### D40 : Kit lens (18-55mm Nikkor Af-S G)

You need to watchout for depth of field at 55mm. I have to reprogram myself after 4 years of using a compact. I keep thinking f5.6 is 'Ok for things at inifinity, like that building over there'

But it ain't. You have to do tricks like 'hyper focus', i.e. focus at infinity (like a building behind this one) and then recompose, or stop down the lens more.

Lets actually work this out:
Circle of confusion (Zeiss formula)
c = d/1730
where d = sqrt(23.7^2 + 15.6^2) = 28.37mm
c = 0.0164mm

Hyper focal distance (Wikipedia)
H = f^2/Nc
f = 55mm
N = 5.6

H = 32937.71 mm = 32 m

The building was probably 10-15m away, and I focused on that, reducing my DOF. I should have kept my aperture at around

N = f^2/Hc = 55^2/(15000*.0164) = f12 for a good shot.

Alternatively, I should have focused on the farthest part of the building, locked focus and recomposed.

Stop down the lens Kaushik, stop it down. This 'ere's a REAL camera :)

### Flowing text in inkscape (Poster making)

You can flow text into arbitrary shapes in inkscape. (From a hint here).

You simply create a text box, type your text into it, create a frame with some drawing tool, select both the text box and the frame (click and shift) and then go to text->flow into frame.

UPDATE:

Trying to enter sentence so that text forms the number three...any ideas?
The solution:
Type '3' using the text toolConvert to path using object->pathSize as necessaryRemove fillUngroupType in actual text in new text boxSelect the text and the '3' pathFlow the text

### Pandas panel = collection of tables/data frames aligned by index and column

Pandas panel provides a nice way to collect related data frames together while maintaining correspondence between the index and column values:

import pandas as pd, pylab #Full dimensions of a slice of our panel index = ['1','2','3','4'] #major_index columns = ['a','b','c'] #minor_index df = pd.DataFrame(pylab.randn(4,3),columns=columns,index=index) #A full slice of the panel df2 = pd.DataFrame(pylab.randn(3,2),columns=['a','c'],index=['1','3','4']) #A partial slice df3 = pd.DataFrame(pylab.randn(2,2),columns=['a','b'],index=['2','4']) #Another partial slice df4 = pd.DataFrame(pylab.randn(2,2),columns=['d','e'],index=['5','6']) #Partial slice with a new column and index pn = pd.Panel({'A': df}) pn['B'] = df2 pn['C'] = df3 pn['D'] = df4 for key in pn.items: print pn[key] -> output …

### Drawing circles using matplotlib

Use the pylab.Circle command

import pylab #Imports matplotlib and a host of other useful modules cir1 = pylab.Circle((0,0), radius=0.75, fc='y') #Creates a patch that looks like a circle (fc= face color) cir2 = pylab.Circle((.5,.5), radius=0.25, alpha =.2, fc='b') #Repeat (alpha=.2 means make it very translucent) ax = pylab.axes(aspect=1) #Creates empty axes (aspect=1 means scale things so that circles look like circles) ax.add_patch(cir1) #Grab the current axes, add the patch to it ax.add_patch(cir2) #Repeat pylab.show()