Advertisements Tables and code at the bottom will probs help much more than description. I have a solution that works but think its very inefficient see bottom. Problem: I have two data frames df_1 and df_2 — these dataframes have a match column – match_id df_2 has a date column that I am trying to… Read More Python: Filling a dataframe sequentially based on matching ids (inefficient code)
Advertisements I have a loop where I update a value that changes the view. In this example I want the updates to happen one at a time so you see it ripple across the row, but they all happen at once. struct AnimationQuestion: View { @State var colors = "🟪🟨🟧🟦🟥🟫⬛️🟩⬜️".map { String($0) } @State var… Read More How do I animate changes one at a time in SwiftUI on a button tap?
Advertisements I have a dataframe with a datetime column in string type, like this: >>> df2 date a b 0 2020/1/1 8.0 5.0 1 2020/1/2 10.0 7.0 2 2020/1/3 6.0 1.0 3 2020/1/4 6.0 3.0 I want use its ‘date’ column to generate a new index with various length by multiply a array, like this:… Read More datetime column of pandas multiply a number
Advertisements In My repository, I have two API calls that should be done sequentially. First API call returns Completable -> If this API call fails, we should not proceed further, if it succeeds we should continue with the second API call Second API call returns Single -> If this API call fails, we should NOT… Read More Chain Completable and a Single RxJava + Retrofit
Advertisements If I have the following model class for example: class MyTestModel(nn.Module): def __init__(self): super(MyTestModel, self).__init__() self.seq1 = nn.Sequential( nn.Conv2d(3, 6, 3), nn.MaxPool2d(2, 2), nn.Conv2d(6, 16, 3), nn.MaxPool2d(2, 2), nn.Flatten(), nn.Linear(myflattendinput(), 120), # how to automate this? nn.ReLU(), nn.Linear(120, 84), nn.ReLU(), nn.Linear(84, 2), ) self.softmax = nn.Softmax(dim=1) def forward(self, x): x = self.seq1(x) x =… Read More Is it possible to auto-size the subsequent input of a layer following torch.nn.Flatten within torch.nn.Sequential in PyTorch?
Advertisements The problem I would like to create a dictionary of dicts out of a flat list I have in order to add a "sequentiality" piece of information, but I am having some trouble finding a solution. The list is something like a = [‘Q=123’, ‘W=456’, ‘E=789’, ‘Q=753’, ‘W=159’, ‘E=888’] and I am shooting for… Read More Adding "sequential" information to python list using dictionaries
Advertisements I made a function that randomly selects one from a list of texts. def ttc(*arg): a = random.choice([*arg]) return ”.join(a) print(ttc("Price", "Condition", "Loan")) print(ttc("entertainment", "geese", "Uruguay", "comedy", "butterfly")) But I found it necessary to make certain words have a higher probability of being selected. For example, can we change the probability of being selected… Read More How to tune random.choice probability – python –
Advertisements To give context, I’m trying to create a simple version of bash, and for that I need to mimic the way bash parses content with multiple sets of single and double quotes. I can’t figure out the overall procedure by which bash handles quotes inside quotes. I noticed some repeated patterns but still don’t… Read More How are strings with multiple kinds of quotes interpreted in bash?
Advertisements We have a large table (2.8M rows) where we are finding a single row by our device_token column CREATE TABLE public.rpush_notifications ( id bigint NOT NULL, device_token character varying, data text, created_at timestamp without time zone NOT NULL, updated_at timestamp without time zone NOT NULL, … We are constantly doing the following query: SELECT… Read More Benefit to adding an Index for an order by column?
Advertisements I am training a convolutional neural network for binary time series classification. The training accuracy on both models is very different. If on the first it grows, then on the second it is always about 40%. There were also strong "jumps". Change filters=32/64/128 and epochs didn’t give the best results(kernel_size = 8). self.model =… Read More Deep learning CNN: low accuracy