“column”

I'm trying to add sodas from ListView to ContentView and have that data passed on and update the view in AisleView. I'm having a lot of trouble getting my columnOne and columnTwo properties to update the AisleView correctly. I know the data is being passed to AisleView, but it isn't updating the actual view. I believe the issue is when I'm trying to initialize my columns. Any help would be appreciated. Thank you! class Inventory { var inventory: [Product] = [ Product(name: Coke, price: 2.99, aisle: 1, location: 10), Product(name: Pepsi, price: 3.99, aisle: 1, location: 6), Product(name: Dr. Pepper, price: 1.99, aisle: 2, location: 8), Product(name: Pibb, price: 1.50, aisle: 2, location: 1) ] } struct ListView: View { @State var base = Inventory() @State var sodas: [Product] = [] var body: some View { VStack { ContentView(sodas: $sodas) List { ForEach(base.inventory) { product in HStack { Text(product.name) Spacer() Text((product.price, specifier: %.2f)) Button { sodas.append(product) } label: { Image

Use navigation split view to enable two and three column navigation in your SwiftUI app while maintaining compatibility with earlier OS versions. View Technote TN3154 >

For a tensorflow layer I need a multi column argsort. So I implemented the following function: import tensorflow as tf def multi_column_argsort(tensor, columns_order): sorted_indices = tf.range(start=0, limit=tf.shape(tensor)[0], dtype=tf.int32) for col in reversed(columns_order): col_vals = tf.gather(tensor[:, col], sorted_indices) col_argsort = tf.argsort(col_vals, stable=True) print(Column:, col) print(Column Values:, col_vals.numpy()) print(Col Argsort:, col_argsort.numpy()) print(Sorted Indices Before:, sorted_indices.numpy()) sorted_indices = tf.gather(sorted_indices, col_argsort) print(Sorted Indices After:, sorted_indices.numpy()) print(---) return sorted_indices After debugging this function for a while I found out that it was not sorting the 3 columns as expected because the argsort were not stable i.e. did not respect the previous sorting. To test this I used the following example: points = tf.constant([[1.1, 2.0, 0.1], [1.1, 1.0, 0.2], [2.2, 1.0, 0.1], [1.1, 2.0

I am working on a SwiftData app, and when I query any of the ones with the Predicate (NOT Predicate) I get Query encountered an error: SwiftData.SwiftDataError(_error: SwiftData.SwiftDataError._Error.unsupportedPredicate). The code for my file is below. import SwiftData import SwiftUI struct timeListView: View { @Environment(.modelContext) var modelContext @Query(sort: Time.date, order: .reverse) var times: [Time] @Query(filter: #Predicate { time in time.unfortime! < 6000 }, sort: Time.date, order: .reverse) var timesSub60: [Time] @Query(filter: #Predicate { time in time.unfortime! < 3000 }, sort: Time.date, order: .reverse) var timesSub30: [Time] @Query(filter: #Predicate { time in time.unfortime! < 2000 }, sort: Time.date, order: .reverse) var timesSub20: [Time] @Query(filter: #Predicate { time in time.unfortime! < 1000 }, sort: Time.date, order: .reverse) var timesSub10: [Time] @Query(filter: #Predicate { time in time.unfortime! < 500 }, sort: .date, order: .reverse) var timesSub5: [Time] @Q

Hi, I was about to delete the expired provisioning profiles, meaning the ones where it said Expired in the last column. Now I see there are some more where the expiration date is clearly in the past, but they don't show as expired. Any idea why that is? Kind regards Thomas

I have probably found a bug when indexing tensors with tensorflow-metal. It is best demonstrated by the following minimal example: import tensorflow as tf print(tf.constant([[1, 2], [3, 4]], dtype=tf.float32)[..., :2, 1]) The expected result is [2, 4] (i.e. the second column of the matrix) which is what I get when tensorflow-metal is not installed (and on other non-Apple machines), but using tensorflow-metal I get [2, 2] (i.e. the first element of the column is repeated - this also happens if there are more than two rows). The following conditions seem to be necessary in order to trigger this behavior: dtype must be float32; it works correctly with float64, int32 and int64. the sequence of ellipsis (for batch axes), stride (for row), index (for column) is critical; i.e. it does work correctly when the column is also a stride, and it does work if the row is a single number or the full slice :. the indexed tensor does not actually have batch axes (the ellipsis is there becaus

Hello, Everyone, I'm developing ios app and have a question. one case that screen of my app has multiple tab including each scrollview, when I change tab scroll offset is initialized. Search.Tag is identifiable and id is different each. and FeedListModel is identifiable also. what's the problem, please give me a tip. This is my screenshot and codes. TabView(selection: $model.selected) { ForEach(model.listByTag, id: .key) { (tag, list) in SearchMoreTab( model: model, feedList: list, tag: tag, stickyHeaderHeight: $stickyHeaderHeight, defaultStickyHeaderHeight: defaultStickyHeaderHeight) .tag(tag) } struct SearchMoreTab: View { @ObservedObject var model: SearchMoreModel @ObservedObject var feedList: FeedListModel let tag: Search.Tag @Binding var stickyHeaderHeight: Float let defaultStickyHeaderHeight: Float // scrollableHeight = contentHeight - scrollViewHeight @State var lastScrollOffset: CGFloat = .zero @State var scrollOffset: CGFloat = .zero @State var contentHeight: CGFloat = .zero @State var scrollHeight: