**I have a tsurf (.ts file), I want to know how we can convert it to a format so that it can be opened in ARCMAP in a form of a raster.
My .ts file contains triangulated data points. **
Its in a format as given below...
.......
GOCAD_ORIGINAL_COORDINATE_SYSTEM
NAME Default
AXIS_NAME "X" "Y" "Z"
AXIS_UNIT "m" "m" "m"
ZPOSITIVE Elevation
END_ORIGINAL_COORDINATE_SYSTEM
GEOLOGICAL_FEATURE bisop64
GEOLOGICAL_TYPE top
STRATIGRAPHIC_POSITION creta 5
TFACE
VRTX 1 473500 3771000 -1103.3717041015625
VRTX 2 473750 3771000 -1087.019775390625
VRTX 3 473500 3770750 -1128.013427734375
VRTX 4 473750 3770750 -1142.8648681640625
VRTX 5 473250 3770750 -1128.40283203125
VRTX 6 473750 3771250 -1025.1702880859375
...............
I tried to look at TIN files in arcmap but have been unsucessful so far.
Any help in this regard would be highly appreciated.
I am having some data coming from csv which has \n character in it and I expect neo4j to add a new line when assigning that string to some attribute in node. Apparently its not working. I can see \n character as it is added in the string.
How to make it work? Thanks in Advance.
Following is one such string example from CSV:
Combo 4 4 4 5 \n\nSpare Fiber Inventory. \nMultimode Individual fibers from 9927/9928 to FDB.\nNo available spares from either BTS to FDB - New conduits would be required\n\nFrom FDB to tower top. 9 of 9 Spares available on 2.5 riser cables.
My load command:
USING PERIODIC COMMIT 500
LOAD CSV WITH HEADERS
FROM 'file:///abc.csv' AS line
WITH line WHERE line.parent <> "" AND line.type = 'LSD' AND line.parent_type = 'XYZ'
This is a hack that I made to replace the occurrences of \n with a newline. The character \ is an escape character so it will replace \n with a new line in line 4. Do not remove line 5 and combine with line 4.
LOAD CSV WITH HEADERS
FROM 'file:///abc.csv' AS line
WITH line WHERE line.parent <> ""
WITH replace(line.parent,'\\n',"
") as parent
MERGE (p:Parent {parent: parent})
RESULT:
{
"identity": 16,
"labels": [
"Parent"
],
"properties": {
"parent": "Combo 4 4 4 5
Spare Fiber Inventory.
Multimode Individual fibers from 9927/9928 to FDB.
No available spares from either BTS to FDB - New conduits would be required
From FDB to tower top. 9 of 9 Spares available on 2.5 riser cables."
}
}
I want to read csvfile in pandas. I have used function:
ace = pd.read_csv('C:\\Users\\C313586\\Desktop\\Daniil\\Daniil\\ACE.csv',sep = '\t')
And as output I got this:
a)First row(should be header)
_AdjustedNetWorthToTotalCapitalEmployed _Ebit _StTradeRec _StTradePay _OrdinaryCf _CfWorkingC _InvestingAc _OwnerAc _FinancingAc _ProdValueGrowth _NetFinancialDebtTotalAdjustedCapitalEmployed_BanksAndOtherInterestBearingLiabilitiesTotalEquityAndLiabilities _NFDEbitda _DepreciationAndAmortizationProductionValue _NumberOfDays _NumberOfDays360
#other rows separated by tab
0 5390\t0000000000000125\t0\t2013-12-31\t2013\tF...
1 5390\t0000000000000306\t0\t2015-12-31\t2015\tF...
2 5390\t00000000000003VG\t0\t2015-12-31\t2015\tF...
3 5390\t0000000000000405\t0\t2016-12-31\t2016\tF...
4 5390\t00000000000007VG\t0\t2013-12-31\t2013\tF...
5 5390\t0000000000000917\t0\t2015-12-31\t2015\tF...
6 5390\t00000000000009VG\t0\t2016-12-31\t2016\tF...
7 5390\t0000000000001052\t0\t2015-12-31\t2015\tF...
8 5390\t00000000000010SG\t0\t2015-12-31\t2015\tF...
Do you have any ideas why it happens? How can I fix it?
You should use the argument sep=r'\t' (note the extra r). This will make pandas search for the exact string \t (the r stands for raw)
I need to read different CSV file in prolog, some row are formatted with 0'\t, in other file are formatted with the space 0'.
I used:
read_points(Filename, Points) :-
csv_read_file(Filename, P,[convert(true),functor(pt),separator(0'\t)]),
csv_read_file(Filename, P,[convert(true),functor(pt),separator(0' )]).
But it dosen't work because return me two different list.
How can I code it correctley?
Thank you.
EDIT:
example file with '0\t:
0.1 5
3 5
5 8
example with '0:
0.1 5
3 5
5 8
I resolve it using the If statement and searching in the first line if there is a space or not.
read(Filename, Elements) :-
( space(Filename)
-> csv_read_file(Filename, L,[functor(line),separator(0' )])
; csv_read_file(Filename, L,[functor(line),separator(0'\t)])
).
space(File):-
read_first(File,L),
once(member(32,L)).
read_first(File, sol) :-
see(File),
read_one_line(Codes),
seen,
Sol = Codes.
read_one_line(Codes) :-
get0(Code),
( Code < 0 /* end of file */ ->
Codes = []
; Code =:= 10 /* end of line */ ->
Codes = []
; Codes = [Code|Codes1],
read_one_line(Codes1)
).
I wanted to import a .txt file in R but the format is really special and it's looks like a json format but I don't know how to import it. There is an example of my data:
{"datetime":"2015-07-08 09:10:00","subject":"MMM","sscore":"-0.2280","smean":"0.2593","svscore":"-0.2795","sdispersion":"0.375","svolume":"8","sbuzz":"0.6026","lastclose":"155.430000000","companyname":"3M Company"},{"datetime":"2015-07-07 09:10:00","subject":"MMM","sscore":"0.2977","smean":"0.2713","svscore":"-0.7436","sdispersion":"0.400","svolume":"5","sbuzz":"0.4895","lastclose":"155.080000000","companyname":"3M Company"},{"datetime":"2015-07-06 09:10:00","subject":"MMM","sscore":"-1.0057","smean":"0.2579","svscore":"-1.3796","sdispersion":"1.000","svolume":"1","sbuzz":"0.4531","lastclose":"155.380000000","companyname":"3M Company"}
To deal with this is used this code:
test1 <- read.csv("C:/Users/test1.txt", header=FALSE)
## Import as 5 observations (5th is all empty) of 1700 variables
#(in fact 40 observations of 11 variables). In fact when I imported the
#.txt file, it's having one line (5th obs) empty, and 4 lines of data and
#placed next to each other 4 lines of data of 11 variables.
# Get the different lines
part1=test1[1:10]
part2=test1[11:20]
part3=test1[21:30]
part4=test1[31:40]
...
## Remove the empty line (there were an empty line after each)
part1=part1[-5,]
part2=part2[-5,]
part3=part3[-5,]
...
## Rename the columns
names(part1)=c("Date Time","Subject","Sscore","Smean","Svscore","Sdispersion","Svolume","Sbuzz","Last close","Company name")
names(part2)=c("Date Time","Subject","Sscore","Smean","Svscore","Sdispersion","Svolume","Sbuzz","Last close","Company name")
names(part3)=c("Date Time","Subject","Sscore","Smean","Svscore","Sdispersion","Svolume","Sbuzz","Last close","Company name")
...
## Assemble data to have one dataset
data=rbind(part1,part2,part3,part4,part5,part6,part7,part8,part9,part10)
## Formate Date Time
times <- as.POSIXct(data$`Date Time`, format='{datetime:%Y-%m-%d %H:%M:%S')
data$`Date Time` <- times
## Keep only the Date
data$Date <- as.Date(times)
## Formate data - Remove text
data$Subject <- gsub("subject:", "", data$Subject)
data$Sscore <- gsub("sscore:", "", data$Sscore)
...
So My code is working to reinstate the data but it's maybe very difficult and more long I know there is better ways to do it, so if you could help me with that I would be very grateful.
There are many packages that read JSON, e.g. rjson, jsonlite, RJSONIO (they will turn in up a google search) - just pick one and give it a go.
e.g.
library(jsonlite)
json.text <- '{"datetime":"2015-07-08 09:10:00","subject":"MMM","sscore":"-0.2280","smean":"0.2593","svscore":"-0.2795","sdispersion":"0.375","svolume":"8","sbuzz":"0.6026","lastclose":"155.430000000","companyname":"3M Company"},{"datetime":"2015-07-07 09:10:00","subject":"MMM","sscore":"0.2977","smean":"0.2713","svscore":"-0.7436","sdispersion":"0.400","svolume":"5","sbuzz":"0.4895","lastclose":"155.080000000","companyname":"3M Company"},{"datetime":"2015-07-06 09:10:00","subject":"MMM","sscore":"-1.0057","smean":"0.2579","svscore":"-1.3796","sdispersion":"1.000","svolume":"1","sbuzz":"0.4531","lastclose":"155.380000000","companyname":"3M Company"}'
x <- fromJSON(paste0('[', json.text, ']'))
datetime subject sscore smean svscore sdispersion svolume sbuzz lastclose companyname
1 2015-07-08 09:10:00 MMM -0.2280 0.2593 -0.2795 0.375 8 0.6026 155.430000000 3M Company
2 2015-07-07 09:10:00 MMM 0.2977 0.2713 -0.7436 0.400 5 0.4895 155.080000000 3M Company
3 2015-07-06 09:10:00 MMM -1.0057 0.2579 -1.3796 1.000 1 0.4531 155.380000000 3M Company
I paste the '[' and ']' around your JSON because you have multiple JSON elements (the rows in the dataframe above) and for this to be well-formed JSON it needs to be an array, i.e. [ {...}, {...}, {...} ] rather than {...}, {...}, {...}.