Camera Design – In-Body Neutral Density Filter (ND Filter)?

Just a guess, but I do not think ND filters are as prevalent as you suspect. A very large proportion of the users of a particular camera will never need an ND filter and therefore will not be interested in paying the extra cost of adding the filter to the camera.

An embedded ND filter would also have to be variable, otherwise it can not replace all potentially required densities. ND filters are available in many densities, and fixed density filters are much easier to manufacture than variable density filters. Variable density filters are typically made by combining multiple polarizing filters, are difficult to build (expensive to read), and may have optical disadvantages compared to fixed density filters.

What is the filter thread size for a Hasselblad 80mm lens?

To do this, answer @JindraLacko

In fact, there are two ways to put filters on the 80mm Hasselblad lenses (as well as all other Blad lenses). The Bay 50 or Bay 60 sockets are the sizes for the internal C / C T * or later CF lenses. The lenses also have the option to mount a bellows-type external lens hood that can accommodate gel filters in various sizes. In this way, you can effectively install all kinds of translucent plastic filters in front of the lens.

For completeness, the Hasselblad has no thread size per say as the bay system is short for bayonet. The filters are held over a single notch engaged with less than a quarter turn.

The exception to the above answer is the 50mm lens which houses the Series 8 filter and requires an included mounting ring.

PHP – Goutte Scraper filter with table attribute

I try to scrap a website with Goutte. But I can not filter with attributes like

(@width="100")(@cellspacing = "1")(@border = "0")

In my page have several table.

Now I want to scrape tables with (@ width = "100") (@ cellspacing = "1") (@ border = "0").

Look at table html

I'm trying to use this code, but I'm not getting any output

$table = $crawler->filter('table')->attr('width=100','cellspacing=1','border=0')->each(function ($tr)  {
    return $tr->filter('td')->each(function ($td, $i) {
        return trim($td->text());

Filter Optimization Problem – MathOverflow

Let me first give you some background information. I am developing embedded software and have a filtering problem where I could use the help of mathematicians.

I have a filter table with the following functions:

  • possible 100 entries
  • 50 entries support exact match filtering
  • 50 entries support range matching filtering

Because it is embedded software, the area filtering is done in bits. That means I can filter in areas in base 2. This part can not be changed.
For example:

  • Numbers from 0-1 (1 bit)
  • Numbers from 0-3 (2 bits)
  • Numbers from 0-7 (3 bits)
  • Numbers from 0-15 (4 bits)

Now comes the problem I have. If I assume that I have random numbers, what would be the best way to arrange them?

In fact, we're talking about 32-bit numbers, but for the sake of simplicity, we're focusing on numbers up to 1000.

An example would be if I have the numbers 1, 5, 565. One solution would be to add these to exact filters since I only have 3 of them.

Another example is that I have the number 0,1,2,9,565. I can add them all to exact filters.
Another approach is to add 0.1.2 to the range filter and only after checking that I have not received a "false" positive (number 3). The rest can go to exact filters.

As you can see, the problems are not trivial as we move to higher numbers. I want to define a cost function for myself, but I do not know how to set it up properly.

The most important parameter is that all numbers are in the filter.
The second is that I use the maximum number of exact filters.
The third is that I have range filters where I have to have as little overhead as possible after the filter says I have a match.

The reason for these "weights" is that this part is performance critical. It is done often and after this step I want to have the smallest possible number of steps to determine if the number was in the filters or not.

Views filter on Boolean with NULL value (not set)

The client wants to hide some published content in certain views.

Unpublishing content is not an option. it has to remain accessible.

I added a Boolean value exclude_from_view Field on multiple content types.

I intended to add a Boolean filter to exclude content from the required ads if the value of this field was TRUEbut I was surprised that Views did not give any results at all. Setting the Boolean filter No NOT FALSE had the same result.

This happens because the field has no default value added to the existing content, so the field is returned NULLThat is not one TRUE Yet FALSE, (In PHP NULL is a "wrong" value, but apparently not for views.)

A small investigation shows that many other people have complained about this problem.

Some of them believe that boolean fields that are not set for entities should be considered FALSENot NULL,

Others want that NULL Fields could be treated as TRUE,

Still others believe that the user interface of Views should provide filtering options for Treat NULL as FALSE"or" Treat NULL as TRUE, "(This is a cool idea, but it requires a patch core that I'm not necessarily against, if that's the best way.)

What should I do?

How do I filter and count lodash.groupby in a typoscript array?

I want the statistics data from echartsjs with & # 39; center & # 39; Show.
Demo is: Enter the link description here

For example
I have an array,
T has some features, such as start time, end time and more …

class T{
  public start: string;
  public end: string;

I use lodash.groupBy get a dictionary,

const groups = groupBy(data, function (item) { 
      return Math.abs(moment(item.end, 'YYYY-MM-DD').diff(moment(item.start.From, 'YYYY-MM-DD'), 'days'));

I will build an xaxis array

 private  buildDateRangeXdata(): Array{
    let xdata = Array();
    return xdata;

I do not know how to find the data in xaxis compliant groups.
how can i do it?

postgresql – Postgres with seq scan with filter for indexed column + EXISTS for associated table

I have the following query, which takes about 25-35 seconds to execute:

EXPLAIN (analyze, buffers, format text) SELECT booking.*
FROM booking
WHERE booking.reference_number = '9999999999' OR booking.booking_id = '9999999999' OR 
        EXISTS (
            SELECT * FROM booking_customer 
            WHERE booking_customer.booking_id = booking.booking_id AND 
                ( = '9999999999' OR = '9999999999') AND 
                booking_customer.deleted = false

The EXPLAIN issue can be found here:

As you can see from the chart, the bookings table is searched one after another, even though filtered by indexed columns. reference_number and booking_id, The booking_customer However, the table uses the index scan correctly.

Does it have something to do with it? EXISTS or OR there clauses?

My table structure is as follows:

                              Table ""
        Column         |           Type           | Collation | Nullable | Default
 deleted               | boolean                  |           |          |
 booking_id            | character varying        |           | not null |
 reference_number      | character varying        |           |          |
 booking_owner         | character varying        |           |          |
 checkin_date          | timestamp with time zone |           |          |
 checkout_date         | timestamp with time zone |           |          |
 status                | character varying        |           |          |
 hold_till             | timestamp with time zone |           |          |
 version               | integer                  |           | not null |
 comments              | text                     |           |          |
 extra_information     | json                     |           |          |
 cancellation_reason   | character varying        |           |          |
 cancellation_datetime | timestamp with time zone |           |          |
 created_at            | timestamp with time zone |           | not null | now()
 modified_at           | timestamp with time zone |           | not null | now()
    "booking_pkey" PRIMARY KEY, btree (booking_id)
    "ix_booking_reference_number" UNIQUE, btree (reference_number)
    "idx_booking_checkin_date" btree (checkin_date)
    "idx_booking_checkout_date" btree (checkout_date)
    "ix_booking_status" btree (status)
    "trgm_booking_ref_num" gist (reference_number gist_trgm_ops)

And customer table:

                          Table "public.booking_customer"
        Column         |           Type           | Collation | Nullable | Default
 deleted               | boolean                  |           |          |
 customer_id           | character varying        |           | not null |
 booking_id            | character varying        |           | not null |
 first_name            | character varying        |           |          |
 last_name             | character varying        |           |          |
 gender                | character varying        |           |          |
 age                   | integer                  |           |          |
 nationality           | character varying        |           |          |
 phone                 | character varying        |           |          |
 email                 | character varying        |           |          |
 gst_addr_field1       | character varying        |           |          |
 gst_addr_field2       | character varying        |           |          |
 gst_addr_city         | character varying        |           |          |
 gst_addr_state        | character varying        |           |          |
 gst_addr_country      | character varying        |           |          |
 gst_pincode           | character varying        |           |          |
 legal_name            | character varying        |           |          |
 created_at            | timestamp with time zone |           | not null | now()
 modified_at           | timestamp with time zone |           | not null | now()
    "booking_customer_pkey" PRIMARY KEY, btree (customer_id, booking_id)
    "book_cust_idx" btree (booking_id, customer_id)
    "ix_booking_customer_email" btree (email)
    "ix_booking_customer_phone" btree (phone)
    "trgm_cust_last_name" gist (last_name gist_trgm_ops)

Details about the total records in the table are as follows:

db=> SELECT COUNT(*) FROM booking;
(1 row)

db=> SELECT COUNT(*) FROM booking_customer;
(1 row)

db=> SELECT COUNT(*) FROM booking WHERE reference_number = '9999999999' OR booking_id = '9999999999';
(1 row)

db=> SELECT COUNT(*) FROM booking_customer WHERE (email = '9999999999' OR phone = '9999999999') AND deleted = false;
(1 row)

db=> SELECT COUNT(DISTINCT(booking_id)) FROM booking_customer WHERE (email = '9999999999' OR phone = '9999999999') AND deleted = false;
(1 row)

So ideally I should have gotten 65196 Rows as a result, which may be a good reason to use sequence scan. However, the planner returns only 14 lines as an estimate. That's funny, considering that yesterday at midnight, I did vacuum analysis on both tables.

Even if I try with a different value for phone or email, giving about 1300 lines, the seq scan is still used for the booking table.

Is there a way to optimize this query?

Postgres details:

db=> SELECT version();
 PostgreSQL 9.6.12 on x86_64-pc-linux-gnu, compiled by gcc (GCC) 4.9.3, 64-bit
(1 row)

Control Systems – Problem Solving the Kalman Filter in Mathematica: How to Define a Spectral Density Matrix and Calculate the Covariance Matrix?

I read the classic book on the theory of space control by Bernard Friedland.

To deepen my understanding of the Kalman filter, I would like to illustrate Example 11A Inverted Pendulum on page 418.

However, I can not find a way to define the spectral density matrices (of excitation noise and observation in equation (11A.2)) in Mathematica. How can I also calculate the covariance matrix of noise from a spectral density matrix?

Thank you very much.

Example 11A

Taxonomy – Looking for a plug-in that can filter my custom post type with dependent dropdowns

I want to have 2 dropdowns on my page and I want the first dropdown categories and the second subcategories. I want the subcategories to be populated as a category based on your selection. And then it should filter my custom post type.

Currently I'm trying a taxonomy and have a parent-child relationship. I've tried using Toolset, but I'm stuck and it does not seem to be possible with Toolset.

What would be the best approach for that? This is my first paid WordPress project and I have some time, so all the tips are more than welcome! I would prefer a plugin that does it visually.

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