Lovely Cat stocks something useful!

%Define Cartesian Coordinates

radiusSZ = floor(imSize/2);

[X, Y] = meshgrid(-radiusSZ:radiusSZ, -radiusSZ:radiusSZ);

[theta, rho] = cart2pol(X, Y);

rho = round(rho);

%2d sinc function

sincFrq = 1;

sincFilter= sin(rho*sincFrq+0.00001)./(rho*sincFrq+0.00001);

sincFilter_clamped = sincFilter; %init

%If you want to clamp the kernel,

clampDist = 4; %variable

cen = ceil(imSize/2); %variable

sincFilter_clamped = sincFilter_clamped(cen-clampDist:cen+clampDist,cen-clampDist:cen+clampDist);

https://fgiesen.wordpress.com/2011/09/06/a-trip-through-the-graphics-pipeline-2011-part-12/

 Likert developed the principle of measuring attitudes by asking people to respond to a series of statements about a topic, in terms of the extent to which they agree with them, and so tapping into the cognitive and affective components of attitudes. A Likert scale assumes that the strength/intensity of experience is linear, i.e. on a continuum from strongly agree to strongly disagree, and makes the assumption that attitudes can be measured. 

 A scale can be created as the simple sum of questionnaire responses over the full range of the scale. In so doing, following characteristics should be considered. 

 - Symmetry: They contain equal numbers of positive and negative positions whose respective distances apart are bilaterally symmetric about the "neutral" value

- Balance: The distance between each candidate value is the same, allowing for quantitative comparisons such as averaging to be valid across items containing more than two candidate values. The format of a typical five-level Likert item could be

   strongly disagree / disagree / neutral / agree / strongly agree

Likert scaling is a bipolar scaling method, measuring either positive or negative response to a statement. Sometimes an even-point scale is used, where the middle option of "neutral" is not available. This is sometimes called a "forced choice" method, since the neutral option is removed. 

 In illustration, the diverging stacked bar charts is highly recommended [Plotting Likert and Other Rating Scales - 2011]. Diverging stacked bar charts make it easier to compare the attitudes of respondents in different demographic categories or who differ on the importance of increasing professional recognition than do any other figures discussed. 

Two-alternative forced choice

  The two-alternative forced choice (2AFC) method is a ubiquitous choice for measuring detection or discrimination thresholds. During one trial of a 2AFC experiment, a subject is asked to make a decision about two stimuli with regard to a particular stimulus parameter of interest (it is also called primary parameter). For example, a subject is instructed to indicate which one of two terrain images shows an more realistic scenes. See following figures.

Figure 1. Two terrain images. Left terrain data is 1/64 down-sampled version of right terrain data. 

 Over repeated trials with stimulus pairs of varying difference in sample rates, a psychometric function can be calculated that reflects the empirical probability of the subject's choice as a function of stimulus difference. The slope of this sigmoidal function is a direct measure of the subject's discrimination threshold. There are many benefits in using the 2AFC method. It requires subjects to perform a simple decision task. It provides a threshold measure in physical units unlike scaling methods. Also, by restricting a subject’s response to a binary decision, it avoids any contamination of the measured perceptual thresholds with motor noise unlike methods of adjustment. Furthermore, it generally provides a large number of data points, thus allowing a statistically sound analysis and robust fits of the data. Finally, with signal detection theory (SDT), there exists a well-accepted and simple observer model framework that links the psychometric functions to an internal sensory representation of the stimulus parameter of interest. For all these reasons, the 2AFC method has been popular in many areas. 

  It is possible to introduce biases in decision making in the 2AFC task. For example, if one stimulus occurs more frequently than the other, then the frequency of exposure to the stimuli may influence the participant's beliefs about the probability of the occurrence of the alternatives. 

In order to solve this problem, I've tried so many things :(

I hope this post help you to save your time.

- Just downgrade your gdal version. 

In my case, every solutions I tried including altering the 32bit to 64bit and changing the python version, 

presented by anonymous user, have not been effective. 

The problem has been solved when I change the gdal version 2.1.0 to 2.0.3

good luck :)

(* Now, my python version is 3.4.4 and gdal version is 2.0.3.)

The first step is to set up the environment. 

Following sites provide kind instruction what you have to do. 

http://cartometric.com/blog/2011/10/17/install-gdal-on-windows/

https://pythongisandstuff.wordpress.com/2011/07/07/installing-gdal-and-ogr-for-python-on-windows/

These sites are helpful

http://www.gisinternals.com/release.php 

* download site

------------------------------------------------------------

* Make sure the environment is established properly. 

The next step is to install the 'ptvs' which helps you to use python into the visual studio. (In my case, the version is  visual studio 2013)

Enter a keyword either 'python for visual studio' or 'ptvs'. 

Then you can find certain website to help you :)

Choose the correct version of ptvs and install it. 

Make new project and enter the following code.

"from osgeo import gdal"

If it works, you are ready to use gdal on visual studio. 

Unless, please check  followings.

- Does your project use proper python version that you set up the gdal environment?

- Does your ptvs version corresponds to your visual studio version?

- Does your python library DB updated? (if not you can do manually by clicking the "completion DB" button)

If you have any problem just leave some comments :)

------------------------------------------------------------------

I'm using gdal to convert IMG data into png data. 

below is code example of it.

import gdal

import numpy as np

import matplotlib.pyplot as plt

from osgeo import gdal

from matplotlib import cm

gdal.UseExceptions()

geo_n = gdal.Open(r'D:\ChromeDownload\USGS_NED_one_meter_x24y459_IL_12_County_HenryCO_2009_IMG_2015\USGS_NED_one_meter_x24y459_IL_12_County_HenryCO_2009_IMG_2015.img')

geo_s = gdal.Open(r'D:\ChromeDownload\USGS_NED_one_meter_x24y460_IL_12_County_HenryCO_2009_IMG_2015\USGS_NED_one_meter_x24y460_IL_12_County_HenryCO_2009_IMG_2015.img')

drv = geo_n.GetDriver()

print(drv.GetMetadataItem('DMD_LONGNAME'))

north = geo_n.ReadAsArray()

south = geo_s.ReadAsArray()

#topo = np.vstack((north,south))

topo = np.vstack(south)

i,j = np.where(topo>0)

topo = topo[min(i):max(i)+1, min(j):max(j)+1]

topo[topo==0] = np.nan

print(topo.shape)

fig = plt.figure(frameon = False)

plt.imshow(topo, cmap=cm.BrBG_r)

plt.axis('off')

cbar = plt.colorbar(shrink=0.75)

cbar.set_label('meters')

plt.savefig('kauai.png', dpi=300, bbox_inches='tight')

plt.show()

1.  Exchange student and a security officer

OK, I'll tell you what. 

- 좋아요. 어떻게 할지 알려주죠. 

connecting flight: 환승 비행기 

2. Montessori method

This is shaping up to be quite an interesting week for us. 

- 우리에게 흥미로운 한주가 되고 있군요.

This amazing result was dubbed the "Montessori Miracle."

- 이 굉장한 결과는 몬테소리의 기적이라고 불렸다. 

arguably: 아마도

year in and year out: 해마다

directorship: 이사직

parlance: 용어, 말투

comprehensive: 포괄적인

1.

d

2. 

d

3. Confederation Bridge

Engineers faces several environmental challenges when building this bridge.. freezing temperatures, heavy ice, snow.. you name it. 

 - 기술자들은 다리를 지을 때 몇몇 환경적 난제에 맞딱드렸습니다. 영하의 기온, 많은 양의 얼음, 눈.. 그밖의 모든 것 들을요. 

It took quite a while to build this bridge. 

 - 이 다리를 짓는데 시간이 꽤 걸렸다. 

It is frigid temperature.

 - 그것은 혹한의 추위다. 

The sheer scope of this project sets it apart from other cold-weather bridges. 

 - 프로젝트의 순수한 크기로만 봐도 다른 추운 기후를 가진 다리들과는 차별된다. 

This causes problems because, you know, a bridge must be anchored to the seabed. 

 - 이것은 문제가 되는데, 알다시피 다리는 해저에 고정되어야 한다. 

How can the construction workers plant the support columns of a bridge into the bottom of the strait if it's completely frozen through?

 - 해협이 완전하게 얼어있다면, 어떻게 기술자들이 다리의 기둥을 바닥에 설치할 수 있었을까요?

This is dangerous enough as it is, even when there's not a bridge traversing the water. 

  - 물을 가로지르는 다리가 없다고 하더라도, 그 자체만으로도 위험하다. 

They designed conical ice shields to sit at water level on all of the piers. 

  - 그들은 콘모양의 방패를 모든 교각의 수면높이에 설치하였다. 

The forces imparted by the ice to be partially deflected away from the bridge itself. 

  - 얼음에 의해 다리 자체에 가해진 충격은 부분적으로 분산된다. 

This can cause lots of stress for the piers supporting the bridge because of the forces exerted by the water expanding as it freezes. 

  -  물이 얼음에 따라서 그 힘이 중폭되었으므로, 이는 다리를 지탱하고있는 교각에 많은 부하를 준다.

They make it so that the piers don't feel the entire brunt of the ice impact. 

  - 그들은 그것을 만들어서 교각들이 얼음에 의한 충격을 정면으로 받지 않도록 한다. 

Over one hundred thaw-freeze cycles

  - 백번이 넘는 녹고 어는 사이클

Their hand will glance off. 

  - 그들의 손은 빗나갈 것이다.

you name it: Everything you can think of

quite a while: 꽤 오랬동안

frigid: Frigid means extremely cold.

sheer: You can use sheer to emphasize that a state or situation is complete and does not involve or is not mixed with anything else.

anchor: An anchor is a heavy hooked object that is dropped from a boat into the water at the end of a chain in order to make the boat stay in one place.

strait: You can refer to a narrow strip of sea which joins two large areas of sea as a strait or the straits.

traverse: If someone or something traverses an area of land or water, they go across it.

conical: A conical object is shaped like a cone.

piers: A pier is a platform sticking out into water, usually the sea, which people walk along or use when getting onto or off boats.

impart: If you impart information to people, you tell it to them.

deflect: If you deflect something such as criticism or attention, you act in a way that prevents it from being directed towards you or affecting you.

brunt: To bear the brunt or take the brunt of something unpleasant means to suffer the main part or force of it.

thaw:  When ice, snow, or something else that is frozen thaws, it melts.

exert: If someone or something exerts influence, authority, or pressure, they use it in a strong or determinedway, especially in order to produce a particular effect.

glance off: if a ball, etc. glances off something, it touches it lightly and moves away from it in a different direction

4. Work in France 

I don't think teaching is really my cup of tea. 

  - 가르치는건 저에게 맞는일이 아닌거 같아요. 

They both resided in France.

  - 그들은 둘다 프랑스에 살았었다.

not be somebody's cup of tea: not be the kind of person, thing or activity that you like

reside: If someone resides somewhere, they live there or are staying there.