Question: I have a program that solves a quadratic equation. The program gives real solutions only. How do I perform the quality testing of the program? Do you need to ask me for some extra input parameters?
Create test cases, and check the result of your program against the expected result (which is calculated externally) in the test case.
The test cases can cover several ordinary cases, together with special cases, such as when the coefficient is 0, or the discriminant is < 0, = 0, near 0. When you compare the result, make sure you handle the comparison properly (since the result is floating point numbers).
# "quadratic-rb.rb" Code by RRB, dated April 2014. email ab_z#yahoo.com
class Quadratic
def input
print "Enter the value of a: "
$a = gets.to_f
print "Enter the value of b: "
$b = gets.to_f
print "Enter the value of c: "
$c = gets.to_f
end
def announcement #Method to display Equation
puts "The formula is " + $a.to_s + "x^2 + " + $b.to_s + "x + " + $c.to_s + "=0"
end
def result #Method to solve the equation and display answer
if ($b**2-4*$a*$c)>0
x1=(((Math.sqrt($b**2-4*$a*$c))-($b))/(2*$a))
x2=(-(((Math.sqrt($b**2-4*$a*$c))-($b))/(2*$a)))
puts "The values of x1 and x2 are " +x1.to_s + " and " + x2.to_s
else
puts "x1 and x2 are imaginary numbers"
end
end
Quadratic_solver = Quadratic.new
Quadratic_solver.input
Quadratic_solver.announcement
Quadratic_solver.result
end
Related
My objective is to extract strings from numbered/bulleted lists in multiple Microsoft Word documents, then to organize those strings into a single, one-line string where each string is ordered in the following manner: 1.string1 2.string2 3.string3 etc. I refer to these one-line strings as procedures, consisting of 'steps' 1., 2., 3., etc.
The reason it has to be in this format is because the procedure strings are being put into a database, the database is used to create Excel spreadsheet outputs, a formatting macro is used on the spreadsheets, and the procedure strings in question have to be in this format in order for that macro to work properly.
The numbered/bulleted lists in MSword are all similar in format, but some use numbers, some use bullets, and some have extra line spaces before the first point, or extra line spaces after the last point.
The following text shows three different examples of how the Word documents are formatted:
Paragraph Keyword 1: arbitrary text
1. Step 1
2. Step 2
3. Step 3
Paragraph Keyword 2: arbitrary text
Paragraph Keyword 3: arbitrary text
• Step 1
• Step 2
• Step 3
Paragraph Keyword 4: arbitrary text
Paragraph Keyword 5: arbitrary text
Step 1
Step 2
Step 3
Paragraph Keyword 6: arbitrary text
(For some reason the first two lists didn't get indented in the formatting of the post, but in my word document all the indentation is the same)
When the numbered/bulleted list is formatted without line extra spaces, my code works fine, e.g. between "paragraph keyword 1:" and "paragraph keyword 2:".
I was trying to use isspace() to isolate the instances where there are extra line spaces that aren't part of the list that I want to include in my procedure strings.
Here is my code:
''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
def extractStrings(file):
doc = file
for i in range(len(doc.paragraphs)):
str1 = doc.paragraphs[i].text
if "Paragraph Keyword 1:" in str1:
start1=i
if "Paragraph Keyword 2:" in str1:
finish1=i
if "Paragraph Keyword 3:" in str1:
start2=i
if "Paragraph Keyword 4:" in str1:
finish2=i
if "Paragraph Keyword 5:" in str1:
start3=i
if "Paragraph Keyword 6:" in str1:
finish3=i
print("----------------------------")
procedure1 = ""
y=1
for x in range(start1 + 1, finish1):
temp = str((doc.paragraphs[x].text))
print(temp)
if not temp.isspace():
if y > 1:
procedure1 = (procedure1 + " " + str(y) + "." + temp)
else:
procedure1 = (procedure1 + str(y) + "." + temp)
y=y+1
print(procedure1)
print("----------------------------")
procedure2 = ""
y=1
for x in range(start2 + 1, finish2):
temp = str((doc.paragraphs[x].text))
print(temp)
if not temp.isspace():
if y > 1:
procedure2 = (procedure2 + " " + str(y) + "." + temp)
else:
procedure2 = (procedure2 + str(y) + "." + temp)
y=y+1
print(procedure2)
print("----------------------------")
procedure3 = ""
y=1
for x in range(start3 + 1, finish3):
temp = str((doc.paragraphs[x].text))
print(temp)
if not temp.isspace():
if y > 1:
procedure3 = (procedure3 + " " + str(y) + "." + temp)
else:
procedure3 = (procedure3 + str(y) + "." + temp)
y=y+1
print(procedure3)
print("----------------------------")
del doc
''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
import docx
doc1 = docx.Document("docx_isspace_experiment_042420.docx")
extractStrings(doc1)
del doc1
Unfortunately I have no way of putting the output into this post, but the problem is that whenever there is a blank line in the word doc, isspace() returns false, and a number "x." is assigned to empty space, so I end up with something like: 1. 2.Step 1 3.Step 2 4.Step 3 5. 6. (that's the last iteration of print(procedure3) from the code)
The problem is that isspace() is returning false even when my python console output shows that the string is just a blank line.
Am I using isspace() incorrectly? Is there something in the string I am not detecting that is causing isspace() to return false? Is there a better way to accomplish this?
Use the test:
# --- for s a str value, like paragraph.text ---
if s.strip() == "":
print("s is a blank line")
str.isspace() returns True if the string contains only whitespace. An empty str contains nothing, and so therefore does not contain whitespace.
I am facing a issue, here is my script. some end or bracket issue but I have checked noting is missing.
function [h, display_array] = displayData(X, example_width)
%DISPLAYDATA Display 2D data in a nice grid
% [h, display_array] = DISPLAYDATA(X, example_width) displays 2D data
% stored in X in a nice grid. It returns the figure handle h and the
% displayed array if requested.
% Set example_width automatically if not passed in
if ~exist('example_width', 'var') || isempty(example_width)
example_width = round(sqrt(size(X, 2)));
end
% Gray Image
colormap(gray);
% Compute rows, cols
[m n] = size(X);
example_height = (n / example_width);
% Compute number of items to display
display_rows = floor(sqrt(m));
display_cols = ceil(m / display_rows);
% Between images padding
pad = 1;
% Setup blank display
display_array = - ones(pad + display_rows * (example_height + pad), ...
pad + display_cols * (example_width + pad));
% Copy each example into a patch on the display array
curr_ex = 1;
for j = 1:display_rows
for i = 1:display_cols
if curr_ex > m,
break;
end
% Copy the patch
% Get the max value of the patch
max_val = max(abs(X(curr_ex, :)));
display_array(pad + (j - 1) * (example_height + pad) +
(1:example_height), ...
pad + (i - 1) * (example_width + pad) +
(1:example_width)) = ...
reshape(X(curr_ex, :),
example_height, example_width) / max_val;
curr_ex = curr_ex + 1;
end
if curr_ex > m,
break;
end
end
% Display Image
h = imagesc(display_array, [-1 1]);
% Do not show axis
axis image off
drawnow;
end
ERROR:
displayData
parse error near line 86 of file C:\Users\ALI\displayData.m
syntax error
Pls guide which is the error in the script, this script is already written in
the coursera so its must be error free.
You seem to have modified the code, and moved the "ellipsis" operator (i.e. ...) or the line that is supposed to follow it, in several places compared to the original code in coursera.
Since the point of the ellipsis operator is to appear at the end of a line, denoting that the line that follows is meant to be a continuation of the line before, then moving either the ellipsis or the line below it will break the code.
E.g.
a = 1 + ... % correct use of ellipsis, code continues below
2 % treated as one line, i.e. a = 1 + 2
vs
a = 1 + % without ellipsis, the line is complete, and has an error
... 2 % bad use of ellipsis; also anything to the right of '...' is ignored
vs
a = 1 + ... % ellipsis used properly so far
% but the empty line here makes the whole 'line' `a = 1 +` which is wrong
2 % This is a new instruction
I performed a CFA using the lavaan package
require('lavaan');
HS.model <- 'external_regulation_soc =~ JOBMOTIVATIE_extsoc1 +
JOBMOTIVATIE_extsoc2 + JOBMOTIVATIE_extsoc3
external_regulation_mat =~ JOBMOTIVATIE_extmat1 +
JOBMOTIVATIE_extmat2 + JOBMOTIVATIE_extmat3
introjected_regulation =~ JOBMOTIVATIE_introj1 +
JOBMOTIVATIE_introj2 + JOBMOTIVATIE_introj3 +
JOBMOTIVATIE_introj4
identified_regulation =~ JOBMOTIVATIE_ident1 +
JOBMOTIVATIE_ident2 + JOBMOTIVATIE_ident3
intrinsic_motivation =~ JOBMOTIVATIE_intrin1 +
JOBMOTIVATIE_intrin2 + JOBMOTIVATIE_intrin3'
fit <- cfa(HS.model, data = dataset, scores="regression")
summary(fit, fit.measures=TRUE, standardized=TRUE)
I managed to get the values for the five factors in a seperate dataset using
data_factor <- predict(fit)
But I need these 5 factors (as columns, as variables), added to my original dataset. How can I achieve this?
I tried cbind, but got an error:
factorERS <- select(dataset, JOBMOTIVATIE_extsoc1 +
JOBMOTIVATIE_extsoc2 + JOBMOTIVATIE_extsoc3)
data_CFA <- cbind(dataset, fit$scores)
Error in fit$scores : $ operator not defined for this S4 class
Thanks for helping me out!
I have a very big polygon shapefile with hundreds of features, often overlapping each other. Each of these features has a value stored in the attribute table. I simply need to calculate the average values in the areas where they overlap.
I can imagine that this task requires several intricate steps: I was wondering if there is a straightforward methodology.
I’m open to every kind of suggestion, I can use ArcMap, QGis, arcpy scripts, PostGis, GDAL… I just need ideas. Thanks!
You should use the Union tool from ArcGIS. It will create new polygons where the polygons overlap. In order to keep the attributes from both polygons, add your polygon shapefile twice as input and use ALL as join_attributes parameter.This creates also polygons intersecting with themselves, you can select and delete them easily as they have the same FIDs. Then just add a new field to the attribute table and calculate it based on the two original value fields from the input polygons.
This can be done in a script or directly with the toolbox's tools.
After few attempts, I found a solution by rasterising all the features singularly and then performing cell statistics in order to calculate the average.
See below the script I wrote, please do not hesitate to comment and improve it!
Thanks!
#This script processes a shapefile of snow persistence (area of interest: Afghanistan).
#the input shapefile represents a month of snow cover and contains several features.
#each feature represents a particular day and a particular snow persistence (low,medium,high,nodata)
#these features are polygons multiparts, often overlapping.
#a feature of a particular day can overlap a feature of another one, but features of the same day and with
#different snow persistence can not overlap each other.
#(potentially, each shapefile contains 31*4 feature).
#the script takes the features singularly and exports each feature in a temporary shapefile
#which contains only one feature.
#Then, each feature is converted to raster, and after
#a logical conditional expression gives a value to the pixel according the intensity (high=3,medium=2,low=1,nodata=skipped).
#Finally, all these rasters are summed and divided by the number of days, in order to
#calculate an average value.
#The result is a raster with the average snow persistence in a particular month.
#This output raster ranges from 0 (no snow) to 3 (persistent snow for the whole month)
#and values outside this range should be considered as small errors in pixel overlapping.
#This script needs a particular folder structure. The folder C:\TEMP\Afgh_snow_cover contains 3 subfolders
#input, temp and outputs. The script takes care automatically of the cleaning of temporary data
import arcpy, numpy, os
from arcpy.sa import *
from arcpy import env
#function for finding unique values of a field in a FC
def unique_values_in_table(table, field):
data = arcpy.da.TableToNumPyArray(table, [field])
return numpy.unique(data[field])
#check extensions
try:
if arcpy.CheckExtension("Spatial") == "Available":
arcpy.CheckOutExtension("Spatial")
else:
# Raise a custom exception
#
raise LicenseError
except LicenseError:
print "spatial Analyst license is unavailable"
except:
print arcpy.GetMessages(2)
finally:
# Check in the 3D Analyst extension
#
arcpy.CheckInExtension("Spatial")
# parameters and environment
temp_folder = r"C:\TEMP\Afgh_snow_cover\temp_rasters"
output_folder = r"C:\TEMP\Afgh_snow_cover\output_rasters"
env.workspace = temp_folder
unique_field = "FID"
field_Date = "DATE"
field_Type = "Type"
cellSize = 0.02
fc = r"C:\TEMP\Afgh_snow_cover\input_shapefiles\snow_cover_Dec2007.shp"
stat_output_name = fc[-11:-4] + ".tif"
#print stat_output_name
arcpy.env.extent = "MAXOF"
#find all the uniquesID of the FC
uniqueIDs = unique_values_in_table(fc, "FID")
#make layer for selecting
arcpy.MakeFeatureLayer_management (fc, "lyr")
#uniqueIDs = uniqueIDs[-5:]
totFeatures = len(uniqueIDs)
#for each feature, get the date and the type of snow persistence(type can be high, medium, low and nodata)
for i in uniqueIDs:
SC = arcpy.SearchCursor(fc)
for row in SC:
if row.getValue(unique_field) == i:
datestring = row.getValue(field_Date)
typestring = row.getValue(field_Type)
month = str(datestring.month)
day = str(datestring.day)
year = str(datestring.year)
#format month and year string
if len(month) == 1:
month = '0' + month
if len(day) == 1:
day = '0' + day
#convert snow persistence to numerical value
if typestring == 'high':
typestring2 = 3
if typestring == 'medium':
typestring2 = 2
if typestring == 'low':
typestring2 = 1
if typestring == 'nodata':
typestring2 = 0
#skip the NoData features, and repeat the following for each feature (a feature is a day and a persistence value)
if typestring2 > 0:
#create expression for selecting the feature
expression = ' "FID" = ' + str(i) + ' '
#select the feature
arcpy.SelectLayerByAttribute_management("lyr", "NEW_SELECTION", expression)
#create
#outFeatureClass = os.path.join(temp_folder, ("M_Y_" + str(i)))
#create faeture class name, writing the snow persistence value at the end of the name
outFeatureClass = "Afg_" + str(year) + str(month) + str(day) + "_" + str(typestring2) + '.shp'
#export the feature
arcpy.FeatureClassToFeatureClass_conversion("lyr", temp_folder, outFeatureClass)
print "exported FID " + str(i) + " \ " + str(totFeatures)
#create name of the raster and convert the newly created feature to raster
outRaster = outFeatureClass[4:-4] + ".tif"
arcpy.FeatureToRaster_conversion(outFeatureClass, field_Type, outRaster, cellSize)
#remove the temporary fc
arcpy.Delete_management(outFeatureClass)
del SC, row
#now many rasters are created, representing the snow persistence types of each day.
#list all the rasters created
rasterList = arcpy.ListRasters("*", "All")
print rasterList
#now the rasters have values 1 and 0. the following loop will
#perform CON expressions in order to assign the value of snow persistence
for i in rasterList:
print i + ":"
inRaster = Raster(i)
#set the value of snow persistence, stored in the raster name
value_to_set = i[-5]
inTrueRaster = int(value_to_set)
inFalseConstant = 0
whereClause = "Value > 0"
# Check out the ArcGIS Spatial Analyst extension license
arcpy.CheckOutExtension("Spatial")
print 'Executing CON expression and deleting input'
# Execute Con , in order to assign to each pixel the value of snow persistence
print str(inTrueRaster)
try:
outCon = Con(inRaster, inTrueRaster, inFalseConstant, whereClause)
except:
print 'CON expression failed (probably empty raster!)'
nameoutput = i[:-4] + "_c.tif"
outCon.save(nameoutput)
#delete the temp rasters with values 0 and 1
arcpy.Delete_management(i)
#list the raster with values of snow persistence
rasterList = arcpy.ListRasters("*_c.tif", "All")
#sum the rasters
print "Caclulating SUM"
outCellStats = CellStatistics(rasterList, "SUM", "DATA")
#calculate the number of days (num of rasters/3)
print "Calculating day ratio"
num_of_rasters = len(rasterList)
print 'Num of rasters : ' + str(num_of_rasters)
num_of_days = num_of_rasters / 3
print 'Num of days : ' + str(num_of_days)
#in order to store decimal values, multiplicate the raster by 1000 before dividing
outCellStats = outCellStats * 1000 / num_of_days
#save the output raster
print "saving output " + stat_output_name
stat_output_name = os.path.join(output_folder,stat_output_name)
outCellStats.save(stat_output_name)
#delete the remaining temporary rasters
print "deleting CON rasters"
for i in rasterList:
print "deleting " + i
arcpy.Delete_management(i)
arcpy.Delete_management("lyr")
Could you rasterize your polygons into multiple layers, each pixel could contain your attribute value. Then merge the layers by averaging the attribute values?
I have a field CODE_USER_2 that can be equal to 1.75, 2, 2.62, 3.75, 5.25, 6, OT(w/2 spaces, or __(4 spaces). If it is 1.75, 2, 2.62, 3.75, 5.25, 6 I would like corresponding weights to result (THIS PART WORKS).
If the field is __ or OT, I would like the equation to result with 0. I currently get #error with the following formula.
=IIf(Fields!CODE_USER_2_IM.Value= " " OR "OT " ,0,Switch(Fields!CODE_USER_2_IM.Value=1.75,.629,Fields!CODE_USER_2_IM.Value=2,.67,Fields!CODE_USER_2_IM.Value=2.62,1.089,Fields!CODE_USER_2_IM.Value=3.75,1.767,Fields!CODE_USER_2_IM.Value=5.25,3.224,Fields!CODE_USER_2_IM.Value=6,3.895))
Please let me know if you have ideas!
You have to repeat "Fields!CODE_USER_2_IM.Value = " after the OR.
Or try this - less wordy but more obscure :
=IIf( ( " |OT |" ).Contains(Fields!CODE_USER_2_IM.Value + "|"
,0,Switch(Fields!CODE_USER_2_IM.Value=1.75,.629,Fields!CODE_USER_2_IM.Value=2,.67,Fields!CODE_USER_2_IM.Value=2.62,1.089,Fields!CODE_USER_2_IM.Value=3.75,1.767,Fields!CODE_USER_2_IM.Value=5.25,3.224,Fields!CODE_USER_2_IM.Value=6,3.895
, True , 0))
Always close out a Switch with:
, True , [default value] )
Also beware that matching in SSRS expressions is exact e.g. 2 spaces not = 4 spaces.