tdf | trading system using real-time data | Business library
kandi X-RAY | tdf Summary
kandi X-RAY | tdf Summary
A paper-trading system for use in studying controls applied to finance.
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QUESTION
The data is basically in CSV format, which is a fasta/genome sequence, basically the whole sequence is a string. To pass this data into a CNN model I convert the data into numeric. The genome/fasta sequence, which I want to change into tensor acceptable format so I convert this string into float e.g., "AACTG,...,AAC.." to [[0.25,0.25,0.50,1.00,0.75],....,[0.25,0.25,0.50.....]]. But the conversion data shows like this (see #data show 2). But, when I run tf.convert_to_tensor(train_data) it gives me an error of Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray). But in order to pass the data into CNN model, it has to be a tensor, but I don't know why it gives an error! What will be the solution to it?
...ANSWER
Answered 2021-Jun-10 at 21:47The problem is probably in your numpy array dtype.
Using array with dtype float32
should fix problem: tf.convert_to_tensor(train_data.astype(np.float32))
QUESTION
I am using some code that I found at AllenBrowne.com, which works fine, but I have a question about what it's doing.
The code is designed to return information about any index found on a specific column of a table in MS Access. Index types are identified with a constant, and there are four possible index types (including None):
...ANSWER
Answered 2021-May-21 at 13:01The bitwise OR is useful in cases where combinations of values can exist, and you'd want to return an additive value. In this specific code block, the code is looping through each of the indices, and setting the flag based on the specific index. If there are two indexes, and one of them is general and the other is primary, you can encode this information in resultant bit pattern.
I'm confused by the choice of bitmaps, though. By choosing values with all of the bits set to true, you'd lose information about individual items (maybe that's a design element).
Generally, bitmaps might look something like:
QUESTION
My dataframe (tdf) has a column called Age that contains a list of ages between 0 and 86. I want to create a new column in the dataframe called age_groups and populate it with a label based on that rows Age value. The code I'm using to do that is:
...ANSWER
Answered 2021-May-18 at 00:48You can try using pandas.DataFrame.loc
.
QUESTION
I have the following data, with each row per ID and DATE. A person with the same ID can occupy multiple rows, hence multiple dates. I want to aggregate it into one person (or ID) per row, and the dates will be aggregated into a list of date
From this
...ANSWER
Answered 2021-Apr-22 at 04:16Simply use groupby()
and apply()
method:
QUESTION
I have a dataframe like as shown below
...ANSWER
Answered 2021-Apr-12 at 10:10You can use
QUESTION
I am using a file dialog
to relinking tables to a backend and then changing the mapped drive connection string of the link tables to UNC
links. However I haven't been that lucky, I have come through the following problems:
1. The code below doesn't work as expected if the link is already a UNC
link. I want to relink with the updated location.
2. Can the sub uncLink
use a loop? I tried a For
loop but without success.
Please see below:
...ANSWER
Answered 2021-Mar-31 at 17:51Following works for me:
QUESTION
This problem occurred when I used chipyard to compile Boom. Is this because of insufficient memory? I am running on a 1 core 2G cloud server.
/bin/bash: line 1: 9986 Killed java -Xmx8G -Xss8M -XX:MaxPermSize=256M -jar /home/cuiyujie/workspace/Boom/chipyard/generators/rocket-chip/sbt-launch.jar -Dsbt.sourcemode=true -Dsbt.workspace=/home/cuiyujie/workspace/Boom/chipyard/tools ";project utilities; runMain utilities.GenerateSimFiles -td /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig -sim verilator" /home/cuiyujie/workspace/Boom/chipyard/common.mk:86: recipe for target '/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/sim_files.f' failed make: *** [/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/sim_files.f] Error 137
When I adjusted the memory to 4G, this appeared.
Done elaborating. OpenJDK 64-Bit Server VM warning: INFO: os::commit_memory(0x00000006dc3b7000, 97148928, 0) failed; error='Cannot allocate memory' (errno=12)
There is insufficient memory for the Java Runtime Environment to continue. Native memory allocation (mmap) failed to map 97148928 bytes for committing reserved memory. An error report file with more information is saved as: /home/cuiyujie/workspace/Boom/chipyard/hs_err_pid2876.log /home/cuiyujie/workspace/Boom/chipyard/common.mk:97: recipe for target 'generator_temp' failed make: *** [generator_temp] Error 1
Should I adjust to 8G memory, or through what command to increase the memory size that the process can use?
When I adjusted the memory to 16G, this appeared.
.../bin/bash: line 1: 2642 Killed java -Xmx8G -Xss8M -XX:MaxPermSize=256M -jar /home/cuiyujie/workspace/Boom/chipyard/generators/rocket-chip/sbt-launch.jar -Dsbt.sourcemode=true -Dsbt.workspace=/home/cuiyujie/workspace/Boom/chipyard/tools ";project tapeout; runMain barstools.tapeout.transforms.GenerateTopAndHarness -o /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.v -tho /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.v -i /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.fir --syn-top ChipTop --harness-top TestHarness -faf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.anno.json -tsaof /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.anno.json -tdf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/firrtl_black_box_resource_files.top.f -tsf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.fir -thaof /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.anno.json -hdf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/firrtl_black_box_resource_files.harness.f -thf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.fir --infer-rw --repl-seq-mem -c:TestHarness:-o:/home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.top.mems.conf -thconf /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig/chipyard.TestHarness.LargeBoomConfig.harness.mems.conf -td /home/cuiyujie/workspace/Boom/chipyard/sims/verilator/generated-src/chipyard.TestHarness.LargeBoomConfig -ll error" /home/cuiyujie/workspace/Boom/chipyard/common.mk:123: recipe for target 'firrtl_temp' failed make: *** [firrtl_temp] Error 137
ANSWER
Answered 2021-Mar-09 at 03:23Short anwer : yes
Error 137
is thrown when your host runs out of memory.
"I am running on a 1 core 2G cloud server"
When you try to assign 8GB to the JVM, OOM-Killer
says "no-no, f... no way", and kicks in sending a SIGKILL
; This Killer is a proactive process that jumps in to save the system when its memory level goes too low, by killing the resource-abusive processes.
In this case, the abusive process (very abusive, indeed) is your java program, which is trying to allocate more than(*) 4 times the maximum avaliable memory in your host.
QUESTION
My co-workers have a bottleneck. Updating contact information in our CRM via bounced e-mails. They have a LOT of emails to wade through considering many are just "out of office" emails.
Here is the full code I have so far:
...ANSWER
Answered 2021-Mar-16 at 13:02You can create regex patterns that better match your phone number variations. Your comments only indicate a single pattern (###-###-####
) your three regexes will return many strings that do not match that pattern. To match that particular pattern, I'd suggest \b\d{3}-\d{3}-\d{4}\b
but that might be too restrictive. You really need to look at the possible patterns more closely. Given the patterns in your code, in addition to the mismatches you mention, one of them would also match 1,,456---89147
clearly not a phone number.
I don't know if the regex is your only problem. Also, I don't understand (at least with North American phone numbers, your possible pattern of 8 digits. I could understand 7 digits. For North American phone numbers, not taking into account international numbers, the following regex will match, including that 10 digit string; and won't match the USC citation:
QUESTION
Similar to my previous question, but this time fighting with tidyverse solution of the problem.
...ANSWER
Answered 2021-Mar-10 at 16:16A combination of separate_rows from tidyr and a grouped summarise seems to work:
QUESTION
I have two pyspark dataframe tdf
and fdf
, where fdf
is extremely larger than tdf
. And the sizes of these dataframes are changing daily, and I don't know them. I want to randomly pick data from fdf
to compose a new dataframe rdf
, where size of rdf
is approximately equal to the size of tdf
. Currently I have these lines:
ANSWER
Answered 2021-Jan-30 at 07:59You can try sampling from the dataframe to get an estimated count:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tdf
Note that this installation has only been tested using Ubuntu 13.10.
Follow the instructions here. For Ubuntu (recommended):.
Install both grunt, the grunt client, and bower globally by:.
Follow the instructions here. In brief:.
Follow the directions here to enable npm to install packages locally. In brief:.
TDF must make repetitive calls to Yahoo Finance in order to collect and store temporal pricing information as well as the value of the agents' portfolios over time. Such calls can be performed manually by opening the URL <host>:<port>/maketick. However, we recommend that this be performed automatically on the host machine using a scheduled chronjob. Further, we recommend that this be performed every hour on the hour while the markets are open (any more frequent than this and TDF stops performing well, and even at this tick rate, TDF slows down and becomes almost unusable with 30 agents after about a month). To aid in creating this crontab entry, we have provided two scripts, tickercron3000 and tickercron80, the former of which assumes that TDF is being run on port 3000 of the local machine and the later assumes that TDF is being run on port 80 of the local machine. Add the crontab entry with. and verify that the entry has been added by viewing the crontab with.
Once you have installed TDF, you will need to begin by creating a league. To do this, you will need an admin account. For now, an admin account is created by registering an account with the username admin (this will be changed in the future for greater security and flexibility of admins). After loging in with the admin account, click on Leagues in the top navigation bar, and then click the button to add a league. Enter a name of the league and then, if you wish, modify the rest of the league parameters. Now that you have a league, you and other users can register agents to trade and compete within this league. See idealabs/byu.edu/Features/TDF.php for more information.
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