I am a beginner with OOP in R and am stuck at a problem for which I can find no solution.
I defined a class "node" in R using setClass that contains information about a "node" in a network -
setClass(Class = "node",
representation = representation(nID = "integer", links = "integer",
capacity = "numeric"),
prototype = prototype(nID = integer(1), links = integer(20),
capacity = numeric(20)))
What I really want to do is create an array/list that holds several "nodes", each of which is of class "node". Something like
nodeID[100] <- new("node")
But that clearly doesnt work. I have tried creating arrays and converting their class to "node" but that didnt do it either.
This will help me do things like loop over all nodes in my system-
for(i in 1:dim(nodeID))
{
nodeID[i]#capacity <- 1000
blah blah....
}
Note that the problem isnt initializing/defaulting the value of slots (e.g. capacity in this case). I can do that. Any help would be greatly appreciate.
Thanks,
Sumit
Answer ----
Thanks #Ricardo and #dickoa. This created the list of nodeID just like I wanted .
Want to add for anyone else facing the same problem that in order to access the elements/slots of the list of class "node" you have to use the following:
nodeID[[1]]#capacity[1]
Also, I will use lapply instead of for.
Sumit
Try using replicate
nodeID <- replicate(100, new("node"), simplify="list")
is(nodeID)
# [1] "list" "vector"
is(nodeID[[1]])
# [1] "node"
Using something like nodeID[100] <- new("node") as you found, does not work. What that (is attempting) to do is look for an object called nodeID and if found, try to set its 100th element to new("node").
It does not, say, create an object nodeID and populate it with 100 elements.
Also, notice that you can avoid your for loop by instead using, say, lapply:
eg, instead of:
for(i in 1:dim(nodeID))
{
nodeID[i]#capacity <- 1000
blah blah....
}
use:
lapply(nodeID, function(n) {blah balh...} )
Related
Each day, I get an email with the quantities of fruit sold on a particular day. The structure of the email is as below:
Date of report:,04-JAN-2022
Time report produced:,5-JAN-2022 02:04
Apples,6
Pears,1
Lemons,4
Oranges,2
Grapes,7
Grapefruit,2
I'm trying to build some code in R that will search through my emails, find all emails with a particular subject, iterate through each email to find the variables I'm looking for, take the values and place them in a dataframe with the "Date of report" put in a date column.
With the assistance of people in the community, I was able to achieve the desired result in Python. However as my project has developed, I need to now achieve the same result in R if at all possible.
Unfortunately, I'm quite new to R and therefore if anyone has any advice on how to take this forward I would greatly appreciate it.
For those interested, my Python code is below:
#PREP THE STUFF
Fruit_1 = "Apples"
Fruit_2 = "Pears"
searchf = [
Fruit_1,
Fruit_2
]
#DEF THE STUFF
def get_report_vals(report, searches):
dct = {}
for line in report:
term, *value = line
if term.casefold().startswith('date'):
dct['date'] = pd.to_datetime(value[0])
elif term in searches:
dct[term] = float(value[0])
if len(dct.keys()) != len(searches):
dct.update({x: None for x in searches if x not in dct})
return dct
#DO THE STUFF
outlook = win32com.client.Dispatch("Outlook.Application").GetNamespace("MAPI")
inbox = outlook.GetDefaultFolder(6)
messages = inbox.Items
messages.Sort("[ReceivedTime]", True)
results = []
for message in messages:
if message.subject == 'FRUIT QUANTITIES':
if Fruit_1 in message.body and Fruit_2 in message.body:
data = [line.strip().split(",") for line in message.body.split('\n')]
results.append(get_report_vals(data, searchf))
else:
pass
fruit_vals = pd.DataFrame(results)
fruit_vals.columns = map(str.upper, fruit_vals.columns)
I'm probably going about this the wrong way, but I'm trying to use the steps I took in Python to achieve the same result in R. So for example I create some variables to hold the fruit sales I'm searching for, then I create a vector to store the searchables, and then when I create an equivalent 'get_vals' function, I create an empty vector.
library(RDCOMClient)
Fruit_1 <- "Apples"
Fruit_2 <- "Pears"
##Create vector to store searchables
searchf <- c(Fruit_1, Fruit_2)
## create object for outlook
OutApp <- COMCreate("Outlook.Application")
outlookNameSpace = OutApp$GetNameSpace("MAPI")
search <- OutApp$AdvancedSearch("Inbox", "urn:schemas:httpmail:subject = 'FRUIT QUANTITIES'")
inbox <- outlookNameSpace$Folders(6)$Folders("Inbox")
vec <- c()
for (x in emails)
{
subject <- emails(i)$Subject(1)
if (grepl(search, subject)[1])
{
text <- emails(i)$Body()
print(text)
break
}
}
read.table could be a good start for get_report_vals.
Code below outputs result as a list, exception handling still needs to be implemented :
report <- "
Date of report:,04-JAN-2022
Apples,6
Pears,1
Lemons,4
Oranges,2
Grapes,7
Grapefruit,2
"
get_report_vals <- function(report,searches) {
data <- read.table(text=report,sep=",")
colnames(data) <- c('key','value')
# find date
date <- data[grepl("date",data$key,ignore.case=T),"value"]
# transform dataframe to list
lst <- split(data$value,data$key)
# output result as list
c(list(date=date),lst[searches])
}
get_report_vals(report,c('Lemons','Oranges'))
$date
[1] "04-JAN-2022"
$Lemons
[1] "4"
$Oranges
[1] "2"
The results of various reports can then be concatenated in a data.frame using rbind:
rbind(get_report_vals(report,c('Lemons','Oranges')),get_report_vals(report,c('Lemons','Oranges')))
date Lemons Oranges
[1,] "04-JAN-2022" "4" "2"
[2,] "04-JAN-2022" "4" "2"
The code now functions as intended. Function was written quite a bit differently from those recommended:
get_vals <- function(email) {
body <- email$body()
date <- str_extract(body, "\\d{2}-[:alpha:]{3}-\\d{4}") %>%
as.character()
data <- read.table(text = body, sep = ",", skip = 9, strip.white = T) %>%
row_to_names(1) %>%
mutate("Date" = date)
return(data)
}
In addition I've written this to bind the rows together:
info <- sapply(results, get_vals, simplify = F) %>%
bind_rows()
May this is not what you are expecting to get as an answer, but I must state that here to help other readers to avoid such mistakes in future.
Unfortunately your Python code is not well-written. For example, I've noticed the following code where you iterate over all items in a folder and check the Subject and message bodies for keywords:
for message in messages:
if message.subject == 'FRUIT QUANTITIES':
if Fruit_1 in message.body and Fruit_2 in message.body:
You need to use the Find/FindNext or Restrict methods of the Items class instead. So, you don't need to iterate over all items in a folder. Instead, you get only items that correspond to your conditions. Read more about these methods in the following articles:
How To: Use Find and FindNext methods to retrieve Outlook mail items from a folder (C#, VB.NET)
How To: Use Restrict method to retrieve Outlook mail items from a folder
You may combine all your search criteria into a single query. So, you just need to iterate over found items and extract the data.
Also you may find the AdvancedSearch method helpful. The key benefits of using the AdvancedSearch method in Outlook are:
The search is performed in another thread. You don’t need to run another thread manually since the AdvancedSearch method runs it automatically in the background.
Possibility to search for any item types: mail, appointment, calendar, notes etc. in any location, i.e. beyond the scope of a certain folder. The Restrict and Find/FindNext methods can be applied to a particular Items collection (see the Items property of the Folder class in Outlook).
Full support for DASL queries (custom properties can be used for searching too). You can read more about this in the Filtering article in MSDN. To improve the search performance, Instant Search keywords can be used if Instant Search is enabled for the store (see the IsInstantSearchEnabled property of the Store class).
You can stop the search process at any moment using the Stop method of the Search class.
See Advanced search in Outlook programmatically: C#, VB.NET for more information.
I'm following this tutorial that codes a sentiment analysis classifier using BERT with the huggingface library and I'm having a very odd behavior. When trying the BERT model with a sample text I get a string instead of the hidden state. This is the code I'm using:
import transformers
from transformers import BertModel, BertTokenizer
print(transformers.__version__)
PRE_TRAINED_MODEL_NAME = 'bert-base-cased'
PATH_OF_CACHE = "/home/mwon/data-mwon/paperChega/src_classificador/data/hugingface"
tokenizer = BertTokenizer.from_pretrained(PRE_TRAINED_MODEL_NAME,cache_dir = PATH_OF_CACHE)
sample_txt = 'When was I last outside? I am stuck at home for 2 weeks.'
encoding_sample = tokenizer.encode_plus(
sample_txt,
max_length=32,
add_special_tokens=True, # Add '[CLS]' and '[SEP]'
return_token_type_ids=False,
padding=True,
truncation = True,
return_attention_mask=True,
return_tensors='pt', # Return PyTorch tensors
)
bert_model = BertModel.from_pretrained(PRE_TRAINED_MODEL_NAME,cache_dir = PATH_OF_CACHE)
last_hidden_state, pooled_output = bert_model(
encoding_sample['input_ids'],
encoding_sample['attention_mask']
)
print([last_hidden_state,pooled_output])
that outputs:
4.0.0
['last_hidden_state', 'pooler_output']
While the answer from Aakash provides a solution to the problem, it does not explain the issue. Since one of the 3.X releases of the transformers library, the models do not return tuples anymore but specific output objects:
o = bert_model(
encoding_sample['input_ids'],
encoding_sample['attention_mask']
)
print(type(o))
print(o.keys())
Output:
transformers.modeling_outputs.BaseModelOutputWithPoolingAndCrossAttentions
odict_keys(['last_hidden_state', 'pooler_output'])
You can return to the previous behavior by adding return_dict=False to get a tuple:
o = bert_model(
encoding_sample['input_ids'],
encoding_sample['attention_mask'],
return_dict=False
)
print(type(o))
Output:
<class 'tuple'>
I do not recommend that, because it is now unambiguous to select a specific part of the output without turning to the documentation as shown in the example below:
o = bert_model(encoding_sample['input_ids'], encoding_sample['attention_mask'], return_dict=False, output_attentions=True, output_hidden_states=True)
print('I am a tuple with {} elements. You do not know what each element presents without checking the documentation'.format(len(o)))
o = bert_model(encoding_sample['input_ids'], encoding_sample['attention_mask'], output_attentions=True, output_hidden_states=True)
print('I am a cool object and you can acces my elements with o.last_hidden_state, o["last_hidden_state"] or even o[0]. My keys are; {} '.format(o.keys()))
Output:
I am a tuple with 4 elements. You do not know what each element presents without checking the documentation
I am a cool object and you can acces my elements with o.last_hidden_state, o["last_hidden_state"] or even o[0]. My keys are; odict_keys(['last_hidden_state', 'pooler_output', 'hidden_states', 'attentions'])
I faced the same issue while learning how to implement Bert. I noticed that using
last_hidden_state, pooled_output = bert_model(encoding_sample['input_ids'], encoding_sample['attention_mask'])
is the issue. Use:
outputs = bert_model(encoding_sample['input_ids'], encoding_sample['attention_mask'])
and extract the last_hidden state using
output[0]
You can refer to the documentation here which tells you what is returned by the BertModel
I am still learning about python and I face some trouble extracting data from a dict. I need to create a loop which check each values and extract the keys. So for this code I need to find the nice students. I am stuck at line 3 #blank.
How do i go about this?
Thanks in advance
class = {"James":"naughty", "Lisa":"nice", "Bryan":"nice"}
for student in class:
if #blank:
print("Hello, "+student+" students!")
else:
print("odd")
Uses dictionary methods "keys(), values(), items()":
def get_students_by_criteria(student_class, criteria):
students = []
for candidate, value in student_class.items():
if value == criteria:
students.append(candidate)
return students
my_class = {"James":"naughty", "Lisa":"nice", "Bryan":"nice"}
print(get_students_by_criteria(my_class, "nice"))
Warning to the word "class" it is a keyword reserved for python programming oriented object
I have 2 Dictionaries:
StatePops={'AL':4887871, 'AK':737438, 'AZ':7278717, 'AR':3013825}
StateNames={'AL':'Alabama', 'AK':'Alaska', 'AZ':'Arizona', 'AR':'Arkansas'}
I am trying to merge so the Value of StateNames is the Key for StatePops.
Ex.
{'Alabama': 4887871, 'Alaska': 737438, ...
I also have to display the name of states w/ population over 4million.
Any help is appreciated!!!
You have not specified in what programming language you want this problem to be solved.
Nonetheless, here is a solution in Python.
state_pops = {
'AL': 4887871,
'AK': 737438,
'AZ':7278717,
'AR':3013825
}
state_names = {
'AL':'Alabama',
'AK':'Alaska',
'AZ':'Arizona',
'AR':'Arkansas'
}
states = dict([([state_names[k],state_pops[k]]) for k in state_pops])
final = {k:v for k, v in states.items() if v > 4000000}
print(states)
print(final)
First, you can merge two dictionaries with the predefined dict python function in the states variable as such. Here, k is an iterator and it is used as index for state_names and state_pops.
Then, store the filtered dictionary in final where the states.items() is used to access the keys and values in states and type-cast it as a string with the str function.
There may be more simpler solutions but this is as far as I can optimize the problem.
Hope this helps.
Dictionary Keys cannot be changed in Python. You need to either add the modified key-value pair to the dictionary and then delete the old key, or you can create a new dictionary. I'd opt for the second option, i.e., creating a new dictionary.
myDict = {}
for i in StatePops:
myDict.update({StateNames[i] : StatePops[i]})
This outputs myDict as
{'Alabama': 4887871, 'Alaska': 737438, 'Arizona': 7278717, 'Arkansas': 3013825}
I am a new user of Julia and I want to work on graphs. I found the Graphs.jl library but not very documented. I tried to create a GenericGraph based on ExVertex and ExEdge but I need more information.
The code I'm using :
using Graphs
CompGraph = GenericGraph{ExVertex, ExEdge{ExVertex}}
temp = ExVertex(1, "VertexName")
temp.attributes["Att"] = "Test"
add_vertex!(CompGraph, temp)
Now I still need the ExVertex list and ExEdge list. Is there any defined parameters? or how can I create such lists?
The solution was too simple. a list is juste a simple array and not a new type. Besides, there is a simple defined function which creates graphs based on different types of edges and vertecies.
I changed my code to :
using Graphs
CG_VertexList = ExVertex[]
CG_EdgeList = ExEdge{ExVertex}[]
CompGraph = graph(CG_VertexList, CG_EdgeList)
temp = ExVertex(1, "VertexName")
temp.attributes["Att"] = "Test"
add_vertex!(CompGraph, temp)