports arrays being passed to print or println and suggests converting them to proper strings
print
println
Example:
var x: Array[Int] print(x)
After the quick-fix is applied:
var x: Array[Int] print(x.mkString("Array(", ", ", ")"))


- Get a good night's sleep before each day! It'll help you focus in class.
- Make sure you are paying attention, a lot of information is given to you in a short amount of time.
- It's okay to have errors, they help you learn from your mistakes and type your code flawlessly the next time.
- Be creative, be yourself, and don't be afraid to ask questions.
- Have fun!
- The teachers and TAs are amazing and supportive people. Ask them questions and for advice on your coding skills and projects you're working on.


Welcome to the 93rd issue of SteemSTEM Distilled, a curation effort by the members of the @steemstem team.
SteemSTEM aims to make Steem a better place for STEM, a task which we believe crucial for the long-term development of the blockchain. Our goals consist in invigorating and inspiring the minds of a community of STEM aficionados on Steem, targeting on the long-term the upgrade of SteemSTEM as a real platform for science communication. In the meantime, this goes through the support of quality, interesting and cutting-edge STEM content and the active development of our app, steemstem.io.
By the way, do not hesitate to set @steemstem as a beneficiary to your post and to use the steemstem.io app. Stronger upvotes (up to 10% more) can be expected. Moreover, feel free to join the SteemSTEM discord server to discuss with us and meet us.
We present in this distilled our top 4 handpicked choices for the last week out about 100 posts weekly supported by the projet (out of several hundreds of STEM-related posts in total that our curators are reading). This week’s distilled highlights were selected once again by @lemouth. Today is party day: four posts were selected instead of 3!
Please do not be discouraged if you did not make it on this issue. The chances to be picked are low. In the meantime, you may wish to check these guidelines for extra tips on how your writing could be more effective.
SteemSTEM proudly supports @tking77798 and his project of designing lab classes in developmental biology (and publishinh them on SteemSTEM). Today, he is not discussing placenta eating at all (yes, this is a thing… apparently…), but how to make use of DNA and a placenta to determine the sex of a child.
If you are not a big fan of playing with blood, maybe is astronomy a better topic four you. @terrylovejoy started to design a series of practical astronomy lessons. Once again, SteemSTEM is proud to fully support this initiative. In the lecture of last week, you will learn how to measure easily (more or less :p) the distance to the moon (without getting there)!
Is the Formosan clouded leopard really extinct. I would say yes, but this is not what everybody thinks. What is your opinion on this topic? if you do not have any, feel free to read this post from @valth in which you will get more information first on the animal itself, and second on the origins of there rumours.
 This holds for smokers of course, but not only. Everyone in the same basket here. And this is the intriguing fact @n4zrizulkafli is after, trying to find some correlations in the numbers.
Statistics are still busy. Water-pony is done and today it is the turn of practicing our strwaberry tasting abitlities. Hopefully, stats will be back next week…
SteemSTEM aims to make Steem a better place for STEM, a task which we believe crucial for the long-term development of the blockchain. Our goals consist in invigorating and inspiring the minds of a community of STEM aficionados on Steem, targeting on the long-term the upgrade of SteemSTEM as a real platform for science communication. In the meantime, this goes through the support of quality, interesting and cutting-edge STEM content and the active development of our app, steemstem.io.
By the way, do not hesitate to set @steemstem as a beneficiary to your post and to use the steemstem.io app. Stronger upvotes (up to 10% more) can be expected. Moreover, feel free to join the SteemSTEM discord server to discuss with us and meet us.
Please do not be discouraged if you did not make it on this issue. The chances to be picked are low. In the meantime, you may wish to check these guidelines for extra tips on how your writing could be more effective.
Monday - Thursday (first half)
Developing a Developmental Biology Lab – Roundabout Sex Determination
Practical Astronomy - Measuring the distance to the moon
Thursday (second half) - Sunday
Could the Formosan clouded leopard (Neofelis nebulosa brachyura) still be extant in the dense jungles of Taiwan?

Statistics
Statistics are still busy. Water-pony is done and today it is the turn of practicing our strwaberry tasting abitlities. Hopefully, stats will be back next week…
All curation rewards earned will be used to fund @steemstem project functioning and activities.
See you all next MonTuesday!
This page is synchronized from the post: SteemSTEM Distilled #93


- I'm injured and broken
- I'm not getting any better
- It's all down hill from here
- I need many pills for my many ills
- I'm unlimited
- My body will heal
- I can improve my health
- My body doesn't need pills, it needs better food, clean water, exercise, and restorative sleep
- Between 60-90% of healthcare visits are related to Mind-Body stress-induced conditions
- Conditions Caused and Exacerbated by Stress:
- Hypertension
- Cardiac Arrhythmias
- Chronic Pain
- Insomnia
- Side Effects of Cancer Therapy
- Side Effects of AIDS Therapy
- Anxiety
- Hostility
- Depression
- Premenstrual Syndrome
- Infertility
- Are you living up to your potential?
- How much of what you are doing wrong with your health is contributing to what you aren't doing right in your life?
- Stress causes deterioration in everything from your gums to your heart and can make you more susceptible to illnesses ranging from the common cold to cancer
- The harmful effects of stress on your health are devastating but they are not inevitable.
- When you perceive a stress in your life or environment, your body releases short term and longer term stress hormones
- Short Term: Epinephrine and Norepinephrine
- Longer Term: Cortisol
- Stress can be helpful, when you are facing short term stressors in the environment
- When Stress is maintained over the long term, there are many negative physical and health effects
- Mobilize & replenish energy
- Help immune cells move to sites where needed
- Promote formation of memories associated with fearful experience
- May increase Growth Hormone levels acutely
- Promote fat deposits, insulin resistance, and cardiovascular disease
- Immunosuppression
- Promote reorganization of nerve cells, cause damage affecting memory and cognition
- Suppression of GH
- The 5 B's of MINDSET Stress Management
- When you feel stress, get physical.
- More physically fit people tend to deal with stress better, which can help them live longer lives.
- The more intense the exercise the more therapeutic it is and the faster it will eradicate your stress.
- Any form of exercise acts as a stress reliever.
- Benefits of Exercise when stressed
- Associated with decreased mortality and morbidity
- Associated with a decrease in anxiety and depression
- Improves cognitive functioning
- Increases levels of circulating dopamine, betaendorphin, and serotonin
- Both exercise and relaxation increase levels of CRH and improve mood
- Breathe
- Control breathing, control your mind
- Your state of mind affects your body and breathing.
- Breathing can change your body and your mind.
- Learn to control your breathing and you learn to control your mind.
- Instead of immediately acting in emotion and anger, pause for a moment. Take a deep breath.
- Then take another.
- And another.
- How you think and how you act can transform how you experience stress.
- When you choose to view your stress response as helpful you create the biology of courage.
- Chasing meaning is better for your health than trying to avoid discomfort. Go after what it is that creates meaning in your life.
- Perceive stress as MANAGEABLE so that you use the stress response only when necessary and for short periods
- Bestow
- Give, care, connect, help others
- When you choose to connect, give, or care for others you create resilience.
- You can treat your stress by spending time helping neighbors, friends, people in your community.
- When you connect and have contact with others, your brain produces a chemical called oxytocin, which counteracts harmful effects of the hormone cortisol
- Schwartz et al, 2003 : 2016 Presbyterian church members in the U.S. Evaluated as to whether altruistic behaviors are correlated with better health. While no association was found for physical health, giving was better correlated with mental health than was being the recipient of help.
- • Brown et al, 2003: 423 older couples over 5 years. An association was found between giving help and reduced risk of dying by half even after controlling for health, age, gender and other factors. No such association was found between receiving help and reduced mortality.
- • Oman et al, 1999 : Volunteer seniors for 2 or more organizations had a 63 percent lower mortality risk than did non-volunteers during the 5-year study period.
- Self awareness enables self regulation
- Breathing - tracking inspiration
- Heart Rate Variability
- Simply paying attention to the present moment can improve your body's cardiovascular health, decrease your stress and strengthen your immune response.
- Increased resilience to anxiety, depression, and even chronic pain, addiction and eating disorders.
- Focus and goal-direct better, allowing you to train your attention and be more productive and less distracted.
- Practice the Relaxation Response
- Discovered by Dr Herbert Benson of Harvard Medical School
- Practicing the Relaxation Response results in a state that decreases metabolism, blood pressure, heart rate, respiratory rate, turns off inflammatory genes, and turns on protective, anti-inflammatory and anti-cancer genes
- The effects of the relaxation response
- turns off your stress response and your sympathetic nervous system, decreasing the inappropriate release of stress neurochemicals and hormones which damage the cells of the body
- Turns on the rational, intelligent parts of your brain, and turns off the emotional, reactive centers of your brain
- Induces Neurogenesis - makes the layers of your brain grow thicker
- turns on protective, anti-inflammatory and anti-cancer genes that support improved regulation of cellular processes, optimizing metabolism, strengthening the immune system and assisting DNA processing
- Some Benefits of the Relaxation Response
- Reduce physiological symptoms
- Diminish anxiety and incapacitating fear
- Reduce pain and the use of pain medications
- Reduce nausea/vomiting side effects of chemotherapy
- Increase feelings of well-being, comfort and control
- Increase procedure safety
- Promote healing and recovery
- How to activate the relaxation response
- The repetition of a word, sound, prayer, thought, phrase or muscular activity
- The passive return to the repetition when other thoughts intrude
- MINDFULNESS (Mind-Body) practices focus on the interactions among the brain, mind, body, and behavior, with the intent to use the mind to affect physical functioning and promote health.
- Mindfulness is a state of active, open attention on the present. When you're mindful, you observe your thoughts and feelings from a distance, without judging them good or bad. Instead of letting your life pass you by, mindfulness means living in the moment and awakening to experience.
- Mindful Eating
- Be MINDFUL of the food you eat and the beverages you drink.
- You don't need sodas, but they are DESIGNED to make you CRAVE them.
- Don't allow the food scientists at Pepsi or any other industrial food producer to control your mind, take your money, and erode your health.
- Stress and Nutrition
- Lowers levels of serotonin, stimulating cravings for sweets and fats
- Decreases the brain's ability to utilize glucose ! Chronic fat intake associated with elevation of cortisol, similar to chronic stress
- Chronic fat intake associated with increased risk of cardiovascular disease and diabetes


I got my BS in Geology at Caltech in 2018. While there, I did research on paleomagnetism with the Kirschvink lab.
Now, I apply those techniques to extraterrestrial samples as a PhD Candidate at Stanford in the Tikoo lab.
My research interests are centered around the Moon: how it solidified from an ocean of magma, how superadiabatic heat flow in the mantle drove a magnetic dynamo, and how impacts throughout the Moon's history have interacted with the magnetic field and the crust.
More about my research projects.


Day 7
Today’s Progress
I have done some algorithm scripting on FreeCodeCamp.
 You want to get to the good stuff, but you need to do the boring stuff first.
After a couple of hours attempting several algorithms, I realise I’m awful at solving them without having to Google for help (partly solutions). I wonder if it’ll ‘click’ or if my brain just doesn’t function that way.
I also need to spend time going over some regex as I have been avoiding it for years; even when I worked as a Linux Sysadmin I couldn’t conjure up the motivation to learn it.
Code Snippets
Title Case A String of Words
function toTitleCase(str) {
return str.replace(/\w\S*/g, function(txt) {
return txt.charAt(0).toUpperCase() + txt.substr(1).toLowerCase();
});
}
toTitleCase('heLLO, DAVE');
// returns: Hello, Dave
Helpful Links
Written on April 27, 2018


2019 Season
Historical Data taken from boardsailor.com/botball
Norcal Regional
- Overall
- 1st place, team 19-0399 with Victor Wang coaching
- 2nd place, team 19-0742 with Victor Wang coaching
- 4th place, team 19-0329 with Pushkar Hingwe coaching
- 5th place, team 19-0338 with Li Liu & Zhimin Ding coaching
- Double Elimination
- 1st place, team 19-0399 with Victor Wang coaching
- 3rd place, team 19-0742 with Victor Wang coaching
- 4th place, team 19-0338 with Li Liu & Zhimin Ding coaching
- Seeding
- 1st place, team 19-0399 with Victor Wang coaching
- 2nd place, team 19-0742 with Victor Wang coaching
- 4th place, team 19-0329 with Pushkar Hingwe coaching
- Outstanding Documentation
- Team 19-0742 with Victor Wang coaching
- Judges Choice Trophies
- Spirit of Botball, team 19-0338 with Li Liu coaching
- KISS Award, team 19-0399 with Victor Wang coaching
- Outstanding Programming, team 19-0636, with Ramu Sunkara coaching
- Outstanding Rookie Team, 19-0338 with Li Liu & Zhimin Ding coaching
- Outstanding Engineering, team 19-0329 with Pushkar Hingwe coaching
- Outstanding use of Sensors, team 19-0329 with Pushkar Hingwe coaching
- Alliance Matches
- 1st place, team 19-0323 with Guangyuan Li coaching
- 1st place, team 19-0329 with Pushkar Hingwe coaching
GCER
- Team 19-0399, Palo Alto, coached by Victor Wang
- World Champion Overall
- Overall Judges Choice Award
- World Champion Double Elimination - undefeated
- 1st place Double Elimination in Curiosity Division
- 1st place Double Seeding
- 2nd place Seeding
- Team 510, Los Altos, coached by Wenshan Liu
- 10th place Overall
- 4th place Double Elimination in Sojourner Division
- 6th place Seeding
- 24th place Double Seeding
- Team 19-636, Los Altos, coached by Ramu Sunkara
- 26th place Overall
- 19th place Seeding
- 31st place Double Seeding
2018 Season
Norcal Regional
- Overall
- 1st place, team 18-0399 with Victor coaching
- 3rd place, team 18-0328 with Li Liu coaching
- Double Elimination
- 1st place, team 18-0399 with Victor coaching
- 3rd place, team 18-0328 with Li Liu coaching
- Seeding
- 1st place, team 18-0399 with Victor coaching
- 3rd place, team 18-0328 with Li Liu coaching
- Outstanding Documentation
- Team 18-0399 with Victor coaching
- Judges Choice Trophies
- Outstanding use of Sensors, team 18-0453 with Warren coaching
- Outstanding Programming, team 18-0328, with Li Liu coaching
GCER
- Team 19-0399, Palo Alto, with Victor Wang coaching
- 3rd Place Overall
- 2nd Place Double Seeding
- 3rd Place Seeding
- Overall Spirit of Botball
- Outstanding Robot Collaboration and Synchronization
- Team 18-0636, Los Altos, with Biswa & Ramu coaching
- 6th Place Seeding
- All attending LACT teams
- Outstanding Outreach


{{ button_text }}
List your potential schedule conflicts, or log in to Google Calendar
If you want to join a group, type the group code here.
Schedule Conflict {{ n }}
final
Submit
Add Conflict


Verify a signature
Did...
... sign ...
Or files?
... with signature ...
... ?
Sign
I am...
... and I'm signing...
Or files?
... with my key ...
Or take it from this file:
... whose passphrase, if not empty, is...
Never leaves your browser! No need to trust; open this page in incognito mode while offline.
... as proven by this URL:


A predicate used while iterating DOM tree. Whose return value affects the flow of iteration.
Counts all immediate element children
Descend the given node (excluding itself) breadth-first. Child nodes of the
current node are pushed to stack before calling the match
predicate.
If match()
returns true
, the loop will break, returning the node at
that point.
Retrieves the first CData child of the given node.
Retrieves the first comment child of the given node.
Retrieves the first element child of the given node.
Retrieves the first processing instruction child of the given node.
Check if the given node is a white space text node
Looks up for something matching certain criteria, falling back to ancestors all the way to the document root. Starting from the given node.
The match
callback should determine whether a given node fulfills criteria.
If match()
returns a value that is not null
or undefined
, the loop will
return immediately, with the return value from match()
.
The node to start looking.
A callback function to determine if the node matches criteria.
Extra arguments to be passed to match
callback.
Looks up for something matching certain criteria, among siblings from
node
onward.
The match
callback should determine whether a given node fulfills criteria.
If match()
returns a value that is not null
or undefined
, the loop will
return immediately, with the return value from match()
.
The node to start looking.
A callback function to determine if the node matches criteria.
Extra arguments to be passed to match
callback.
Looks up for something matching certain criteria.
The next
callback should return the next node of interest. If next()
returns a falsy value, the loop breaks and returns null
.
The match
callback should determine whether a given node fulfills criteria.
If match()
returns a value that is not null
or undefined
, the loop will
return immediately, with the return value from match()
.
The node to start looking.
A callback function to determine if the node matches criteria.
A callback that returns the next node to be matched.
Extra arguments to be passed to match
callback.
Retrieves the next element sibling of the given node.
Remove all empty text nodes from descendants of the given node.
{@link String.trim} all descendants' text nodes.
Generated using TypeDoc
A predicate used while iterating DOM tree. See lookupThrough for more detail.


View 1
Standard Transitions
Slide
Slide (Reverse)
Flip
Fade
View 2
Standard Transitions
Slide
Slide (Reverse)
Flip
Fade
View 3
Standard Transitions
Slide
Slide (Reverse)
Flip
Fade


Something
Something
Something
Tasks
Today
This Week
This Month
07/14
Call Mathew
Matthew Smith
Re:
System Upates
07/14
Call Mathew
Matthew Smith
Re:
System Upates
07/14
Call Mathew
Matthew Smith
Re:
System Upates
07/14
Call Mathew
Matthew Smith
Re:
System Upates
07/14
Call Mathew
Matthew Smith
Re:
System Upates
07/14
Call Mathew
Matthew Smith
Re:
System Upates


Installing and configuring
Edit (pull request)Find here how to install and configure the Cloudify 3 driver.
Download
First step of course is to download the plugin.
- last stable version works with the latest stable alien version.
- last build version works with the latest build alien version.
Install
The driver is packaged as an ALIEN plugin, install it in Administration > Plugins
of your running instance of ALIEN.
Configure
You need to create an orchestrator and configure it.
Creating the orchestrator
- Login as an admin, and create an orchestrator:
Administration > Orchestrators > New Orchestrator
. - As
Plugin
for this orchestrator, make sure to select Cloudify 3 Orchestrator from the list. Validate.
Configuring the orchestrator
On the orchestrator list, select and click on the newly created orchestrator, follow these steps to configure your orchestrator:
-
Connection Configuration: Click on the
Configuration
link to configure connection to your bootstrapped cloudify’s manager. In theDriver configuration
section, change the URL to use the correct IP of your manager that you obtained after the bootstrap operation. If your manager is secured, you can configure the admin credentials, thedisableSslVerification
option should only be set to true for testing purpose, it will disable all certificate validation for SSL.
-
Enable Orchestrator: You can then switch back to the
Information
tab and enable the orchestrator by clicking on theEnable orchestrator
button.
If the orchestrator is not enabled, please check Alien’s log to have details on the error, it might be a bad configuration (bad connection url, bad user/password, invalid certificate etc…) -
Locations: An orchestrator can manage multiple locations, for example, you can have the same orchestrator which manages your local cloud and your public cloud. It is possible for the same deployment to span on multiple locations. For the moment cloudify 3 only supports single location, so we can only have 1 location per cloudify 3 orchestrator. Click on
New Location
, in the popup, enter the name of your location and its type.
-
Configuration Resources: The configuration resources are not real IAAS resources as such. In general they are configurations for other resources. Choose the type of your resource, then click on
Add
to create a new one
In this example, you have a configuration resource of type Image on an OpenStack location, you can describe here the details of the image, such as os type (linux, windows …), distribution(Ubuntu, CentOS …), which must correspond to what you have on your IAAS. The same thing can be done for the types flavor and availability zone. -
On Demand Resources: On demand resources are real IAAS resources that can be used to replace abstract resources in a topology. Click on
Auto-config
to generate on demand resources from precedent configuration resources. As you can see below, with the Image Ubuntu and the Flavor Medium, Alien generated a Compute template Medium_Ubuntu
You can always configure your resources (in this case compute) without using theAuto-config
functionality. To create resources that cannot be auto-configured (such as volume or network or non auto-configured compute etc …), choose the type of the resource, then click onAdd
.
-
Concrete examples of configuration can be found in our various integration tests for Openstack, AWS, BYON
Congratulation!! You’ve finished to configure your cloudify 3 orchestrator. You can now begin to deploy your application with this orchestrator.
Edit (pull request)


{% comment %}
This is probably the worst template in the whole project.
Here, we display the possible actions depending on the user's permissions.
{% endcomment %}
{% endif %}
{% if not latest_revision.is_under_review %}
{% if latest_revision.can_be_reviewed and perms.documents.can_control_document %}
{% url "document_start_review" organisation_slug category_slug document.document_key as start_review_url %}


0ms
<iframe>
context
reported ua
reported ver
restored ua
restored ver
features
platform
canvas
window
contentWindow
nested
window[n]
dead
rejected url
fragment
same origin
Computing...


Red Dead Redemption 2 on its lowest PC settings is a faceless polygonal nightmare
by Emily GeraWhat does Red Dead Redemption 2 look like on its lowest PC setting? Extremely weird.
Rockstar’s cowboy blockbuster is now out on PC, and youtuber LowSpecGamer is doing what they do best – sliding every visual option all the way down to their lowest setting, fiddling with files, and seeing what the hell happens.
The result, as you can see for yourself in the video below, is a nightmarish world of faceless cowboys with hands but no fingers, eyeless horses, and invisible wagons.
Red Dead Redemption 2 launched on PC earlier this month. The PC version comes loaded with a range of enhancements such as resolution support up to 8K, unlocked framerates, an extensive settings menu, a photo mode and several other PC-specific updates, which we previewed when we played it recently.
Games featured in this article


'Mystery Men' (1999)
A movie review by Walter Frith
<EMAIL_ADDRESS>Member of the 'Online Film Critics Society' http://www.ofcs.org
'Mystery Men' has all of the ingredients of a typical 1990's film that looks like an adult comic book layered with special effects. Naturally it's all computerized and has paid advertising seen throughout the film by the corporate states of America. The hero, Captain Amazing (Greg Kinnear) wears his outfit plastered with ads from sponsors and the film's bizarre visuals look in many cases like 'Batman' and 'Blade Runner' on LSD.
Now that you have an idea of how it looks, it's important to tell you how it feels. There are moments of sporadic laughter but the film has clumsy execution and an even clumsier tone. The way the heroes carry out their mission is unconvincing in the face of unspeakable evil and no one would believe for a second that they could overcome their adversaries and save the day for the forces of good.
Mr. Furious (Ben Stiller), the Blue Raja (Hank Azaria), the Bowler (Janeane Garofalo), the Shoveler (William H. Macy), Invisible Boy (Kel Mitchell), the Spleen (Paul Reubens) are a team of wannabe heroes. Some of them have fake accents, some use the tools of mere mortals and in general look like a gang of club members who got together in one afternoon and decided to be crime fighters and went to the nearest garage sale to get their arsenal of weapons. Forks, shovels and other oddities are used and in the opening scene we find they need a lot of work when they try and save a seniors home from a group of invading meanies. The original members of the group are Mr Furious, the Blue Raja and the Shoveler. They are joined later by the Bowler, Invisible Boy and the Spleen. The most intriguing member of the group is the Bowler (Garofolo) who has the skull of her dead father inside her ball and brags effortlessly that "The guy at the pro shop did it for me."
When Captain Amazing is held captive in the evil clutches of Casanova Frankenstein (Geoffrey Rush), the heroes try and save him but have to deal with the goons aiding the chief bad guy. Casanova Frankenstein's plot is to destroy the city that kept him in an insane asylum for many torturous years. With his ego the size a dozen pro athletes, some would argue that Captain Amazing's eventual fate is justice in the making while the amateurs get all the deserving glory.
Director Kinka Usher catapults the film like a guided missile gone awry. I enjoyed some of the antics and the way it made me laugh from time to time but overall I just couldn't find enough to sustain a film with a running length of 121 minutes. Neil Cuthbert is the author of the film's screenplay based on the comic book series Dark Horse created by Bob Burden.
In my review of 1998's 'There's Something About Mary', I criticized the film for going too far in its display of overly crude material and I said that Ben Stiller was rather flat and unfunny. In 'Mystery Men' I found that his performance as the most screwed up hero probably looked good on paper but his execution of it is comparable to the least funny member of the original Three Stooges. The rest of the cast members are very flat and the fact that there are definitely too many of them makes it hard to root for any single one of them.
Throughout the history of film, many have argued that some material just isn't capable of being filmed. Some literature worked better in plain text on paper. Some of it looks better as images in squares known as comic books and while special effects have worked marvelously for many films in the nineties, just as many of them have suffered from overkill and have passed themselves off as flash over substance. 'Mystery Men' may be 1999's ultimate definition of that.
OUT OF 5 > * * *
Visit FILM FOLLOW-UP by Walter Frith http://www.cgocable.net/~wfrith/movies.htm
* * * * * - a must see * * * * 1/2 - don't miss it * * * * - an excellent film * * * 1/2 - a marginal recommendation * * * - can't quite recommend it * * 1/2 - don't recommend it * * - avoid it * 1/2 - avoid it seriously * - avoid it AT ALL COSTS 1/2 - see it at your own risk zero - may be hazardous to your health
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


COM6503 3D Computer Graphics
| Summary |
This module is an introduction to the techniques used in modern 3D computer graphics. It deals with fundamental techniques that are the basis of work in a range of industries, e.g. entertainment and computer-aided design. Both basic and advanced topics concerned with the production of images of abstract 3D objects are covered, including: 3D representations and manipulations in graphics, light reflection models, realism techniques such as shadows and textures, ray tracing and 3D animation. Students should be aware that there are limited places available on this course. |
| Session |
Autumn 2018/19 |
| Credits |
15 |
| Assessment |
Formal examination (2 hours) [40%]
Two assignments: Programming assignment and an individual, focussed study on one topic from the module [60%]. |
| Lecturer(s) |
Dr Steve Maddock |
| Resources |
|
| Aims |
The aims of this module are:
- to provide a comprehensive theoretical and practical
approach to the foundation topics in three-dimensional
computer graphics; and
- to make use of a graphics API (application
programming interface) for the construction of 3D
computer graphics software
|
| Objectives |
By the end of this course the students should:
- be able to use matrices to transform (hierarchical)
objects in 3D coordinate systems;
- be able to describe and apply a 3D viewing pipeline
to display data-structured objects, modelled in a world
of real numbers, on a discrete, raster screen device;
- be able to reason about the most suitable modelling
techniques to use for particular real-world
applications;
- be able to implement standard 3D shading and
rendering techniques using a library of graphics
routines;
- understand and be able to describe and discuss a
range of techniques for increasing the realism of
rendered scenes;
- understand and be able to compare and contrast
advanced rendering techniques;
- be able to describe and discuss a range of computer
animation techniques;
- understand and be able to implement a range of
three-dimensional computer graphics algorithms;
- be able to describe how computer graphics
techniques are used in a variety of application areas, such as in the entertainment industry.
|
| Content |
Coordinate systems and transformations [2
lectures]
Building and Representing Objects [ 3 lectures ]
The graphics pipeline [ 1 lecture ]
Rendering [ 3 lectures ]
- Incremental shading
- Hidden surface removal
- The Z-buffer
- Anti-aliasing
Simulating 3D Reality [ 7 lectures ]
- Simple light object interaction
- Textures and shadows
- Advanced light object interaction
Computer Animation [ 3 lectures ]
Review [1 lecture]
|
| Restrictions |
This module assumes students already have some experience
with vector and matrix arithmetic, as well as previous practical experience in an imperative programing language. |
| Teaching Method |
In addition to the formal lectures, there will be approximately 10 hours of practical sessions related to learning OpenGL, as well as online help with the assignment work. |
| Feedback |
Ongoing during lab sessions, via online help and in office hours;
Final feedback sheet for the assignment |
| Recommended Reading |
- Learn OpenGL (https://learnopengl.com/) by Joey de Vries
- Anton's OpenGL 4 Tutorials (http://antongerdelan.net/opengl)
- Either: D. Shreiner and the Khronos OpenGL ARB Working Group, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Versions 3.0 and 3.1, Addison-Wesley, 7th edition, 2009.
- Or: John Kessenich, Graham Sellers, Dave Shreiner. OpenGL Programming Guide: The Official Guide to Learning OpenGL, Version 4.5 with SPIR-V Paperback (ninth edition), Addison Wesley, 2016
- A H Watt, 3D Computer Graphics (third edition), Addison-Wesley, 2000.
- immersive linear algebra by J. Ström, K. Åström, and T. Akenine-Möller
- F. Dunn and I. Parberry, 3D Math Primer for Graphics and Games Development, 2nd edition, A.K.Peters/CRC Press, 2011.
- Vince, J.A., "Mathematics for Computer Graphics (Undergraduate Topics in Computer Science)", (Fifth edition), Springer, 2017
|
|


{# This file is used as a parent template. If you create a child template by extending this file, please assign values to the following variables and blocks in your file: * variable 'navbar_link' * variable 'language' * block 'title' * block 'head' * block 'content' #} {# Utility #} {% macro nav_link(id, name, icon, link=id) %} {% if navbar_link == id %}


« CSS « CSS Reference
The transition-timing-function
CSS property is used to describe how the intermediate values of the CSS properties being affected by a transition effect are calculated. This in essence lets you establish an acceleration curve, so that the speed of the transition can vary over its duration.
This acceleration curve is defined using one
<timing-function>
for each property to be transitioned.
transition-timing-function
is based on a draft specification and is therefore experimental : the syntax is subject to change.ease
:before
and
:after
pseudo elementsinteractive
-moz-transition-timing-function: <timing-function> [, <timing-function>]*
where:
<timing-function>
represents the timing function to link to the corresponding property to transition, as defined in
transition-property
.There are several examples of CSS transitions included in the main CSS transitions article.
| Browser | Lowest Version |
|---|---|
| Internet Explorer | --- |
| Firefox (Gecko) | 4.0 (2.0) -moz |
| Opera | --- |
| Safari (WebKit) | 3.1 -webkit |


Originally written as a Dangerous Demo for ClueCon 2019 a few months ago: having fun with WebRTC and music!
Press the Start button above to launch the demo.
Start


Flight level to true altitude calculator
QNH
hPa
Elevation of reporting station
m
ft
Outside air temperature (OAT) at FL
°C
Flight level
Estimated true altitude
For demonstration purposes only!


{% block head %} {% endblock %}
Pandemic is not a word to use lightly or carelessly. It is a word that, if misused, can cause unreasonable fear, or unjustified acceptance that the fight is over, leading to unnecessary suffering and death.


Stat of num of repo created per day
Date
Num of repo created
{{ range . }}
{{ .Date }}
{{ .Count }}
{{ end }}


Custom engineering and technical software with an
expertise in RF/Microwave applications.
810 Labs; Software Division develops custom engineering and technical software using the Python programming language. We leverage an array of open source scientific python modules such as scipy, numpy, pandas and others to enable rapid development of scientific applications.
We specialize in RF and Microwave applications. At the heart of our RF and microwave applications is scikit-rf, a BSD licensed python module developed and supported by 810 Labs.


-e doesn't work with globs. Use a for loop.
if [ -e dir/*.mp3 ]
then
echo "There are mp3 files."
fi
for file in dir/*.mp3
do
if [ -e "$file" ]
then
echo "There are mp3 files"
break
fi
done
[ -e file* ]
only works if there's 0 or 1 matches. If there are multiple, it becomes [ -e file1 file2 ]
, and the test fails.
[[ -e file* ]]
doesn't work at all.
Instead, use a for loop to expand the glob and check each result individually.
If you are looking for the existence of a directory, do:
for f in /path/to/your/files*; do
## Check if the glob gets expanded to existing files.
## If not, f here will be exactly the pattern above
## and the exists test will evaluate to false.
[ -e "$f" ] && echo "files do exist" || echo "files do not exist"
## This is all we needed to know, so we can break after the first iteration
break
done
If filename expansion (globbing) is disabled (set -f
), then the [
statement works as expected.


Calculator will display existing average balance for the month as well as average balance to be maintained in the remaining days of the month for not getting a fine.
To use the calculator, please follow the steps given below:
-> Select your account Scheme(1000 RS scheme is default).
-> Select a date(or multiple dates) and Enter the balance amount for that day(s) (end of day balance).
-> Repeat this for all(optional) dates of the month on which transactions have been made.
-> In the account summary, you will be able to see the details of inputs provided by you.


{% extends "base.html" %} {% block title %} All Call {% endblock %} {% block includes %} {% endblock %} {% block body %}
Your request has been uploaded to Tropo, and should begin shortly. Please note, depending on the number of contacts you selected, there may be a slight delay. Thank you!


5 minutes
KVM, QEMU, Libvirt
Introduction
I was looking into virtualization in Linux systems. As we know Linux has arsenal of tools in its back-pocket. It did have something up its sleeve KVM, QEMU, Libvirt. And there a lot of other 3rd party options like VMWare, VirtulBox to name some.
Its interesting that KVM is a kernel module in the Linux system, which helps in getting native-like performance in the virtual machine. So we will be looking into tweaking KVM, QEMU, Libvirt to our convenience and usage.
A tl;dr of Virtualization
-
Well, Virtualization is a technology which lets a user create multiple virtual instances of the same host OS or different one in a single, physical hardware.
-
This means we can create, manage and use multiple operating systems in a single machine.
-
There are many uses of a virtual machine. For Example
- To test an application in a particular environment.
- To experience an operating system before moving to it.
- To improve ones privacy by creating a true Internet sandboxes.
- For Data centers and Service providers:
- Resource efficiency
- Easier management
- Faster provisioning
-
Virtualization is done with the help of Hypervisor. A Hypervisor is a software that creates and runs virtual machine. It connects directly to the hardware and allows a user to split a single system into separate, different environments. It also distributes the resources to the VM and the host appropriately. It can also be called as virtual machine monitor (VMM).
Hypervisor
- There are 2 types of Hypervisors
- Type 1 - Bare Metal hypervisors
- Type 2 - Hosted hypervisors
Type 1 Hypervisor
-
A Type 1 hypervisor directly interacts with the physical hardware’s CPU, memory, and storage.
-
They are mostly used in server-based environments.
-
These type of hypervisors are highly efficient. They provide bare-metal performances.
-
They require a separate management machine to control/administer different VMs and control the host machine.
-
Examples:
- KVM (Kernel-based Virtual Machine)
- Xen
- VMWare ESXi
Type 2 Hypervisor
-
A Type 2 hypervisor runs in an application which runs in an OS.
-
They are mostly used by the individuals running multiple systems in their personal computer.
-
These type of hypervisors enables the use of multiple guest operating systems alongside the host for the end user.
-
They access the resources via host operating system introducing latency, which decreases the performance.
-
The security of these guest machines can be compromised.
-
Examples:
- QEMU
- VirtualBox
- VMWare Player
- VMWare Workstation
Types of Virtualization
-
Desktop virtualization
-
Network virtualization
-
Storage virtualization
-
Data virtualization
-
Application virtualization
-
Data center virtualization
-
CPU virtualization
-
GPU virtualization
-
Linux virtualization
-
Cloud virtualization
We will looking into Linux Virtualization with KVM, QEMU, Libvirt.
KVM
-
KVM stands for Kernel-based Virtual Machine.
-
It is built into the Linux kernel from 2.6.20.
-
KVM make the Linux into a hypervisor, which allows a user to to run multiple virtual machines in the host machine.
-
KVM converts Linux into type-1 hypervisor. Every guest machine hosted on the host machine in Linux with KVM is treated as a regular process.
-
The guest machines uses the standard Linux scheduler built into the kernel with the help of KVM.
-
Rest of the components like network card, graphics adapter, CPUs, memory and storage are virtualized.
-
Features
- As KVM is built in kernel it acquires the scalability and performance.
- As the VM is a Linux process, it can be controlled through the kernel features like cgroups, completely fair scheduler, name spaces, etc.
- It inherits memory management from the kernel, like kernel same-paging, non-uniform memory access.
- It can support different types and hardware.
- KVM uses SELinux (Security Enhanced Linux) and secure virtualization (sVirt) to improve VM’s security.
- Lower latency issues.
QEMU
-
QEMU stands for Quick Emulator.
-
It is an open source machine emulator and virtualizer.
-
With the help of dynamic binary translation it can emulate a different machine’s processor.
-
For example, using QEMU an user can emulate an ARM board in their PC.
-
By using binary translation it achieves good performance.
-
It can use other hypervisors like Xen, KVM to use Hardware-assisted virtualization.
-
Features
- QEMU can save and restore a virtual machine wit all the application running.
- Operating systems need not to be patched for running them in QEMU.
- Can emulate a lot different types of architectures.
- Uses special format for storing the virtual machine qcow or qcow2. This formats only take up as much disk space as the guest OS does.
- Allows the host and guest machine to communicate with integrating services like SMB server.
- Can also support different image formats like
.vdi
,.vmdk
, etc.
Libvirt
-
Libvirt is an Open source API, daemon that provides a way to manage virtual machines.
-
It can be used to manage KVM/QEMU, Xen, LXC, etc.
-
Features
- VM Management
- Remote machine support
- Storage management
- Network interface management
- Virtual NAT and Route based networking
-
There are different user interfaces that use libvirt Virtual Machine Manager, GNOME Boxes, virsh, oVirt, etc.
Differences between QEMU, KVM and Libvirt
-
QEMU and KVM both act as a hypervisor.
-
QEMU runs slower when the system doesn’t have hardware virtualization. To resolve this we use KVM. KVM helps QEMU access the virtualization features on different architectures. KVM also adds acceleration feature to the QEMU process.
-
Libvirt is a simple virtualization library. It is used to manage KVM and QEMU. It is effective and can handle a lot of hypervisors together. It consists of three utilities: API library, a daemon (libvirtd) and a command line tool (virsh).
-
So in-short:
- QEMU - Hypervisor
- KVM - Accelerating agent
- Libvirt - A Management library
Continued
In the next post, we will be looking into virt-install to create VM and virsh to manage them.


menu
Who
Work
Contact
Who
Work
Contact
All the fun things I've made for the internet
.
For Someone Else
Kissalyss
Beauty Salon
For Myself
"Baseball Cards" For Music
JavaScript Focus
Star Wars API
JSON & API


Locker for A
2 A
Locker for B
2 B
Its A's turn
ROLL!
1
2
3
4
5
6
Would You Like To Play Again?
Play Again


DeCE processes given commands one-line by one-line. Each line contains an operation keyword first, then some optional letters or numbers follow depending on the operation.
DeCE ignores blank lines. "#" can be used for a comment line.
The operation keywords are case-insensitive. DeCE recognizes the following keywords.
These operations fall into the following categories.
When DeCE detects an operation that DeCE cannot understand, the code stops immediately. This is because ENDF-6 formatting process should be so careful that any errors in the input data must be eliminated.
The simplest usage of DeCE is just to renumber the ENDF-6 formatted file. No command other than quit is needed. However, the option -o has to be specified.
% dece ENDF_in.DAT -o ENDF_out.DAT % quit
DeCE reads the entire ENDF_in.DAT file, then calculates NWDand NXC (number of lines in the comment and dictionary part), make a new dictionary, renumber all the section, and write the result on the file ENDF_out.DAT.
In this case, the file ENDF_in.DAT can be incomplete, which means, the NWDand NXC numbers and the dictionary can be inconsistent with the actual numbers. DeCE does not trust those data in the input ENDF-6 file, but scans the whole file to determine the correct values.
Note that the line-number in DeCE starts with one, not zero.
To modify a Tape ID, use the tpid operation. It might be convenient to use a separate data file in this case. When an input file contains the following two lines;
tpid "As 75 ENDF/B-VII.0 + CoH3 calculation" quit
% dece ENDF_in.DAT -o ENDF_out.DAT < input.dat
then the top part of the output ENDF-6 file becomes
As 75 ENDF/B-VII.0 + CoH3 calculation 0 0 0 3.307500+4 7.427800+1 1 0 0 03325 1451 1 0.000000+0 0.000000+0 0 0 0 63325 1451 2 1.000000+0 2.000000+7 0 0 10 73325 1451 3 0.000000+0 0.000000+0 0 0<PHONE_NUMBER> 1451 4
A useful function of DeCE is to extract a section in an ENDF-6 file, and convert it into a table format. There are two ways to do this. The first one is to give a MF and MT numbers as command line options.
Another way is to use the extract or table operation. Here we have a file that contains three lines:
extract 3 22 table 3 22 quit
then feed this file to DeCE, one gets;
% dece ENDF_in.DAT < input.dat
3.307400+4 7.328890+1 0 0 0 03322 3 22 1 -4.380000+6-4.380000+6 0 0 1 143322 3 22 2 14 2 3322 3 22 3 4.439760+6 0.000000+0 7.000000+6 0.000000+0 8.000000+6 2.722850-93322 3 22 4 9.000000+6 2.148920-8 1.000000+7 2.998550-6 1.100000+7 5.546240-53322 3 22 5 1.200000+7 4.000550-4 1.300000+7 2.103910-3 1.400000+7 6.563180-33322 3 22 6 1.500000+7 1.435070-2 1.600000+7 2.380840-2 1.800000+7 4.308410-23322 3 22 7 1.900000+7 5.158810-2 2.000000+7 5.909400-2 3322 3 22 8 3322 3 099999 # MAT: 3322 MF: 3 MT: 22 ZA: 33 - 74 # NR: 1 C1: -4.380000e+06 C2: -4.380000e+06 # IR: 1 NP: 14 INT: lin-lin 4.439760e+06 0.000000e+00 7.000000e+06 0.000000e+00 8.000000e+06 2.722850e-09 9.000000e+06 2.148920e-08 1.000000e+07 2.998550e-06 1.100000e+07 5.546240e-05 1.200000e+07 4.000550e-04 1.300000e+07 2.103910e-03 1.400000e+07 6.563180e-03 1.500000e+07 1.435070e-02 1.600000e+07 2.380840e-02 1.800000e+07 4.308410e-02 1.900000e+07 5.158810e-02 2.000000e+07 5.909400e-02
The first block is a dead-copy of the section MF=3, MT=22, and the next block, starting with # MAT line, is the result of table operation, where the (X,Y) data are converted into two column table.
An important rule of ENDF-6 is that the total cross section should equal to the sum of all partial cross sections. This is often satisfied by subtracting the sum of of partial cross sections from the total cross section. This can be done very easily with DeCE.
make4 calc 3 = 4+16 calc 3 = 3+22 calc 3 = 3+28 calc 3 = 3+32 calc 3 = 3+102 calc 3 = 3+103 calc 3 = 3+104 calc 3 = 3+105 calc 3 = 3+106 calc 3 = 3+107 calc 3 = 3+111 calc 3 = 3+112 calc 2 = 1-3 calc 1 = 2+3 delete 3 3 quit
% dece ENDF_in.DAT -o ENDF_out.DAT < input.dat
The first line of the input data, make4 is to make recalculate MF/MT=3/4, which is the total inelastic scattering cross section. Usually this section is already given, so that this is not needed. The following calc operations make a temporary section MF/MT=3/3 that contains the sum of partial cross sections.
We first make the elastic scattering MT=2 by subtracting MT=3 from the total (calc 2 = 1 -3), then the total is reconstructed again (calc 1 = 2 + 3), which can make sure that the MT=1 section includes all the energy points appeared in the whole ENDF-6 file.
The original ENDF_in.DAT may have the MT=2 section too. If you want to see how much the new elastic cross sections are changed from the original data, you can take a ratio of the old section to the recalculated section.
make4 calc 3 = 4+16 calc 3 = 3+22 ...(snip)... calc 3 = 3+112 calc 4 = 1-3 calc 5 = 2/4 extract 3 5 quit
2.305100+4 5.050630+1 0 0 0 02328 3 5 1 0.000000+0 0.000000+0 0 0 1 117512328 3 5 2 11751 2 2328 3 5 3 1.000000-5 0.000000+0 2.530000-2 0.000000+0 1.000000+5 0.000000+02328 3 5 4 1.000000+5 1.000000+0 1.001200+5 1.000000+0 1.002900+5 1.000000+02328 3 5 5 1.004700+5 1.000001+0 1.006400+5 1.000002+0 1.008100+5 1.000002+02328 3 5 6 1.009900+5 1.000002+0 1.011600+5 1.000003+0 1.013400+5 1.000002+02328 3 5 7 1.015100+5 1.000004+0 1.016900+5 1.000002+0 1.018700+5 1.000004+02328 3 5 8 1.020400+5 1.000003+0 1.022200+5 1.000004+0 1.024000+5 1.000005+02328 3 5 9 1.025700+5 1.000005+0 1.027500+5 1.000006+0 1.029300+5 1.000006+02328 3 5 10 ...(snip)...
There are tiny differences at the last digit (10-6), which could be just a numerical noise.


|
Bitstream Interpretation Library (BIL)
0.1
|
Contains definition of CfgDecoder class. More...
#include <cfgdecode/CfgDecoder.hpp>
Go to the source code of this file.
Contains definition of CfgDecoder class.
Definition in file CfgDecoder.cpp.


Welcome to my first website built from the ground up on my blood, sweat, and tears. Just kidding. Or am I? Anyways, here is where I blog about my experience at Dev Bootcamp, both the technical and cultural side of the journey; post my explanations of programming concepts and jargon for fellow DBCers, coding newbs, and the curious laymen; share awesome tech articles and resources, and one day showcase my projects. Enjoy it while it's still in its marvelous alpha-stage glory.
- Caitlyn


Do you need a new or updated website? We offer custom and affordable website design and hosting, allowing you to focus on what you do best.
Custom and affordable software/apps built specifically to solve your small business needs.
We automate and visualize your data reports so you are able to make quick and informed decisions. Direct your company into a prosperous future.
Full Stack Web and Mobile Developer | Dev Ops
Full Stack Web Developer | Data Science
Business Developer | Electrical Wizard
Graphic/Web Designer
Web Designer | Front-end developer
Business Coordinator | Social Media Marketing
Loved working with the Ideal Enigma team! Friendly and approachable. Created an outstanding product for my business. I couldn't believe how affordable it was.
We want to hear about the problems you face as a small business, then build tools to solve them. You are an expert at your business and we want to hear about it. Consulations and quotes are always free!
After our intial meeting we will develop some potiential solutions within your budget, along with timelines and other options. Once you choose a solution, build phase begins!
Development is broken into smaller phases, where you will be able to give feedback and direction to the development of your new product. Towards the end there will be a big review and trial phase, where we will adjust and perfect the product before the launch!
Time to celebrate!


---
layout: archive
nav-type: blog
title: CAF Developer Blog
---
Blog Archive
{% for post in site.posts %}
{% capture post_year2 %}{{ post.date | date: '%Y' }}{% endcapture %}
{% if post_year1 != post_year2 %}
{% assign post_year1 = post_year2 %}
{{ post_year1 }}


Peanut
:
Documentation
: {title}
{summary}
{body}
Copyright © 2011
Purple Dogfish
. Running on
Peanut
(of course)
. Memory usage {memory_usage}.


---
layout: post
title: Adaptive search only in Firefox OS
date: 2014-08-28 00:00:00.000000000 +05:30
type: post
published: true
status: publish
categories:
- Firefox
- Firefox OS
- Firefox OS Apps
tags: []
meta:
blogger_blog: www.technoruler.com
blogger_author: VISWAPRASATH KS
blogger_cb097c283b9bbfde97b4822e7250157d_permalink: '9123811851403593612'
author:
login: viswaprasath
email<EMAIL_ADDRESS>display_name: Vitchu
first_name: ''
last_name: ''
---
Searching the contents is one of the biggest thing we do every day. We need to know lot of information every time. We spend lot of working in searching some thing, many times what we search many not be displayed properly by some Search engine.
|
| Adaptive search in Firefox OS |
We might have got the result, but have to save it and access it quickly (bookmark it) from our mobile, but these features are available only in browser till now. We were not able to create a shortcut in our home screen.
To make user experience easier and help users to access information easily Firefox have a search by default. This is called as Adaptive searching. Mozilla partnered with Everything.me to achieve this.
Here we just need to
- Type a word or subject you’re interested in
- Find exactly what you want — and more
- Get instant access or save apps to your phone
- Discover more web apps
How to use Adaptive Search
When you goto Home screen of Firefox OS, you can see I'm thinking of... click on that text area.
Type a word which you love and leave it. (Eg:- Sachin Tendulkar)
You will get lot of web applications related to your query.
|
Adaptive search in Firefox OS searching Sachin Tendulakar |
One of the most interesting thing is the background of the screen will be changed according to your query. If you have searched for Sachin Tendulkar, the famous cricketer face will be coming as background.
To bookmark and reuse
To bookmark our query which we have used we just need to click on the star icon, it will change its colorless to yellow color star. An icon will be created in screen and whenever needed we can easily click the icon and access the variety of information available.
|
Adaptive search in Firefox OS bookmark which can be used for accessing faster |


Protein diagrams with pfam domains
BTB domain containing protein examples
Protocadherin protein examples
Large protein example


Show all orders
Collapse Order List
Enter email
Enter coffee type
Order
Enter email to delete order
Delete Order
Enter email to get order
Get Order by Email


NMBLOOKUP
Section: User Commands (1)Updated: 06/14/2011
Index Return to Main Contents
NAME
nmblookup - NetBIOS over TCP/IP client used to lookup NetBIOS namesSYNOPSIS
- nmblookup [-M] [-R] [-S] [-r] [-A] [-h] [-B <broadcast address>] [-U <unicast address>] [-d <debug level>] [-s <smb config file>] [-i <NetBIOS scope>] [-T] [-f] {name}
DESCRIPTION
This tool is part of the samba(7) suite.
nmblookup is used to query NetBIOS names and map them to IP addresses in a network using NetBIOS over TCP/IP queries. The options allow the name queries to be directed at a particular IP broadcast area or to a particular machine. All queries are done over UDP.
OPTIONS
-M
- Searches for a master browser by looking up the NetBIOS name name with a type of 0x1d. If name is "-" then it does a lookup on the special name __MSBROWSE__. Please note that in order to use the name "-", you need to make sure "-" isn't parsed as an argument, e.g. use : nmblookup -M -- -.
-R
- Set the recursion desired bit in the packet to do a recursive lookup. This is used when sending a name query to a machine running a WINS server and the user wishes to query the names in the WINS server. If this bit is unset the normal (broadcast responding) NetBIOS processing code on a machine is used instead. See RFC1001, RFC1002 for details.
-S
- Once the name query has returned an IP address then do a node status query as well. A node status query returns the NetBIOS names registered by a host.
-r
- Try and bind to UDP port 137 to send and receive UDP datagrams. The reason for this option is a bug in Windows 95 where it ignores the source port of the requesting packet and only replies to UDP port 137. Unfortunately, on most UNIX systems root privilege is needed to bind to this port, and in addition, if the nmbd(8) daemon is running on this machine it also binds to this port.
-A
- Interpret name as an IP Address and do a node status query on this address.
-n|--netbiosname <primary NetBIOS name>
- This option allows you to override the NetBIOS name that Samba uses for itself. This is identical to setting the m[blue]smb.conf.5.html#m[] parameter in the smb.conf file. However, a command line setting will take precedence over settings in smb.conf.
-i|--scope <scope>
- This specifies a NetBIOS scope that nmblookup will use to communicate with when generating NetBIOS names. For details on the use of NetBIOS scopes, see rfc1001.txt and rfc1002.txt. NetBIOS scopes are very rarely used, only set this parameter if you are the system administrator in charge of all the NetBIOS systems you communicate with.
-W|--workgroup=domain
- Set the SMB domain of the username. This overrides the default domain which is the domain defined in smb.conf. If the domain specified is the same as the servers NetBIOS name, it causes the client to log on using the servers local SAM (as opposed to the Domain SAM).
-O|--socket-options socket options
- TCP socket options to set on the client socket. See the socket options parameter in the smb.conf manual page for the list of valid options.
-h|--help
- Print a summary of command line options.
-B <broadcast address>
- Send the query to the given broadcast address. Without this option the default behavior of nmblookup is to send the query to the broadcast address of the network interfaces as either auto-detected or defined in the interfaces parameter of the smb.conf(5) file.
-U <unicast address>
- Do a unicast query to the specified address or host unicast address. This option (along with the -R option) is needed to query a WINS server.
-d|--debuglevel=level
-
level
is an integer from 0 to 10. The default value if this parameter is not specified is 0.
The higher this value, the more detail will be logged to the log files about the activities of the server. At level 0, only critical errors and serious warnings will be logged. Level 1 is a reasonable level for day-to-day running - it generates a small amount of information about operations carried out.
Levels above 1 will generate considerable amounts of log data, and should only be used when investigating a problem. Levels above 3 are designed for use only by developers and generate HUGE amounts of log data, most of which is extremely cryptic.
Note that specifying this parameter here will override the m[blue]smb.conf.5.html#m[] parameter in the smb.conf file.
-V|--version
- Prints the program version number.
-s|--configfile <configuration file>
- The file specified contains the configuration details required by the server. The information in this file includes server-specific information such as what printcap file to use, as well as descriptions of all the services that the server is to provide. See smb.conf for more information. The default configuration file name is determined at compile time.
-l|--log-basename=logdirectory
- Base directory name for log/debug files. The extension ".progname" will be appended (e.g. log.smbclient, log.smbd, etc...). The log file is never removed by the client.
-T
-
This causes any IP addresses found in the lookup to be looked up via a reverse DNS lookup into a DNS name, and printed out before each
IP address .... NetBIOS name
pair that is the normal output.
-f
- Show which flags apply to the name that has been looked up. Possible answers are zero or more of: Response, Authoritative, Truncated, Recursion_Desired, Recursion_Available, Broadcast.
name
- This is the NetBIOS name being queried. Depending upon the previous options this may be a NetBIOS name or IP address. If a NetBIOS name then the different name types may be specified by appending '#<type>' to the name. This name may also be '*', which will return all registered names within a broadcast area.
EXAMPLES
nmblookup can be used to query a WINS server (in the same way nslookup is used to query DNS servers). To query a WINS server, nmblookup must be called like this:
nmblookup -U server -R 'name'
For example, running :
nmblookup -U samba.org -R 'IRIX#1B'
would query the WINS server samba.org for the domain master browser (1B name type) for the IRIX workgroup.
VERSION
This man page is correct for version 3 of the Samba suite.
SEE ALSO
nmbd(8), samba(7), and smb.conf(5).
AUTHOR
The original Samba software and related utilities were created by Andrew Tridgell. Samba is now developed by the Samba Team as an Open Source project similar to the way the Linux kernel is developed.
The original Samba man pages were written by Karl Auer. The man page sources were converted to YODL format (another excellent piece of Open Source software, available at ftp://ftp.icce.rug.nl/pub/unix/) and updated for the Samba 2.0 release by Jeremy Allison. The conversion to DocBook for Samba 2.2 was done by Gerald Carter. The conversion to DocBook XML 4.2 for Samba 3.0 was done by Alexander Bokovoy.
Index
This document was created by man2html, using the manual pages.
Time: 05:29:06 GMT, December 24, 2015