diff options
27 files changed, 2073 insertions, 796 deletions
diff --git a/misc/notes.txt b/misc/notes.txt index 5a43ab8a..f8ce2759 100644 --- a/misc/notes.txt +++ b/misc/notes.txt @@ -273,6 +273,12 @@ grep -ir (search string) (directory) =========================================== +Command line arguments: + +Use argparse to deal with command line arguments (instead of argv or optparse) + +=========================================== + Change owner/group: chown zas1024 somefile (change owner of somefile to zas1024) diff --git a/wqflask/base/data_set.py b/wqflask/base/data_set.py index fbe78d5d..3deaa655 100755 --- a/wqflask/base/data_set.py +++ b/wqflask/base/data_set.py @@ -168,13 +168,13 @@ class Markers(object): for marker, p_value in itertools.izip(self.markers, p_values): marker['p_value'] = p_value - if math.isnan(marker['p_value']): - print("p_value is:", marker['p_value']) - marker['lod_score'] = -math.log10(marker['p_value']) - #Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values - marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61 - - + if math.isnan(marker['p_value']) or marker['p_value'] <= 0: + marker['lod_score'] = 0 + marker['lrs_value'] = 0 + else: + marker['lod_score'] = -math.log10(marker['p_value']) + #Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values + marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61 class HumanMarkers(Markers): @@ -184,6 +184,7 @@ class HumanMarkers(Markers): self.markers = [] for line in marker_data_fh: splat = line.strip().split() + #print("splat:", splat) marker = {} marker['chr'] = int(splat[0]) marker['name'] = splat[1] @@ -203,6 +204,7 @@ class HumanMarkers(Markers): # #Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values # marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61 + print("p_values2:", p_values) super(HumanMarkers, self).add_pvalues(p_values) with Bench("deleting markers"): diff --git a/wqflask/wqflask/marker_regression/marker_regression.py b/wqflask/wqflask/marker_regression/marker_regression.py index 006c586b..0dd55729 100755 --- a/wqflask/wqflask/marker_regression/marker_regression.py +++ b/wqflask/wqflask/marker_regression/marker_regression.py @@ -7,16 +7,20 @@ from pprint import pformat as pf import string import sys +import datetime import os import collections +import uuid import numpy as np from scipy import linalg -import simplejson as json +import cPickle as pickle -#from redis import Redis +import simplejson as json +from redis import Redis +Redis = Redis() from base.trait import GeneralTrait from base import data_set @@ -38,7 +42,7 @@ class MarkerRegression(object): helper_functions.get_species_dataset_trait(self, start_vars) - tempdata = temp_data.TempData(temp_uuid) + #tempdata = temp_data.TempData(temp_uuid) self.samples = [] # Want only ones with values self.vals = [] @@ -48,7 +52,9 @@ class MarkerRegression(object): self.samples.append(str(sample)) self.vals.append(value) - self.gen_data(tempdata) + #self.qtl_results = self.gen_data(tempdata) + self.qtl_results = self.gen_data(str(temp_uuid)) + self.lod_cutoff = self.get_lod_score_cutoff() #Get chromosome lengths for drawing the manhattan plot chromosome_mb_lengths = {} @@ -61,15 +67,23 @@ class MarkerRegression(object): ) - def gen_data(self, tempdata): + #def gen_data(self, tempdata): + def gen_data(self, temp_uuid): """Generates p-values for each marker""" self.dataset.group.get_markers() pheno_vector = np.array([val == "x" and np.nan or float(val) for val in self.vals]) + #lmm_uuid = str(uuid.uuid4()) + + key = "pylmm:input:" + temp_uuid + print("key is:", pf(key)) + #with Bench("Loading cache"): + # result = Redis.get(key) + if self.dataset.group.species == "human": - p_values, t_stats = self.gen_human_results(pheno_vector, tempdata) + p_values, t_stats = self.gen_human_results(pheno_vector, key, temp_uuid) else: genotype_data = [marker['genotypes'] for marker in self.dataset.group.markers.markers] @@ -77,24 +91,66 @@ class MarkerRegression(object): trimmed_genotype_data = self.trim_genotypes(genotype_data, no_val_samples) genotype_matrix = np.array(trimmed_genotype_data).T + + #print("pheno_vector: ", pf(pheno_vector)) + #print("genotype_matrix: ", pf(genotype_matrix)) + #print("genotype_matrix.shape: ", pf(genotype_matrix.shape)) + + #params = {"pheno_vector": pheno_vector, + # "genotype_matrix": genotype_matrix, + # "restricted_max_likelihood": True, + # "refit": False, + # "temp_data": tempdata} - print("pheno_vector: ", pf(pheno_vector)) - print("genotype_matrix: ", pf(genotype_matrix)) - print("genotype_matrix.shape: ", pf(genotype_matrix.shape)) + params = dict(pheno_vector = pheno_vector.tolist(), + genotype_matrix = genotype_matrix.tolist(), + restricted_max_likelihood = True, + refit = False, + temp_uuid = temp_uuid, + + # meta data + timestamp = datetime.datetime.now().isoformat(), + ) - t_stats, p_values = lmm.run( - pheno_vector, - genotype_matrix, - restricted_max_likelihood=True, - refit=False, - temp_data=tempdata - ) - + json_params = json.dumps(params) + print("json_params:", json_params) + Redis.set(key, json_params) + Redis.expire(key, 60*60) + print("before printing command") + + command = 'python /home/zas1024/gene/wqflask/wqflask/my_pylmm/pyLMM/lmm.py --key {} --species {}'.format(key, + "other") + print("command is:", command) + print("after printing command") + + os.system(command) + + #t_stats, p_values = lmm.run(key) + #lmm.run(key) + + json_results = Redis.blpop("pylmm:results:" + temp_uuid, 45*60) + results = json.loads(json_results[1]) + p_values = results['p_values'] + t_stats = results['t_stats'] + + #t_stats, p_values = lmm.run( + # pheno_vector, + # genotype_matrix, + # restricted_max_likelihood=True, + # refit=False, + # temp_data=tempdata + #) + #print("p_values:", p_values) + self.dataset.group.markers.add_pvalues(p_values) - self.qtl_results = self.dataset.group.markers.markers + + self.get_lod_score_cutoff() + + return self.dataset.group.markers.markers - def gen_human_results(self, pheno_vector, tempdata): + #def gen_human_results(self, pheno_vector, tempdata): + def gen_human_results(self, pheno_vector, key, temp_uuid): file_base = os.path.join(webqtlConfig.PYLMM_PATH, self.dataset.group.name) plink_input = input.plink(file_base, type='b') @@ -105,16 +161,62 @@ class MarkerRegression(object): kinship_matrix = np.fromfile(open(file_base + '.kin','r'),sep=" ") kinship_matrix.resize((len(plink_input.indivs),len(plink_input.indivs))) - p_values, t_stats = lmm.run_human( - pheno_vector, - covariate_matrix, - input_file_name, - kinship_matrix, - loading_progress=tempdata - ) + print("Before creating params") + + params = dict(pheno_vector = pheno_vector.tolist(), + covariate_matrix = covariate_matrix.tolist(), + input_file_name = input_file_name, + kinship_matrix = kinship_matrix.tolist(), + refit = False, + temp_uuid = temp_uuid, + + # meta data + timestamp = datetime.datetime.now().isoformat(), + ) + + print("After creating params") + + json_params = json.dumps(params) + Redis.set(key, json_params) + Redis.expire(key, 60*60) + + print("Before creating the command") + + command = 'python /home/zas1024/gene/wqflask/wqflask/my_pylmm/pyLMM/lmm.py --key {} --species {}'.format(key, + "human") + + print("command is:", command) + + os.system(command) + + json_results = Redis.blpop("pylmm:results:" + temp_uuid, 45*60) + results = json.loads(json_results[1]) + t_stats = results['t_stats'] + p_values = results['p_values'] + + + #p_values, t_stats = lmm.run_human(key) + + #p_values, t_stats = lmm.run_human( + # pheno_vector, + # covariate_matrix, + # input_file_name, + # kinship_matrix, + # loading_progress=tempdata + # ) return p_values, t_stats + def get_lod_score_cutoff(self): + high_qtl_count = 0 + for marker in self.dataset.group.markers.markers: + if marker['lod_score'] > 2: + high_qtl_count += 1 + + if high_qtl_count > 10000: + return 1 + else: + return 2 def identify_empty_samples(self): no_val_samples = [] @@ -157,6 +259,11 @@ def create_snp_iterator_file(group): with gzip.open(snp_file_base, "wb") as fh: pickle.dump(data, fh, pickle.HIGHEST_PROTOCOL) +#if __name__ == '__main__': +# import cPickle as pickle +# import gzip +# create_snp_iterator_file("HLC") + if __name__ == '__main__': import cPickle as pickle import gzip diff --git a/wqflask/wqflask/my_pylmm/data/genofile_parser.py b/wqflask/wqflask/my_pylmm/data/genofile_parser.py index 4a647959..4ebadb6e 100644 --- a/wqflask/wqflask/my_pylmm/data/genofile_parser.py +++ b/wqflask/wqflask/my_pylmm/data/genofile_parser.py @@ -93,12 +93,12 @@ class ConvertGenoFile(object): this_marker = Marker() this_marker.name = row_items[1] this_marker.chr = row_items[0] - this_marker.cM = row_items[2] + #this_marker.cM = row_items[2] if self.mb_exists: - this_marker.Mb = row_items[3] - genotypes = row_items[4:] - else: + this_marker.Mb = row_items[2] genotypes = row_items[3:] + else: + genotypes = row_items[2:] for item_count, genotype in enumerate(genotypes): if genotype.upper() in self.configurations: this_marker.genotypes.append(self.configurations[genotype.upper()]) @@ -106,8 +106,8 @@ class ConvertGenoFile(object): this_marker.genotypes.append("NA") #print("this_marker is:", pf(this_marker.__dict__)) - - self.markers.append(this_marker.__dict__) + if this_marker.chr == "14": + self.markers.append(this_marker.__dict__) with open(self.output_file, 'w') as fh: json.dump(self.markers, fh, indent=" ", sort_keys=True) @@ -125,8 +125,8 @@ class ConvertGenoFile(object): def process_rows(self): for self.latest_row_pos, row in enumerate(self.input_fh): - if self.input_file.endswith(".geno.gz"): - print("row: ", row) + #if self.input_file.endswith(".geno.gz"): + # print("row: ", row) self.latest_row_value = row # Take care of headers if not row.strip(): @@ -186,8 +186,10 @@ if __name__=="__main__": Old_Geno_Directory = """/home/zas1024/gene/web/genotypes/""" New_Geno_Directory = """/home/zas1024/gene/web/new_genotypes/""" #Input_File = """/home/zas1024/gene/web/genotypes/BXD.geno""" - #Output_File = """/home/zas1024/gene/wqflask/wqflask/pylmm/data/bxd.snps""" - ConvertGenoFile.process_all(Old_Geno_Directory, New_Geno_Directory) + #Output_File = """/home/zas1024/gene/wqflask/wqflask/pylmm/data/bxd.snps""" + convertob = ConvertGenoFile("/home/zas1024/gene/web/genotypes/HSNIH.geno.gz", "/home/zas1024/gene/web/new_genotypes/HSNIH.json") + convertob.convert() + #ConvertGenoFile.process_all(Old_Geno_Directory, New_Geno_Directory) #ConvertGenoFiles(Geno_Directory) #process_csv(Input_File, Output_File) \ No newline at end of file diff --git a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py index 60d36b8d..a0ff31ef 100644..100755 --- a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py +++ b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py @@ -19,6 +19,7 @@ from __future__ import absolute_import, print_function, division import sys import time +import argparse import uuid import numpy as np @@ -27,6 +28,8 @@ from scipy import optimize from scipy import stats import pdb +import simplejson as json + import gzip import zlib import datetime @@ -35,22 +38,34 @@ import simplejson as json from pprint import pformat as pf +from redis import Redis +Redis = Redis() + +import sys +sys.path.append("/home/zas1024/gene/wqflask/") +print("sys.path2:", sys.path) + from utility.benchmark import Bench from utility import temp_data from wqflask.my_pylmm.pyLMM import chunks -import redis -Redis = redis.Redis() #np.seterr('raise') +#def run_human(pheno_vector, +# covariate_matrix, +# plink_input_file, +# kinship_matrix, +# refit=False, +# loading_progress=None): + def run_human(pheno_vector, covariate_matrix, plink_input_file, kinship_matrix, refit=False, - loading_progress=None): + tempdata=None): v = np.isnan(pheno_vector) keep = True - v @@ -58,17 +73,17 @@ def run_human(pheno_vector, identifier = str(uuid.uuid4()) - print("pheno_vector: ", pf(pheno_vector)) - print("kinship_matrix: ", pf(kinship_matrix)) - print("kinship_matrix.shape: ", pf(kinship_matrix.shape)) - - lmm_vars = pickle.dumps(dict( - pheno_vector = pheno_vector, - covariate_matrix = covariate_matrix, - kinship_matrix = kinship_matrix - )) - Redis.hset(identifier, "lmm_vars", lmm_vars) - Redis.expire(identifier, 60*60) + #print("pheno_vector: ", pf(pheno_vector)) + #print("kinship_matrix: ", pf(kinship_matrix)) + #print("kinship_matrix.shape: ", pf(kinship_matrix.shape)) + + #lmm_vars = pickle.dumps(dict( + # pheno_vector = pheno_vector, + # covariate_matrix = covariate_matrix, + # kinship_matrix = kinship_matrix + #)) + #Redis.hset(identifier, "lmm_vars", lmm_vars) + #Redis.expire(identifier, 60*60) if v.sum(): pheno_vector = pheno_vector[keep] @@ -136,13 +151,13 @@ def run_human(pheno_vector, #print("***** Added to {} queue *****".format(key)) for snp, this_id in plink_input: #with Bench("part before association"): - #if count > 2000: + #if count > 1000: # break count += 1 percent_complete = (float(count) / total_snps) * 100 #print("percent_complete: ", percent_complete) - loading_progress.store("percent_complete", percent_complete) + tempdata.store("percent_complete", percent_complete) #with Bench("actual association"): ps, ts = human_association(snp, @@ -218,11 +233,17 @@ def human_association(snp, return ps, ts -def run(pheno_vector, +#def run(pheno_vector, +# genotype_matrix, +# restricted_max_likelihood=True, +# refit=False, +# temp_data=None): + +def run_other(pheno_vector, genotype_matrix, restricted_max_likelihood=True, refit=False, - temp_data=None): + tempdata=None): """Takes the phenotype vector and genotype matrix and returns a set of p-values and t-statistics restricted_max_likelihood -- whether to use restricted max likelihood; True or False @@ -232,8 +253,10 @@ def run(pheno_vector, """ + + print("In run_other") with Bench("Calculate Kinship"): - kinship_matrix = calculate_kinship(genotype_matrix, temp_data) + kinship_matrix = calculate_kinship(genotype_matrix, tempdata) print("kinship_matrix: ", pf(kinship_matrix)) print("kinship_matrix.shape: ", pf(kinship_matrix.shape)) @@ -252,9 +275,9 @@ def run(pheno_vector, kinship_matrix, restricted_max_likelihood=True, refit=False, - temp_data=temp_data) + temp_data=tempdata) Bench().report() - return t_stats, p_values + return p_values, t_stats def matrixMult(A,B): @@ -677,3 +700,48 @@ class LMM: pl.xlabel("Heritability") pl.ylabel("Probability of data") pl.title(title) + +def main(): + parser = argparse.ArgumentParser(description='Run pyLMM') + parser.add_argument('-k', '--key') + parser.add_argument('-s', '--species') + + opts = parser.parse_args() + + key = opts.key + species = opts.species + + json_params = Redis.get(key) + + params = json.loads(json_params) + print("params:", params) + + tempdata = temp_data.TempData(params['temp_uuid']) + if species == "human" : + ps, ts = run_human(pheno_vector = np.array(params['pheno_vector']), + covariate_matrix = np.array(params['covariate_matrix']), + plink_input_file = params['input_file_name'], + kinship_matrix = np.array(params['kinship_matrix']), + refit = params['refit'], + tempdata = tempdata) + else: + ps, ts = run_other(pheno_vector = np.array(params['pheno_vector']), + genotype_matrix = np.array(params['genotype_matrix']), + restricted_max_likelihood = params['restricted_max_likelihood'], + refit = params['refit'], + tempdata = tempdata) + + results_key = "pylmm:results:" + params['temp_uuid'] + + json_results = json.dumps(dict(p_values = ps, + t_stats = ts)) + + #Pushing json_results into a list where it is the only item because blpop needs a list + Redis.rpush(results_key, json_results) + Redis.expire(results_key, 60*60) + +if __name__ == '__main__': + main() + + + diff --git a/wqflask/wqflask/my_pylmm/run_pylmm.py b/wqflask/wqflask/my_pylmm/run_pylmm.py new file mode 100644 index 00000000..0c96d986 --- /dev/null +++ b/wqflask/wqflask/my_pylmm/run_pylmm.py @@ -0,0 +1,77 @@ +from __future__ import absolute_import, print_function, division + +from base import data_set +from base.species import TheSpecies + + def run(dataset_name, vals, temp_uuid): + """Generates p-values for each marker""" + + tempdata = temp_data.TempData(temp_uuid) + + dataset = data_set.create_dataset(dataset_name) + species = TheSpecies(dataset=dataset) + + samples = [] # Want only ones with values + vals = vals + + for sample in dataset.group.samplelist: + samples.append(str(sample)) + + gen_data(dataset, vals, tempdata) + + + def gen_data(dataset, vals) + dataset.group.get_markers() + + pheno_vector = np.array([val == "x" and np.nan or float(val) for val in vals]) + + if dataset.group.species == "human": + p_values, t_stats = gen_human_results(pheno_vector, tempdata) + else: + genotype_data = [marker['genotypes'] for marker in dataset.group.markers.markers] + + no_val_samples = self.identify_empty_samples() + trimmed_genotype_data = self.trim_genotypes(genotype_data, no_val_samples) + + genotype_matrix = np.array(trimmed_genotype_data).T + + #print("pheno_vector: ", pf(pheno_vector)) + #print("genotype_matrix: ", pf(genotype_matrix)) + #print("genotype_matrix.shape: ", pf(genotype_matrix.shape)) + + t_stats, p_values = lmm.run( + pheno_vector, + genotype_matrix, + restricted_max_likelihood=True, + refit=False, + temp_data=tempdata + ) + #print("p_values:", p_values) + + self.dataset.group.markers.add_pvalues(p_values) + return self.dataset.group.markers.markers + + + def gen_human_results(self, pheno_vector, tempdata): + file_base = os.path.join(webqtlConfig.PYLMM_PATH, self.dataset.group.name) + + plink_input = input.plink(file_base, type='b') + input_file_name = os.path.join(webqtlConfig.SNP_PATH, self.dataset.group.name + ".snps.gz") + + pheno_vector = pheno_vector.reshape((len(pheno_vector), 1)) + covariate_matrix = np.ones((pheno_vector.shape[0],1)) + kinship_matrix = np.fromfile(open(file_base + '.kin','r'),sep=" ") + kinship_matrix.resize((len(plink_input.indivs),len(plink_input.indivs))) + + p_values, t_stats = lmm.run_human( + pheno_vector, + covariate_matrix, + input_file_name, + kinship_matrix, + loading_progress=tempdata + ) + + return p_values, t_stats + +if __name__ == '__main__': + run(dataset_name, vals, temp_uuid) \ No newline at end of file diff --git a/wqflask/wqflask/static/new/css/bar_chart.css b/wqflask/wqflask/static/new/css/bar_chart.css index ba14fe4e..c8e081f9 100644 --- a/wqflask/wqflask/static/new/css/bar_chart.css +++ b/wqflask/wqflask/static/new/css/bar_chart.css @@ -7,6 +7,7 @@ .bar { fill: steelblue; + shape-rendering: crispEdges; } .x.axis path { diff --git a/wqflask/wqflask/static/new/css/marker_regression.css b/wqflask/wqflask/static/new/css/marker_regression.css index a737c97e..56980026 100644 --- a/wqflask/wqflask/static/new/css/marker_regression.css +++ b/wqflask/wqflask/static/new/css/marker_regression.css @@ -15,10 +15,17 @@ stroke: black; shape-rendering: crispEdges; } + .manhattan_plot .x_axis text { text-anchor: end; font-family: sans-serif; - font-size: 8px; + font-size: 10px; +} + +rect.pane { + cursor: move; + fill: none; + pointer-events: all; } /*rect { diff --git a/wqflask/wqflask/static/new/javascript/bar_chart.coffee b/wqflask/wqflask/static/new/javascript/bar_chart.coffee index e1bb36e1..3f12d956 100644 --- a/wqflask/wqflask/static/new/javascript/bar_chart.coffee +++ b/wqflask/wqflask/static/new/javascript/bar_chart.coffee @@ -129,89 +129,31 @@ class Bar_Chart #$('.x.axis').remove() #@add_x_axis(x_scale) ) - - - - #d3.select(".update_bar_chart").on("click", => - # console.log("THIS IS:", $(this)) - # sort_by = $(this).val() - # console.log("sort_by: ", sort_by) - # if @attributes.length > 0 - # attribute = $("#color_attribute").val() - # if sort_by = "value" - # console.log("sorting by value") - # sortItems = (a, b) -> - # return a[1] - b[1] - # - # @svg.selectAll(".bar") - # .data(@sorted_samples()) - # .transition() - # .duration(1000) - # .attr("y", (d) => - # - # return @y_scale(d[1]) - # ) - # .attr("height", (d) => - # return @plot_height - @y_scale(d[1]) - # ) - # .style("fill", (d) => - # if @attributes.length > 0 - # return @attr_color_dict[attribute][d[2][attribute]] - # else - # return "steelblue" - # ) - # .select("title") - # .text((d) => - # return d[1] - # ) - # sorted_sample_names = (sample[0] for sample in @sorted_samples()) - # x_scale = d3.scale.ordinal() - # .domain(sorted_sample_names) - # .rangeBands([0, @plot_width], .1) - # $('.x.axis').remove() - # @add_x_axis(x_scale) - # else - # console.log("sorting by name") - # #$("#update_bar_chart").html('Sort By Value') - # @svg.selectAll(".bar") - # .data(@samples) - # .transition() - # .duration(1000) - # .attr("y", (d) => - # return @y_scale(d[1]) - # ) - # .attr("height", (d) => - # return @plot_height - @y_scale(d[1]) - # ) - # .style("fill", (d) => - # if @attributes.length > 0 - # return @attr_color_dict[attribute][d[2][attribute]] - # else - # return "steelblue" - # ) - # .select("title") - # .text((d) => - # return d[1] - # ) - # x_scale = d3.scale.ordinal() - # .domain(@sample_names) - # .rangeBands([0, @plot_width], .1) - # $('.x.axis').remove() - # @add_x_axis(x_scale) - #) - + d3.select("#color_by_trait").on("click", => @open_trait_selection() - ) - rebuild_bar_graph: (samples) -> console.log("samples:", samples) @svg.selectAll(".bar") .data(samples) .transition() .duration(1000) + .style("fill", (d) => + if @attributes.length == 0 and @trait_color_dict? + console.log("SAMPLE:", d[0]) + console.log("CHECKING:", @trait_color_dict[d[0]]) + #return "steelblue" + return @trait_color_dict[d[0]] + else if @attributes.length > 0 and @attribute != "None" + console.log("@attribute:", @attribute) + console.log("d[2]", d[2]) + console.log("the_color:", @attr_color_dict[@attribute][d[2][@attribute]]) + return @attr_color_dict[@attribute][d[2][@attribute]] + else + return "steelblue" + ) .attr("y", (d) => return @y_scale(d[1]) ) @@ -222,15 +164,10 @@ class Bar_Chart .text((d) => return d[1] ) - .style("fill", (d) => - if @attributes.length > 0 and @attribute != "None" - console.log("@attribute:", @attribute) - console.log("d[2]", d[2]) - console.log("the_color:", @attr_color_dict[@attribute][d[2][@attribute]]) - return @attr_color_dict[@attribute][d[2][@attribute]] - else - return "steelblue" - ) + #.style("fill", (d) => + # return @trait_color_dict[d[0]] + # #return @attr_color_dict["collection_trait"][trimmed_samples[d[0]]] + #) sample_names = (sample[0] for sample in samples) console.log("sample_names2:", sample_names) x_scale = d3.scale.ordinal() @@ -268,6 +205,35 @@ class Bar_Chart #this_color_dict[value] = d3.rgb("lightblue").darker(color_range(parseInt(value))) #this_color_dict[value] = "rgb(0, 0, " + color_range(parseInt(value)) + ")" @attr_color_dict[key] = this_color_dict + + get_trait_color_dict: (samples, vals) -> + @trait_color_dict = {} + console.log("vals:", vals) + for own key, distinct_vals of vals + this_color_dict = {} + if distinct_vals.length < 10 + color = d3.scale.category10() + for value, i in distinct_vals + this_color_dict[value] = color(i) + else + console.log("distinct_values:", distinct_vals) + #Check whether all values are numbers, and if they are get a corresponding + #color gradient + if _.every(distinct_vals, (d) => + if isNaN(d) + return false + else + return true + ) + color_range = d3.scale.linear() + .domain([d3.min(distinct_vals), + d3.max(distinct_vals)]) + .range([0,255]) + for value, i in distinct_vals + console.log("color_range(value):", parseInt(color_range(value))) + this_color_dict[value] = d3.rgb(parseInt(color_range(value)),0, 0) + for own sample, value of samples + @trait_color_dict[sample] = this_color_dict[value] convert_into_colors: (values) -> color_range = d3.scale.linear() @@ -450,29 +416,38 @@ class Bar_Chart trimmed_samples = @trim_values(trait_sample_data) distinct_values = {} distinct_values["collection_trait"] = @get_distinct_values(trimmed_samples) - @get_attr_color_dict(distinct_values) - if $("#update_bar_chart").html() == 'Sort By Name' + #@get_attr_color_dict(distinct_values) + @get_trait_color_dict(trimmed_samples, distinct_values) + console.log("TRAIT_COLOR_DICT:", @trait_color_dict) + console.log("SAMPLES:", @samples) + if @sort_by = "value" @svg.selectAll(".bar") - .data(@sorted_samples()) + .data(@samples) .transition() .duration(1000) .style("fill", (d) => - return @attr_color_dict["collection_trait"][trimmed_samples[d[0]]] + console.log("this color:", @trait_color_dict[d[0]]) + return @trait_color_dict[d[0]] ) .select("title") .text((d) => return d[1] - ) + ) + else @svg.selectAll(".bar") - .data(@samples) + .data(@sorted_samples()) .transition() .duration(1000) .style("fill", (d) => - return @attr_color_dict["collection_trait"][trimmed_samples[d[0]]] + console.log("this color:", @trait_color_dict[d[0]]) + return @trait_color_dict[d[0]] ) - - + .select("title") + .text((d) => + return d[1] + ) + trim_values: (trait_sample_data) -> trimmed_samples = {} for sample in @sample_names diff --git a/wqflask/wqflask/static/new/javascript/bar_chart.js b/wqflask/wqflask/static/new/javascript/bar_chart.js index b02ee1da..c0b056f8 100644 --- a/wqflask/wqflask/static/new/javascript/bar_chart.js +++ b/wqflask/wqflask/static/new/javascript/bar_chart.js @@ -95,14 +95,12 @@ var sample, sample_names, x_scale, _this = this; console.log("samples:", samples); - this.svg.selectAll(".bar").data(samples).transition().duration(1000).attr("y", function(d) { - return _this.y_scale(d[1]); - }).attr("height", function(d) { - return _this.plot_height - _this.y_scale(d[1]); - }).select("title").text(function(d) { - return d[1]; - }).style("fill", function(d) { - if (_this.attributes.length > 0 && _this.attribute !== "None") { + this.svg.selectAll(".bar").data(samples).transition().duration(1000).style("fill", function(d) { + if (_this.attributes.length === 0 && (_this.trait_color_dict != null)) { + console.log("SAMPLE:", d[0]); + console.log("CHECKING:", _this.trait_color_dict[d[0]]); + return _this.trait_color_dict[d[0]]; + } else if (_this.attributes.length > 0 && _this.attribute !== "None") { console.log("@attribute:", _this.attribute); console.log("d[2]", d[2]); console.log("the_color:", _this.attr_color_dict[_this.attribute][d[2][_this.attribute]]); @@ -110,6 +108,12 @@ } else { return "steelblue"; } + }).attr("y", function(d) { + return _this.y_scale(d[1]); + }).attr("height", function(d) { + return _this.plot_height - _this.y_scale(d[1]); + }).select("title").text(function(d) { + return d[1]; }); sample_names = (function() { var _i, _len, _results; @@ -164,6 +168,48 @@ return _results; }; + Bar_Chart.prototype.get_trait_color_dict = function(samples, vals) { + var color, color_range, distinct_vals, i, key, sample, this_color_dict, value, _i, _j, _len, _len1, _results, + _this = this; + this.trait_color_dict = {}; + console.log("vals:", vals); + for (key in vals) { + if (!__hasProp.call(vals, key)) continue; + distinct_vals = vals[key]; + this_color_dict = {}; + if (distinct_vals.length < 10) { + color = d3.scale.category10(); + for (i = _i = 0, _len = distinct_vals.length; _i < _len; i = ++_i) { + value = distinct_vals[i]; + this_color_dict[value] = color(i); + } + } else { + console.log("distinct_values:", distinct_vals); + if (_.every(distinct_vals, function(d) { + if (isNaN(d)) { + return false; + } else { + return true; + } + })) { + color_range = d3.scale.linear().domain([d3.min(distinct_vals), d3.max(distinct_vals)]).range([0, 255]); + for (i = _j = 0, _len1 = distinct_vals.length; _j < _len1; i = ++_j) { + value = distinct_vals[i]; + console.log("color_range(value):", parseInt(color_range(value))); + this_color_dict[value] = d3.rgb(parseInt(color_range(value)), 0, 0); + } + } + } + } + _results = []; + for (sample in samples) { + if (!__hasProp.call(samples, sample)) continue; + value = samples[sample]; + _results.push(this.trait_color_dict[sample] = this_color_dict[value]); + } + return _results; + }; + Bar_Chart.prototype.convert_into_colors = function(values) { var color_range, i, value, _i, _len, _results; color_range = d3.scale.linear().domain([d3.min(values), d3.max(values)]).range([0, 255]); @@ -346,16 +392,22 @@ trimmed_samples = this.trim_values(trait_sample_data); distinct_values = {}; distinct_values["collection_trait"] = this.get_distinct_values(trimmed_samples); - this.get_attr_color_dict(distinct_values); - if ($("#update_bar_chart").html() === 'Sort By Name') { - return this.svg.selectAll(".bar").data(this.sorted_samples()).transition().duration(1000).style("fill", function(d) { - return _this.attr_color_dict["collection_trait"][trimmed_samples[d[0]]]; + this.get_trait_color_dict(trimmed_samples, distinct_values); + console.log("TRAIT_COLOR_DICT:", this.trait_color_dict); + console.log("SAMPLES:", this.samples); + if (this.sort_by = "value") { + return this.svg.selectAll(".bar").data(this.samples).transition().duration(1000).style("fill", function(d) { + console.log("this color:", _this.trait_color_dict[d[0]]); + return _this.trait_color_dict[d[0]]; }).select("title").text(function(d) { return d[1]; }); } else { - return this.svg.selectAll(".bar").data(this.samples).transition().duration(1000).style("fill", function(d) { - return _this.attr_color_dict["collection_trait"][trimmed_samples[d[0]]]; + return this.svg.selectAll(".bar").data(this.sorted_samples()).transition().duration(1000).style("fill", function(d) { + console.log("this color:", _this.trait_color_dict[d[0]]); + return _this.trait_color_dict[d[0]]; + }).select("title").text(function(d) { + return d[1]; }); } }; diff --git a/wqflask/wqflask/static/new/javascript/chr_manhattan_plot.coffee b/wqflask/wqflask/static/new/javascript/chr_manhattan_plot.coffee new file mode 100644 index 00000000..30e6ea5e --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/chr_manhattan_plot.coffee @@ -0,0 +1,211 @@ +root = exports ? this + +class Chr_Manhattan_Plot + constructor: (@plot_height, @plot_width, @chr) -> + @qtl_results = js_data.qtl_results + console.log("qtl_results are:", @qtl_results) + console.log("chr is:", @chr) + + @get_max_chr() + + @filter_qtl_results() + console.log("filtered results:", @these_results) + @get_qtl_count() + + @x_coords = [] + @y_coords = [] + @marker_names = [] + + console.time('Create coordinates') + @create_coordinates() + console.log("@x_coords: ", @x_coords) + console.log("@y_coords: ", @y_coords) + console.timeEnd('Create coordinates') + + # Buffer to allow for the ticks/labels to be drawn + @x_buffer = @plot_width/30 + @y_buffer = @plot_height/20 + + @x_max = d3.max(@x_coords) + @y_max = d3.max(@y_coords) * 1.2 + + @svg = @create_svg() + + @plot_coordinates = _.zip(@x_coords, @y_coords, @marker_names) + console.log("coordinates:", @plot_coordinates) + + @plot_height -= @y_buffer + + @create_scales() + + console.time('Create graph') + @create_graph() + console.timeEnd('Create graph') + + get_max_chr: () -> + @max_chr = 0 + for key of js_data.chromosomes + console.log("key is:", key) + if parseInt(key) > @max_chr + @max_chr = parseInt(key) + + filter_qtl_results: () -> + @these_results = [] + this_chr = 100 + for result in @qtl_results + if result.chr == "X" + this_chr = @max_chr + else + this_chr = result.chr + console.log("this_chr is:", this_chr) + console.log("@chr[0] is:", parseInt(@chr[0])) + if this_chr > parseInt(@chr[0]) + break + if parseInt(this_chr) == parseInt(@chr[0]) + @these_results.push(result) + + get_qtl_count: () -> + high_qtl_count = 0 + for result in @these_results + if result.lod_score > 1 + high_qtl_count += 1 + console.log("high_qtl_count:", high_qtl_count) + + if high_qtl_count > 10000 + @y_axis_filter = 2 + else if high_qtl_count > 1000 + @y_axis_filter = 1 + else + @y_axis_filter = 0 + + create_coordinates: () -> + for result in @these_results + @x_coords.push(parseFloat(result.Mb)) + @y_coords.push(result.lod_score) + @marker_names.push(result.name) + + create_svg: () -> + svg = d3.select("#manhattan_plot") + .append("svg") + .attr("class", "manhattan_plot") + .attr("width", @plot_width+@x_buffer) + .attr("height", @plot_height+@y_buffer) + .append("g") + return svg + + create_scales: () -> + @x_scale = d3.scale.linear() + .domain([0, @chr[1]]) + .range([@x_buffer, @plot_width]) + @y_scale = d3.scale.linear() + .domain([@y_axis_filter, @y_max]) + .range([@plot_height, @y_buffer]) + + create_graph: () -> + @add_border() + @add_x_axis() + @add_y_axis() + @add_plot_points() + + add_border: () -> + border_coords = [[@y_buffer, @plot_height, @x_buffer, @x_buffer], + [@y_buffer, @plot_height, @plot_width, @plot_width], + [@y_buffer, @y_buffer, @x_buffer, @plot_width], + [@plot_height, @plot_height, @x_buffer, @plot_width]] + + @svg.selectAll("line") + .data(border_coords) + .enter() + .append("line") + .attr("y1", (d) => + return d[0] + ) + .attr("y2", (d) => + return d[1] + ) + .attr("x1", (d) => + return d[2] + ) + .attr("x2", (d) => + return d[3] + ) + .style("stroke", "#000") + + add_x_axis: () -> + @xAxis = d3.svg.axis() + .scale(@x_scale) + .orient("bottom") + .ticks(20) + + @xAxis.tickFormat((d) => + d3.format("d") #format as integer + return (d) + ) + + @svg.append("g") + .attr("class", "x_axis") + .attr("transform", "translate(0," + @plot_height + ")") + .call(@xAxis) + .selectAll("text") + .attr("text-anchor", "right") + .attr("font-size", "12px") + .attr("dx", "-1.6em") + .attr("transform", (d) => + return "translate(-12,0) rotate(-90)" + ) + + add_y_axis: () -> + @yAxis = d3.svg.axis() + .scale(@y_scale) + .orient("left") + .ticks(5) + + @svg.append("g") + .attr("class", "y_axis") + .attr("transform", "translate(" + @x_buffer + ",0)") + .call(@yAxis) + + add_plot_points: () -> + @plot_point = @svg.selectAll("circle") + .data(@plot_coordinates) + .enter() + .append("circle") + .attr("cx", (d) => + return @x_scale(d[0]) + ) + .attr("cy", (d) => + return @y_scale(d[1]) + ) + .attr("r", 2) + .attr("id", (d) => + return "point_" + String(d[2]) + ) + .classed("circle", true) + .on("mouseover", (d) => + console.log("d3.event is:", d3.event) + console.log("d is:", d) + this_id = "point_" + String(d[2]) + d3.select("#" + this_id).classed("d3_highlight", true) + .attr("r", 5) + .attr("fill", "yellow") + .call(@show_marker_in_table(d)) + ) + .on("mouseout", (d) => + this_id = "point_" + String(d[2]) + d3.select("#" + this_id).classed("d3_highlight", false) + .attr("r", 2) + .attr("fill", "black") + #.call(@show_marker_in_table()) + ) + + show_marker_in_table: (marker_info) -> + console.log("in show_marker_in_table") + ### Searches for the select marker in the results table below ### + if marker_info + marker_name = marker_info[2] + $("#qtl_results_filter").find("input:first").val(marker_name).change() + #else + # marker_name = "" + #$("#qtl_results_filter").find("input:first").val(marker_name).change() + +root.Chr_Manhattan_Plot = Chr_Manhattan_Plot \ No newline at end of file diff --git a/wqflask/wqflask/static/new/javascript/chr_manhattan_plot.js b/wqflask/wqflask/static/new/javascript/chr_manhattan_plot.js new file mode 100644 index 00000000..2cbab00c --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/chr_manhattan_plot.js @@ -0,0 +1,206 @@ +// Generated by CoffeeScript 1.6.1 +(function() { + var Chr_Manhattan_Plot, root; + + root = typeof exports !== "undefined" && exports !== null ? exports : this; + + Chr_Manhattan_Plot = (function() { + + function Chr_Manhattan_Plot(plot_height, plot_width, chr) { + this.plot_height = plot_height; + this.plot_width = plot_width; + this.chr = chr; + this.qtl_results = js_data.qtl_results; + console.log("qtl_results are:", this.qtl_results); + console.log("chr is:", this.chr); + this.get_max_chr(); + this.filter_qtl_results(); + console.log("filtered results:", this.these_results); + this.get_qtl_count(); + this.x_coords = []; + this.y_coords = []; + this.marker_names = []; + console.time('Create coordinates'); + this.create_coordinates(); + console.log("@x_coords: ", this.x_coords); + console.log("@y_coords: ", this.y_coords); + console.timeEnd('Create coordinates'); + this.x_buffer = this.plot_width / 30; + this.y_buffer = this.plot_height / 20; + this.x_max = d3.max(this.x_coords); + this.y_max = d3.max(this.y_coords) * 1.2; + this.svg = this.create_svg(); + this.plot_coordinates = _.zip(this.x_coords, this.y_coords, this.marker_names); + console.log("coordinates:", this.plot_coordinates); + this.plot_height -= this.y_buffer; + this.create_scales(); + console.time('Create graph'); + this.create_graph(); + console.timeEnd('Create graph'); + } + + Chr_Manhattan_Plot.prototype.get_max_chr = function() { + var key, _results; + this.max_chr = 0; + _results = []; + for (key in js_data.chromosomes) { + console.log("key is:", key); + if (parseInt(key) > this.max_chr) { + _results.push(this.max_chr = parseInt(key)); + } else { + _results.push(void 0); + } + } + return _results; + }; + + Chr_Manhattan_Plot.prototype.filter_qtl_results = function() { + var result, this_chr, _i, _len, _ref, _results; + this.these_results = []; + this_chr = 100; + _ref = this.qtl_results; + _results = []; + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + result = _ref[_i]; + if (result.chr === "X") { + this_chr = this.max_chr; + } else { + this_chr = result.chr; + } + console.log("this_chr is:", this_chr); + console.log("@chr[0] is:", parseInt(this.chr[0])); + if (this_chr > parseInt(this.chr[0])) { + break; + } + if (parseInt(this_chr) === parseInt(this.chr[0])) { + _results.push(this.these_results.push(result)); + } else { + _results.push(void 0); + } + } + return _results; + }; + + Chr_Manhattan_Plot.prototype.get_qtl_count = function() { + var high_qtl_count, result, _i, _len, _ref; + high_qtl_count = 0; + _ref = this.these_results; + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + result = _ref[_i]; + if (result.lod_score > 1) { + high_qtl_count += 1; + } + } + console.log("high_qtl_count:", high_qtl_count); + if (high_qtl_count > 10000) { + return this.y_axis_filter = 2; + } else if (high_qtl_count > 1000) { + return this.y_axis_filter = 1; + } else { + return this.y_axis_filter = 0; + } + }; + + Chr_Manhattan_Plot.prototype.create_coordinates = function() { + var result, _i, _len, _ref, _results; + _ref = this.these_results; + _results = []; + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + result = _ref[_i]; + this.x_coords.push(parseFloat(result.Mb)); + this.y_coords.push(result.lod_score); + _results.push(this.marker_names.push(result.name)); + } + return _results; + }; + + Chr_Manhattan_Plot.prototype.create_svg = function() { + var svg; + svg = d3.select("#manhattan_plot").append("svg").attr("class", "manhattan_plot").attr("width", this.plot_width + this.x_buffer).attr("height", this.plot_height + this.y_buffer).append("g"); + return svg; + }; + + Chr_Manhattan_Plot.prototype.create_scales = function() { + this.x_scale = d3.scale.linear().domain([0, this.chr[1]]).range([this.x_buffer, this.plot_width]); + return this.y_scale = d3.scale.linear().domain([this.y_axis_filter, this.y_max]).range([this.plot_height, this.y_buffer]); + }; + + Chr_Manhattan_Plot.prototype.create_graph = function() { + this.add_border(); + this.add_x_axis(); + this.add_y_axis(); + return this.add_plot_points(); + }; + + Chr_Manhattan_Plot.prototype.add_border = function() { + var border_coords, + _this = this; + border_coords = [[this.y_buffer, this.plot_height, this.x_buffer, this.x_buffer], [this.y_buffer, this.plot_height, this.plot_width, this.plot_width], [this.y_buffer, this.y_buffer, this.x_buffer, this.plot_width], [this.plot_height, this.plot_height, this.x_buffer, this.plot_width]]; + return this.svg.selectAll("line").data(border_coords).enter().append("line").attr("y1", function(d) { + return d[0]; + }).attr("y2", function(d) { + return d[1]; + }).attr("x1", function(d) { + return d[2]; + }).attr("x2", function(d) { + return d[3]; + }).style("stroke", "#000"); + }; + + Chr_Manhattan_Plot.prototype.add_x_axis = function() { + var _this = this; + this.xAxis = d3.svg.axis().scale(this.x_scale).orient("bottom").ticks(20); + this.xAxis.tickFormat(function(d) { + d3.format("d"); + return d; + }); + return this.svg.append("g").attr("class", "x_axis").attr("transform", "translate(0," + this.plot_height + ")").call(this.xAxis).selectAll("text").attr("text-anchor", "right").attr("font-size", "12px").attr("dx", "-1.6em").attr("transform", function(d) { + return "translate(-12,0) rotate(-90)"; + }); + }; + + Chr_Manhattan_Plot.prototype.add_y_axis = function() { + this.yAxis = d3.svg.axis().scale(this.y_scale).orient("left").ticks(5); + return this.svg.append("g").attr("class", "y_axis").attr("transform", "translate(" + this.x_buffer + ",0)").call(this.yAxis); + }; + + Chr_Manhattan_Plot.prototype.add_plot_points = function() { + var _this = this; + return this.plot_point = this.svg.selectAll("circle").data(this.plot_coordinates).enter().append("circle").attr("cx", function(d) { + return _this.x_scale(d[0]); + }).attr("cy", function(d) { + return _this.y_scale(d[1]); + }).attr("r", 2).attr("id", function(d) { + return "point_" + String(d[2]); + }).classed("circle", true).on("mouseover", function(d) { + var this_id; + console.log("d3.event is:", d3.event); + console.log("d is:", d); + this_id = "point_" + String(d[2]); + return d3.select("#" + this_id).classed("d3_highlight", true).attr("r", 5).attr("fill", "yellow").call(_this.show_marker_in_table(d)); + }).on("mouseout", function(d) { + var this_id; + this_id = "point_" + String(d[2]); + return d3.select("#" + this_id).classed("d3_highlight", false).attr("r", 2).attr("fill", "black"); + }); + }; + + Chr_Manhattan_Plot.prototype.show_marker_in_table = function(marker_info) { + var marker_name; + console.log("in show_marker_in_table"); + /* Searches for the select marker in the results table below + */ + + if (marker_info) { + marker_name = marker_info[2]; + return $("#qtl_results_filter").find("input:first").val(marker_name).change(); + } + }; + + return Chr_Manhattan_Plot; + + })(); + + root.Chr_Manhattan_Plot = Chr_Manhattan_Plot; + +}).call(this); diff --git a/wqflask/wqflask/static/new/javascript/histogram.coffee b/wqflask/wqflask/static/new/javascript/histogram.coffee new file mode 100644 index 00000000..97b833fd --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/histogram.coffee @@ -0,0 +1,106 @@ +root = exports ? this + +class Histogram + constructor: (@sample_list, @sample_group) -> + @sort_by = "name" + @format_count = d3.format(",.0f") #a formatter for counts + @get_sample_vals() + + @margin = {top: 10, right: 30, bottom: 30, left: 30} + @plot_width = 960 - @margin.left - @margin.right + @plot_height = 500 - @margin.top - @margin.bottom + + @x_buffer = @plot_width/20 + @y_buffer = @plot_height/20 + + @y_min = d3.min(@sample_vals) + @y_max = d3.max(@sample_vals) * 1.1 + + @plot_height -= @y_buffer + @create_x_scale() + @get_histogram_data() + @create_y_scale() + + @svg = @create_svg() + + @create_graph() + + get_sample_vals: () -> + @sample_vals = (sample.value for sample in @sample_list when sample.value != null) + + create_svg: () -> + svg = d3.select("#histogram") + .append("svg") + .attr("class", "bar_chart") + .attr("width", @plot_width + @margin.left + @margin.right) + .attr("height", @plot_height + @margin.top + @margin.bottom) + .append("g") + .attr("transform", "translate(" + @margin.left + "," + @margin.top + ")") + + return svg + + create_x_scale: () -> + console.log("min/max:", d3.min(@sample_vals) + "," + d3.max(@sample_vals)) + @x_scale = d3.scale.linear() + .domain([d3.min(@sample_vals), d3.max(@sample_vals)]) + .range([0, @plot_width]) + + get_histogram_data: () -> + console.log("sample_vals:", @sample_vals) + @histogram_data = d3.layout.histogram() + .bins(@x_scale.ticks(20))(@sample_vals) + console.log("histogram_data:", @histogram_data[0]) + + create_y_scale: () -> + @y_scale = d3.scale.linear() + .domain([0, d3.max(@histogram_data, (d) => return d.y )]) + .range([@plot_height, 0]) + + create_graph: () -> + @add_x_axis() + @add_bars() + + add_x_axis: () -> + x_axis = d3.svg.axis() + .scale(@x_scale) + .orient("bottom"); + + @svg.append("g") + .attr("class", "x axis") + .attr("transform", "translate(0," + @plot_height + ")") + .call(x_axis) + + add_y_axis: () -> + y_axis = d3.svg.axis() + .scale(@y_scale) + .orient("left") + .ticks(5) + + add_bars: () -> + console.log("bar_width:", @x_scale(@histogram_data[0].dx)) + bar = @svg.selectAll(".bar") + .data(@histogram_data) + .enter().append("g") + .attr("class", "bar") + .attr("transform", (d) => + return "translate(" + @x_scale(d.x) + "," + @y_scale(d.y) + ")") + + bar.append("rect") + .attr("x", 1) + .attr("width", (@x_scale(@histogram_data[1].x) - @x_scale(@histogram_data[0].x)) - 1) + .attr("height", (d) => + return @plot_height - @y_scale(d.y) + ) + bar.append("text") + .attr("dy", ".75em") + .attr("y", 6) + .attr("x", (@x_scale(@histogram_data[1].x) - @x_scale(@histogram_data[0].x))/2) + .attr("text-anchor", "middle") + .style("fill", "#fff") + .text((d) => + bar_height = @plot_height - @y_scale(d.y) + if bar_height > 20 + return @format_count(d.y) + ) + +root.Histogram = Histogram \ No newline at end of file diff --git a/wqflask/wqflask/static/new/javascript/histogram.js b/wqflask/wqflask/static/new/javascript/histogram.js new file mode 100644 index 00000000..eb00ca73 --- /dev/null +++ b/wqflask/wqflask/static/new/javascript/histogram.js @@ -0,0 +1,118 @@ +// Generated by CoffeeScript 1.6.1 +(function() { + var Histogram, root; + + root = typeof exports !== "undefined" && exports !== null ? exports : this; + + Histogram = (function() { + + function Histogram(sample_list, sample_group) { + this.sample_list = sample_list; + this.sample_group = sample_group; + this.sort_by = "name"; + this.format_count = d3.format(",.0f"); + this.get_sample_vals(); + this.margin = { + top: 10, + right: 30, + bottom: 30, + left: 30 + }; + this.plot_width = 960 - this.margin.left - this.margin.right; + this.plot_height = 500 - this.margin.top - this.margin.bottom; + this.x_buffer = this.plot_width / 20; + this.y_buffer = this.plot_height / 20; + this.y_min = d3.min(this.sample_vals); + this.y_max = d3.max(this.sample_vals) * 1.1; + this.plot_height -= this.y_buffer; + this.create_x_scale(); + this.get_histogram_data(); + this.create_y_scale(); + this.svg = this.create_svg(); + this.create_graph(); + } + + Histogram.prototype.get_sample_vals = function() { + var sample; + return this.sample_vals = (function() { + var _i, _len, _ref, _results; + _ref = this.sample_list; + _results = []; + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + sample = _ref[_i]; + if (sample.value !== null) { + _results.push(sample.value); + } + } + return _results; + }).call(this); + }; + + Histogram.prototype.create_svg = function() { + var svg; + svg = d3.select("#histogram").append("svg").attr("class", "bar_chart").attr("width", this.plot_width + this.margin.left + this.margin.right).attr("height", this.plot_height + this.margin.top + this.margin.bottom).append("g").attr("transform", "translate(" + this.margin.left + "," + this.margin.top + ")"); + return svg; + }; + + Histogram.prototype.create_x_scale = function() { + console.log("min/max:", d3.min(this.sample_vals) + "," + d3.max(this.sample_vals)); + return this.x_scale = d3.scale.linear().domain([d3.min(this.sample_vals), d3.max(this.sample_vals)]).range([0, this.plot_width]); + }; + + Histogram.prototype.get_histogram_data = function() { + console.log("sample_vals:", this.sample_vals); + this.histogram_data = d3.layout.histogram().bins(this.x_scale.ticks(20))(this.sample_vals); + return console.log("histogram_data:", this.histogram_data[0]); + }; + + Histogram.prototype.create_y_scale = function() { + var _this = this; + return this.y_scale = d3.scale.linear().domain([ + 0, d3.max(this.histogram_data, function(d) { + return d.y; + }) + ]).range([this.plot_height, 0]); + }; + + Histogram.prototype.create_graph = function() { + this.add_x_axis(); + return this.add_bars(); + }; + + Histogram.prototype.add_x_axis = function() { + var x_axis; + x_axis = d3.svg.axis().scale(this.x_scale).orient("bottom"); + return this.svg.append("g").attr("class", "x axis").attr("transform", "translate(0," + this.plot_height + ")").call(x_axis); + }; + + Histogram.prototype.add_y_axis = function() { + var y_axis; + return y_axis = d3.svg.axis().scale(this.y_scale).orient("left").ticks(5); + }; + + Histogram.prototype.add_bars = function() { + var bar, + _this = this; + console.log("bar_width:", this.x_scale(this.histogram_data[0].dx)); + bar = this.svg.selectAll(".bar").data(this.histogram_data).enter().append("g").attr("class", "bar").attr("transform", function(d) { + return "translate(" + _this.x_scale(d.x) + "," + _this.y_scale(d.y) + ")"; + }); + bar.append("rect").attr("x", 1).attr("width", (this.x_scale(this.histogram_data[1].x) - this.x_scale(this.histogram_data[0].x)) - 1).attr("height", function(d) { + return _this.plot_height - _this.y_scale(d.y); + }); + return bar.append("text").attr("dy", ".75em").attr("y", 6).attr("x", (this.x_scale(this.histogram_data[1].x) - this.x_scale(this.histogram_data[0].x)) / 2).attr("text-anchor", "middle").style("fill", "#fff").text(function(d) { + var bar_height; + bar_height = _this.plot_height - _this.y_scale(d.y); + if (bar_height > 20) { + return _this.format_count(d.y); + } + }); + }; + + return Histogram; + + })(); + + root.Histogram = Histogram; + +}).call(this); diff --git a/wqflask/wqflask/static/new/javascript/marker_regression.coffee b/wqflask/wqflask/static/new/javascript/marker_regression.coffee index f5f13c27..3f8fbe0d 100644 --- a/wqflask/wqflask/static/new/javascript/marker_regression.coffee +++ b/wqflask/wqflask/static/new/javascript/marker_regression.coffee @@ -1,311 +1,443 @@ -$ -> - class Manhattan_Plot - constructor: (@plot_height, @plot_width) -> - @qtl_results = js_data.qtl_results - console.log("qtl_results are:", @qtl_results) - @chromosomes = js_data.chromosomes +root = exports ? this - @total_length = 0 +class Manhattan_Plot + constructor: (@plot_height, @plot_width) -> + @qtl_results = js_data.qtl_results + console.log("qtl_results are:", @qtl_results) + @chromosomes = js_data.chromosomes - @max_chr = @get_max_chr() + @total_length = 0 - @x_coords = [] - @y_coords = [] - @marker_names = [] - console.time('Create coordinates') - @create_coordinates() - console.log("@x_coords: ", @x_coords) - console.log("@y_coords: ", @y_coords) - console.timeEnd('Create coordinates') - [@chr_lengths, @cumulative_chr_lengths] = @get_chr_lengths() + @max_chr = @get_max_chr() - # Buffer to allow for the ticks/labels to be drawn - @x_buffer = @plot_width/30 - @y_buffer = @plot_height/20 - - #@x_max = d3.max(@x_coords) - @x_max = @total_length - console.log("@x_max: ", @x_max) - console.log("@x_buffer: ", @x_buffer) - @y_max = d3.max(@y_coords) * 1.2 + @x_coords = [] + @y_coords = [] + @marker_names = [] + console.time('Create coordinates') + @get_qtl_count() + @create_coordinates() + console.log("@x_coords: ", @x_coords) + console.log("@y_coords: ", @y_coords) + console.timeEnd('Create coordinates') + [@chr_lengths, @cumulative_chr_lengths] = @get_chr_lengths() - @svg = @create_svg() - @plot_coordinates = _.zip(@x_coords, @y_coords, @marker_names) - - @plot_height -= @y_buffer - @create_scales() - console.time('Create graph') - @create_graph() - console.timeEnd('Create graph') + # Buffer to allow for the ticks/labels to be drawn + @x_buffer = @plot_width/30 + @y_buffer = @plot_height/20 + + #@x_max = d3.max(@x_coords) + @x_max = @total_length + console.log("@x_max: ", @x_max) + console.log("@x_buffer: ", @x_buffer) + @y_max = d3.max(@y_coords) * 1.2 - get_max_chr: () -> - max_chr = 0 - for result in @qtl_results - chr = parseInt(result.chr) - if not _.isNaN(chr) - if chr > max_chr - max_chr = chr - return max_chr + @svg = @create_svg() + console.log("svg created") - get_chr_lengths: () -> - ### - #Gets a list of both individual and cumulative (the position of one on the graph - #is its own length plus the lengths of all preceding chromosomes) lengths in order - #to draw the vertical lines separating chromosomes and the chromosome labels - # - ### - - console.log("@chromosomes: ", @chromosomes) - - cumulative_chr_lengths = [] - chr_lengths = [] - total_length = 0 - for key of @chromosomes - this_length = @chromosomes[key] - chr_lengths.push(this_length) - cumulative_chr_lengths.push(total_length + this_length) - total_length += this_length + @plot_coordinates = _.zip(@x_coords, @y_coords, @marker_names) + console.log("coordinates:", @plot_coordinates) + + @plot_height -= @y_buffer - console.log("chr_lengths: ", chr_lengths) + @create_scales() - return [chr_lengths, cumulative_chr_lengths] + console.time('Create graph') + @create_graph() + console.timeEnd('Create graph') - create_coordinates: () -> - chr_lengths = [] - chr_seen = [] - for result in js_data.qtl_results - if result.chr == "X" - chr_length = parseFloat(@chromosomes[20]) - else - chr_length = parseFloat(@chromosomes[result.chr]) - if not(result.chr in chr_seen) - chr_seen.push(result.chr) - chr_lengths.push(chr_length) - if result.chr != "1" - @total_length += parseFloat(chr_lengths[chr_lengths.length - 2]) + get_max_chr: () -> + max_chr = 0 + for result in @qtl_results + chr = parseInt(result.chr) + if not _.isNaN(chr) + if chr > max_chr + max_chr = chr + return max_chr + + get_chr_lengths: () -> + ### + #Gets a list of both individual and cumulative (the position of one on the graph + #is its own length plus the lengths of all preceding chromosomes) lengths in order + #to draw the vertical lines separating chromosomes and the chromosome labels + # + ### + + console.log("@chromosomes: ", @chromosomes) + + cumulative_chr_lengths = [] + chr_lengths = [] + total_length = 0 + for key of @chromosomes + this_length = @chromosomes[key] + chr_lengths.push(this_length) + cumulative_chr_lengths.push(total_length + this_length) + total_length += this_length + + console.log("chr_lengths: ", chr_lengths) + + return [chr_lengths, cumulative_chr_lengths] + + get_qtl_count: () -> + high_qtl_count = 0 + for result in js_data.qtl_results + if result.lod_score > 1 + high_qtl_count += 1 + console.log("high_qtl_count:", high_qtl_count) + + if high_qtl_count > 10000 + @y_axis_filter = 2 + else if high_qtl_count > 1000 + @y_axis_filter = 1 + else + @y_axis_filter = 0 + + + create_coordinates: () -> + chr_lengths = [] + chr_seen = [] + for result in js_data.qtl_results + if result.chr == "X" + chr_length = parseFloat(@chromosomes[20]) + else + chr_length = parseFloat(@chromosomes[result.chr]) + if not(result.chr in chr_seen) + chr_seen.push(result.chr) + chr_lengths.push(chr_length) + console.log("result.chr:", result.chr) + console.log("total_length:", @total_length) + if parseInt(result.chr) != 1 + console.log("plus:", chr_lengths.length - 2) + @total_length += parseFloat(chr_lengths[chr_lengths.length - 2]) + if result.lod_score > @y_axis_filter @x_coords.push(@total_length + parseFloat(result.Mb)) @y_coords.push(result.lod_score) @marker_names.push(result.name) - @total_length += parseFloat(chr_lengths[chr_lengths.length-1]) - #console.log("chr_lengths: ", chr_lengths) + @total_length += parseFloat(chr_lengths[chr_lengths.length-1]) - show_marker_in_table: (marker_info) -> - console.log("in show_marker_in_table") - ### Searches for the select marker in the results table below ### - if marker_info - marker_name = marker_info[2] - else - marker_name = "" - $("#qtl_results_filter").find("input:first").val(marker_name).keypress() + show_marker_in_table: (marker_info) -> + console.log("in show_marker_in_table") + ### Searches for the select marker in the results table below ### + if marker_info + marker_name = marker_info[2] + $("#qtl_results_filter").find("input:first").val(marker_name).change() + #else + # marker_name = "" + #$("#qtl_results_filter").find("input:first").val(marker_name).change() - create_svg: () -> - svg = d3.select("#manhattan_plots") - .append("svg") - .attr("class", "manhattan_plot") - .attr("width", @plot_width+@x_buffer) - .attr("height", @plot_height+@y_buffer) - - return svg + create_svg: () -> + svg = d3.select("#manhattan_plot") + .append("svg") + .attr("class", "manhattan_plot") + .attr("width", @plot_width+@x_buffer) + .attr("height", @plot_height+@y_buffer) + .append("g") + #.call(d3.behavior.zoom().x(@x_scale).y(@y_scale).scaleExtent([1,8]).on("zoom", () -> + # @svg.selectAll("circle") + # .attr("transform", transform) + #)) + return svg - create_graph: () -> - @add_border() - @add_x_axis() - @add_y_axis() - @add_chr_lines() - @fill_chr_areas() - @add_chr_labels() - @add_plot_points() + #zoom: () -> + # #@svg.selectAll.attr("transform", @transform) + # @svg.selectAll("circle") + # .attr("transform", transform) + # + #transform: (d) -> + # return "translate(" + @x_scale(d[0]) + "," + @y_scale(d[1]) + ")" - add_border: () -> - border_coords = [[@y_buffer, @plot_height, @x_buffer, @x_buffer], - [@y_buffer, @plot_height, @plot_width, @plot_width], - [@y_buffer, @y_buffer, @x_buffer, @plot_width], - [@plot_height, @plot_height, @x_buffer, @plot_width]] + create_graph: () -> + @add_border() + @add_x_axis() + @add_y_axis() + @add_axis_labels() + @add_chr_lines() + #@fill_chr_areas() + @add_chr_labels() + @add_plot_points() + #@create_zoom_pane() - @svg.selectAll("line") - .data(border_coords) - .enter() - .append("line") - .attr("y1", (d) => - return d[0] - ) - .attr("y2", (d) => - return d[1] - ) - .attr("x1", (d) => - return d[2] - ) - .attr("x2", (d) => - return d[3] - ) - .style("stroke", "#000") + add_border: () -> + border_coords = [[@y_buffer, @plot_height, @x_buffer, @x_buffer], + [@y_buffer, @plot_height, @plot_width, @plot_width], + [@y_buffer, @y_buffer, @x_buffer, @plot_width], + [@plot_height, @plot_height, @x_buffer, @plot_width]] - create_scales: () -> + @svg.selectAll("line") + .data(border_coords) + .enter() + .append("line") + .attr("y1", (d) => + return d[0] + ) + .attr("y2", (d) => + return d[1] + ) + .attr("x1", (d) => + return d[2] + ) + .attr("x2", (d) => + return d[3] + ) + .style("stroke", "#000") + + create_scales: () -> + #@x_scale = d3.scale.linear() + # .domain([0, d3.max(@x_coords)]) + # .range([@x_buffer, @plot_width]) + if '24' of @chromosomes + console.log("@chromosomes[24]:", @chromosomes['24']) + console.log("@chromosomes[23]:", @chromosomes['23']) + console.log("@total_length:", @total_length) + console.log("d3.max(@xcoords):", d3.max(@x_coords)) @x_scale = d3.scale.linear() - .domain([0, d3.max(@x_coords)]) + .domain([0, (@total_length + @chromosomes['24'])]) .range([@x_buffer, @plot_width]) + else + @x_scale = d3.scale.linear() + .domain([0, (@total_length + @chromosomes['20'])]) + .range([@x_buffer, @plot_width]) + @y_scale = d3.scale.linear() + .domain([@y_axis_filter, @y_max]) + .range([@plot_height, @y_buffer]) - @y_scale = d3.scale.linear() - .domain([0, @y_max]) - .range([@plot_height, @y_buffer]) - - create_x_axis_tick_values: () -> - tick_vals = [] - for val in [25..@cumulative_chr_lengths[0]] when val%25 == 0 - tick_vals.push(val) + create_x_axis_tick_values: () -> + tick_vals = [] + for val in [25..@cumulative_chr_lengths[0]] when val%25 == 0 + tick_vals.push(val) + + for length, i in @cumulative_chr_lengths + if i == 0 + continue + chr_ticks = [] + tick_count = Math.floor(@chr_lengths[i]/25) + tick_val = parseInt(@cumulative_chr_lengths[i-1]) + for tick in [0..(tick_count-1)] + tick_val += 25 + chr_ticks.push(tick_val) + Array::push.apply tick_vals, chr_ticks - for length, i in @cumulative_chr_lengths - if i == 0 - continue - chr_ticks = [] - tick_count = Math.floor(@chr_lengths[i]/25) - tick_val = parseInt(@cumulative_chr_lengths[i-1]) - for tick in [0..(tick_count-1)] - tick_val += 25 - chr_ticks.push(tick_val) - Array::push.apply tick_vals, chr_ticks - - #console.log("tick_vals:", tick_vals) - return tick_vals + #console.log("tick_vals:", tick_vals) + return tick_vals - add_x_axis: () -> - xAxis = d3.svg.axis() - .scale(@x_scale) - .orient("bottom") - .tickValues(@create_x_axis_tick_values()) + add_x_axis: () -> + @xAxis = d3.svg.axis() + .scale(@x_scale) + .orient("bottom") + .tickValues(@create_x_axis_tick_values()) - next_chr = 1 - tmp_tick_val = 0 - xAxis.tickFormat((d) => - d3.format("d") #format as integer - if d < @cumulative_chr_lengths[0] - tick_val = d + next_chr = 1 + tmp_tick_val = 0 + @xAxis.tickFormat((d) => + d3.format("d") #format as integer + if d < @cumulative_chr_lengths[0] + tick_val = d + else + next_chr_length = @cumulative_chr_lengths[next_chr] + if d > next_chr_length + next_chr += 1 + tmp_tick_val = 25 + tick_val = tmp_tick_val else - next_chr_length = @cumulative_chr_lengths[next_chr] - if d > next_chr_length - next_chr += 1 - tmp_tick_val = 25 - tick_val = tmp_tick_val - else - tmp_tick_val += 25 - tick_val = tmp_tick_val - return (tick_val) - ) - - @svg.append("g") - .attr("class", "x_axis") - .attr("transform", "translate(0," + @plot_height + ")") - .call(xAxis) - .selectAll("text") - .attr("text-anchor", "right") - .attr("dx", "-1.6em") - .attr("transform", (d) => - return "translate(-12,0) rotate(-90)" - ) - #.attr("dy", "-1.0em") - + tmp_tick_val += 25 + tick_val = tmp_tick_val + return (tick_val) + ) - add_y_axis: () -> - yAxis = d3.svg.axis() - .scale(@y_scale) - .orient("left") - .ticks(5) + @svg.append("g") + .attr("class", "x_axis") + .attr("transform", "translate(0," + @plot_height + ")") + .call(@xAxis) + .selectAll("text") + .attr("text-anchor", "right") + .attr("dx", "-1.6em") + .attr("transform", (d) => + return "translate(-12,0) rotate(-90)" + ) + #.attr("dy", "-1.0em") + + + add_y_axis: () -> + @yAxis = d3.svg.axis() + .scale(@y_scale) + .orient("left") + .ticks(5) + + @svg.append("g") + .attr("class", "y_axis") + .attr("transform", "translate(" + @x_buffer + ",0)") + .call(@yAxis) - @svg.append("g") - .attr("class", "y_axis") - .attr("transform", "translate(" + @x_buffer + ",0)") - .call(yAxis) + add_axis_labels: () -> + @svg.append("text") + .attr("transform","rotate(-90)") + .attr("y", 0 - (@plot_height / 2)) + .attr("x", @x_buffer) + .attr("dy", "1em") + .style("text-anchor", "middle") + .text("LOD Score") - add_chr_lines: () -> - @svg.selectAll("line") - .data(@cumulative_chr_lengths, (d) => - return d - ) - .enter() - .append("line") - .attr("x1", @x_scale) - .attr("x2", @x_scale) - .attr("y1", @y_buffer) - .attr("y2", @plot_height) - .style("stroke", "#ccc") - - fill_chr_areas: () -> - @svg.selectAll("rect.chr_fill_area_1") - .data(_.zip(@chr_lengths, @cumulative_chr_lengths), (d) => - return d - ) - .enter() - .append("rect") - .attr("class", "chr_fill_area_1") - .attr("x", (d, i) => - if i == 0 - return @x_scale(0) - else - return @x_scale(@cumulative_chr_lengths[i-1]) - ) - .attr("y", @y_buffer) - .attr("width", (d) => - return @x_scale(d[0]) - ) - .attr("height", @plot_height-@y_buffer) + add_chr_lines: () -> + @svg.selectAll("line") + .data(@cumulative_chr_lengths, (d) => + return d + ) + .enter() + .append("line") + .attr("x1", @x_scale) + .attr("x2", @x_scale) + .attr("y1", @y_buffer) + .attr("y2", @plot_height) + .style("stroke", "#ccc") + + + fill_chr_areas: () -> + console.log("cumu_chr_lengths:", @cumulative_chr_lengths) + console.log("example:", @x_scale(@cumulative_chr_lengths[0])) + @svg.selectAll("rect.chr_fill_area") + .data(_.zip(@chr_lengths, @cumulative_chr_lengths), (d) => + return d + ) + .enter() + .append("rect") + .attr("x", (d) => + if i == 0 + return @x_scale(0) + else + return @x_scale(d[1]) + ) + .attr("y", @y_buffer) + .attr("width", (d) => + return @x_scale(d[0]) + ) + .attr("height", @plot_height-@y_buffer) + #.attr("fill", (d, i) => + # if i%2 + # return "whitesmoke" + # else + # return "none" + #) + + fill_chr_areas2: () -> + console.log("cumu_chr_lengths:", @cumulative_chr_lengths) + console.log("example:", @x_scale(@cumulative_chr_lengths[0])) + @svg.selectAll("rect.chr_fill_area") + .data(_.zip(@chr_lengths, @cumulative_chr_lengths), (d) => + return d + ) + .enter() + .append("rect") + .attr("x", (d) => + if i == 0 + return @x_scale(0) + else + return @x_scale(d[1]) + ) + .attr("y", @y_buffer) + .attr("width", (d) => + return @x_scale(d[0]) + ) + .attr("height", @plot_height-@y_buffer) + .attr("fill", (d, i) => + return "whitesmoke" + #if i%2 + # return "whitesmoke" + #else + # return "none" + ) - add_chr_labels: () -> - chr_names = [] - for key of @chromosomes - chr_names.push(key) - chr_info = _.zip(chr_names, @chr_lengths, @cumulative_chr_lengths) - @svg.selectAll("text") - .data(chr_info, (d) => - return d - ) - .enter() - .append("text") - .text((d) => + add_chr_labels: () -> + chr_names = [] + for key of @chromosomes + chr_names.push(key) + chr_info = _.zip(chr_names, @chr_lengths, @cumulative_chr_lengths) + @svg.selectAll("text") + .data(chr_info, (d) => + return d + ) + .enter() + .append("text") + .attr("class", "chr_label") + .text((d) => + if d[0] == "23" + return "X" + else if d[0] == "24" + return "X/Y" + else return d[0] - ) - .attr("x", (d) => - return @x_scale(d[2] - d[1]/2) - ) - .attr("y", @plot_height * 0.1) - .attr("dx", "0em") - .attr("text-anchor", "middle") - .attr("font-family", "sans-serif") - .attr("font-size", "18px") - .attr("fill", "grey") + ) + .attr("x", (d) => + return @x_scale(d[2] - d[1]/2) + ) + .attr("y", @plot_height * 0.1) + .attr("dx", "0em") + .attr("text-anchor", "middle") + .attr("font-family", "sans-serif") + .attr("font-size", "18px") + .attr("fill", "black") + .on("click", (d) => + this_chr = d + @redraw_plot(d) + ) - add_plot_points: () -> - @svg.selectAll("circle") - .data(@plot_coordinates) - .enter() - .append("circle") - .attr("cx", (d) => - return parseFloat(@x_buffer) + ((parseFloat(@plot_width)-parseFloat(@x_buffer)) * d[0]/parseFloat(@x_max)) - ) - .attr("cy", (d) => - return @plot_height - ((@plot_height-@y_buffer) * d[1]/@y_max) - ) - .attr("r", 2) - .attr("id", (d) => - return "point_" + String(d[2]) - ) - .classed("circle", true) - .on("mouseover", (d) => - console.log("d3.event is:", d3.event) - console.log("d is:", d) - this_id = "point_" + String(d[2]) - d3.select("#" + this_id).classed("d3_highlight", true) - .attr("r", 5) - .attr("fill", "yellow") - .call(@show_marker_in_table(d)) - ) - .on("mouseout", (d) => - this_id = "point_" + String(d[2]) - d3.select("#" + this_id).classed("d3_highlight", false) - .attr("r", 2) - .attr("fill", "black") - .call(@show_marker_in_table()) - ) + add_plot_points: () -> + @plot_point = @svg.selectAll("circle") + .data(@plot_coordinates) + .enter() + .append("circle") + .attr("cx", (d) => + return @x_scale(d[0]) + ) + .attr("cy", (d) => + return @y_scale(d[1]) + ) + .attr("r", 2) + .attr("id", (d) => + return "point_" + String(d[2]) + ) + .classed("circle", true) + .on("mouseover", (d) => + console.log("d3.event is:", d3.event) + console.log("d is:", d) + this_id = "point_" + String(d[2]) + d3.select("#" + this_id).classed("d3_highlight", true) + .attr("r", 5) + .attr("fill", "yellow") + .call(@show_marker_in_table(d)) + ) + .on("mouseout", (d) => + this_id = "point_" + String(d[2]) + d3.select("#" + this_id).classed("d3_highlight", false) + .attr("r", 2) + .attr("fill", "black") + ) + + redraw_plot: (chr_ob) -> + console.log("chr_name is:", chr_ob[0]) + console.log("chr_length is:", chr_ob[1]) + $('#manhattan_plot').remove() + $('#manhattan_plot_container').append('<div id="manhattan_plot"></div>') + root.chr_plot = new Chr_Manhattan_Plot(600, 1200, chr_ob) + + + create_zoom_pane: () -> + zoom = d3.behavior.zoom() + .on("zoom", draw); + + @svg.append("rect") + .attr("class", "pane") + .attr("width", @plot_width) + .attr("height", @plot_height) + .call(zoom) + + draw: () -> + @svg.select("g.x_axis").call(@xAxis); + @svg.select("g.y_axis").call(@yAxis); + @svg.select("path.area").attr("d", area); + @svg.select("path.line").attr("d", line); + - console.time('Create manhattan plot') - new Manhattan_Plot(600, 1200) - console.timeEnd('Create manhattan plot') \ No newline at end of file + #console.time('Create manhattan plot') + #new Manhattan_Plot(600, 1200) + #console.timeEnd('Create manhattan plot') + +root.Manhattan_Plot = new Manhattan_Plot(600, 1200) \ No newline at end of file diff --git a/wqflask/wqflask/static/new/javascript/marker_regression.js b/wqflask/wqflask/static/new/javascript/marker_regression.js index cdf37671..86509316 100644 --- a/wqflask/wqflask/static/new/javascript/marker_regression.js +++ b/wqflask/wqflask/static/new/javascript/marker_regression.js @@ -1,286 +1,374 @@ // Generated by CoffeeScript 1.6.1 (function() { - var __indexOf = [].indexOf || function(item) { for (var i = 0, l = this.length; i < l; i++) { if (i in this && this[i] === item) return i; } return -1; }; + var Manhattan_Plot, root, + __indexOf = [].indexOf || function(item) { for (var i = 0, l = this.length; i < l; i++) { if (i in this && this[i] === item) return i; } return -1; }; - $(function() { - var Manhattan_Plot; - Manhattan_Plot = (function() { + root = typeof exports !== "undefined" && exports !== null ? exports : this; - function Manhattan_Plot(plot_height, plot_width) { - var _ref; - this.plot_height = plot_height; - this.plot_width = plot_width; - this.qtl_results = js_data.qtl_results; - console.log("qtl_results are:", this.qtl_results); - this.chromosomes = js_data.chromosomes; - this.total_length = 0; - this.max_chr = this.get_max_chr(); - this.x_coords = []; - this.y_coords = []; - this.marker_names = []; - console.time('Create coordinates'); - this.create_coordinates(); - console.log("@x_coords: ", this.x_coords); - console.log("@y_coords: ", this.y_coords); - console.timeEnd('Create coordinates'); - _ref = this.get_chr_lengths(), this.chr_lengths = _ref[0], this.cumulative_chr_lengths = _ref[1]; - this.x_buffer = this.plot_width / 30; - this.y_buffer = this.plot_height / 20; - this.x_max = this.total_length; - console.log("@x_max: ", this.x_max); - console.log("@x_buffer: ", this.x_buffer); - this.y_max = d3.max(this.y_coords) * 1.2; - this.svg = this.create_svg(); - this.plot_coordinates = _.zip(this.x_coords, this.y_coords, this.marker_names); - this.plot_height -= this.y_buffer; - this.create_scales(); - console.time('Create graph'); - this.create_graph(); - console.timeEnd('Create graph'); - } + Manhattan_Plot = (function() { + + function Manhattan_Plot(plot_height, plot_width) { + var _ref; + this.plot_height = plot_height; + this.plot_width = plot_width; + this.qtl_results = js_data.qtl_results; + console.log("qtl_results are:", this.qtl_results); + this.chromosomes = js_data.chromosomes; + this.total_length = 0; + this.max_chr = this.get_max_chr(); + this.x_coords = []; + this.y_coords = []; + this.marker_names = []; + console.time('Create coordinates'); + this.get_qtl_count(); + this.create_coordinates(); + console.log("@x_coords: ", this.x_coords); + console.log("@y_coords: ", this.y_coords); + console.timeEnd('Create coordinates'); + _ref = this.get_chr_lengths(), this.chr_lengths = _ref[0], this.cumulative_chr_lengths = _ref[1]; + this.x_buffer = this.plot_width / 30; + this.y_buffer = this.plot_height / 20; + this.x_max = this.total_length; + console.log("@x_max: ", this.x_max); + console.log("@x_buffer: ", this.x_buffer); + this.y_max = d3.max(this.y_coords) * 1.2; + this.svg = this.create_svg(); + console.log("svg created"); + this.plot_coordinates = _.zip(this.x_coords, this.y_coords, this.marker_names); + console.log("coordinates:", this.plot_coordinates); + this.plot_height -= this.y_buffer; + this.create_scales(); + console.time('Create graph'); + this.create_graph(); + console.timeEnd('Create graph'); + } - Manhattan_Plot.prototype.get_max_chr = function() { - var chr, max_chr, result, _i, _len, _ref; - max_chr = 0; - _ref = this.qtl_results; - for (_i = 0, _len = _ref.length; _i < _len; _i++) { - result = _ref[_i]; - chr = parseInt(result.chr); - if (!_.isNaN(chr)) { - if (chr > max_chr) { - max_chr = chr; - } + Manhattan_Plot.prototype.get_max_chr = function() { + var chr, max_chr, result, _i, _len, _ref; + max_chr = 0; + _ref = this.qtl_results; + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + result = _ref[_i]; + chr = parseInt(result.chr); + if (!_.isNaN(chr)) { + if (chr > max_chr) { + max_chr = chr; } } - return max_chr; - }; + } + return max_chr; + }; - Manhattan_Plot.prototype.get_chr_lengths = function() { - /* - #Gets a list of both individual and cumulative (the position of one on the graph - #is its own length plus the lengths of all preceding chromosomes) lengths in order - #to draw the vertical lines separating chromosomes and the chromosome labels - # - */ + Manhattan_Plot.prototype.get_chr_lengths = function() { + /* + #Gets a list of both individual and cumulative (the position of one on the graph + #is its own length plus the lengths of all preceding chromosomes) lengths in order + #to draw the vertical lines separating chromosomes and the chromosome labels + # + */ + + var chr_lengths, cumulative_chr_lengths, key, this_length, total_length; + console.log("@chromosomes: ", this.chromosomes); + cumulative_chr_lengths = []; + chr_lengths = []; + total_length = 0; + for (key in this.chromosomes) { + this_length = this.chromosomes[key]; + chr_lengths.push(this_length); + cumulative_chr_lengths.push(total_length + this_length); + total_length += this_length; + } + console.log("chr_lengths: ", chr_lengths); + return [chr_lengths, cumulative_chr_lengths]; + }; - var chr_lengths, cumulative_chr_lengths, key, this_length, total_length; - console.log("@chromosomes: ", this.chromosomes); - cumulative_chr_lengths = []; - chr_lengths = []; - total_length = 0; - for (key in this.chromosomes) { - this_length = this.chromosomes[key]; - chr_lengths.push(this_length); - cumulative_chr_lengths.push(total_length + this_length); - total_length += this_length; + Manhattan_Plot.prototype.get_qtl_count = function() { + var high_qtl_count, result, _i, _len, _ref; + high_qtl_count = 0; + _ref = js_data.qtl_results; + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + result = _ref[_i]; + if (result.lod_score > 1) { + high_qtl_count += 1; } - console.log("chr_lengths: ", chr_lengths); - return [chr_lengths, cumulative_chr_lengths]; - }; + } + console.log("high_qtl_count:", high_qtl_count); + if (high_qtl_count > 10000) { + return this.y_axis_filter = 2; + } else if (high_qtl_count > 1000) { + return this.y_axis_filter = 1; + } else { + return this.y_axis_filter = 0; + } + }; - Manhattan_Plot.prototype.create_coordinates = function() { - var chr_length, chr_lengths, chr_seen, result, _i, _len, _ref, _ref1; - chr_lengths = []; - chr_seen = []; - _ref = js_data.qtl_results; - for (_i = 0, _len = _ref.length; _i < _len; _i++) { - result = _ref[_i]; - if (result.chr === "X") { - chr_length = parseFloat(this.chromosomes[20]); - } else { - chr_length = parseFloat(this.chromosomes[result.chr]); - } - if (!(_ref1 = result.chr, __indexOf.call(chr_seen, _ref1) >= 0)) { - chr_seen.push(result.chr); - chr_lengths.push(chr_length); - if (result.chr !== "1") { - this.total_length += parseFloat(chr_lengths[chr_lengths.length - 2]); - } + Manhattan_Plot.prototype.create_coordinates = function() { + var chr_length, chr_lengths, chr_seen, result, _i, _len, _ref, _ref1; + chr_lengths = []; + chr_seen = []; + _ref = js_data.qtl_results; + for (_i = 0, _len = _ref.length; _i < _len; _i++) { + result = _ref[_i]; + if (result.chr === "X") { + chr_length = parseFloat(this.chromosomes[20]); + } else { + chr_length = parseFloat(this.chromosomes[result.chr]); + } + if (!(_ref1 = result.chr, __indexOf.call(chr_seen, _ref1) >= 0)) { + chr_seen.push(result.chr); + chr_lengths.push(chr_length); + console.log("result.chr:", result.chr); + console.log("total_length:", this.total_length); + if (parseInt(result.chr) !== 1) { + console.log("plus:", chr_lengths.length - 2); + this.total_length += parseFloat(chr_lengths[chr_lengths.length - 2]); } + } + if (result.lod_score > this.y_axis_filter) { this.x_coords.push(this.total_length + parseFloat(result.Mb)); this.y_coords.push(result.lod_score); this.marker_names.push(result.name); } - return this.total_length += parseFloat(chr_lengths[chr_lengths.length - 1]); - }; + } + return this.total_length += parseFloat(chr_lengths[chr_lengths.length - 1]); + }; - Manhattan_Plot.prototype.show_marker_in_table = function(marker_info) { - var marker_name; - console.log("in show_marker_in_table"); - /* Searches for the select marker in the results table below - */ + Manhattan_Plot.prototype.show_marker_in_table = function(marker_info) { + var marker_name; + console.log("in show_marker_in_table"); + /* Searches for the select marker in the results table below + */ - if (marker_info) { - marker_name = marker_info[2]; - } else { - marker_name = ""; - } - return $("#qtl_results_filter").find("input:first").val(marker_name).keypress(); - }; + if (marker_info) { + marker_name = marker_info[2]; + return $("#qtl_results_filter").find("input:first").val(marker_name).change(); + } + }; - Manhattan_Plot.prototype.create_svg = function() { - var svg; - svg = d3.select("#manhattan_plots").append("svg").attr("class", "manhattan_plot").attr("width", this.plot_width + this.x_buffer).attr("height", this.plot_height + this.y_buffer); - return svg; - }; + Manhattan_Plot.prototype.create_svg = function() { + var svg; + svg = d3.select("#manhattan_plot").append("svg").attr("class", "manhattan_plot").attr("width", this.plot_width + this.x_buffer).attr("height", this.plot_height + this.y_buffer).append("g"); + return svg; + }; - Manhattan_Plot.prototype.create_graph = function() { - this.add_border(); - this.add_x_axis(); - this.add_y_axis(); - this.add_chr_lines(); - this.fill_chr_areas(); - this.add_chr_labels(); - return this.add_plot_points(); - }; + Manhattan_Plot.prototype.create_graph = function() { + this.add_border(); + this.add_x_axis(); + this.add_y_axis(); + this.add_axis_labels(); + this.add_chr_lines(); + this.add_chr_labels(); + return this.add_plot_points(); + }; - Manhattan_Plot.prototype.add_border = function() { - var border_coords, - _this = this; - border_coords = [[this.y_buffer, this.plot_height, this.x_buffer, this.x_buffer], [this.y_buffer, this.plot_height, this.plot_width, this.plot_width], [this.y_buffer, this.y_buffer, this.x_buffer, this.plot_width], [this.plot_height, this.plot_height, this.x_buffer, this.plot_width]]; - return this.svg.selectAll("line").data(border_coords).enter().append("line").attr("y1", function(d) { - return d[0]; - }).attr("y2", function(d) { - return d[1]; - }).attr("x1", function(d) { - return d[2]; - }).attr("x2", function(d) { - return d[3]; - }).style("stroke", "#000"); - }; + Manhattan_Plot.prototype.add_border = function() { + var border_coords, + _this = this; + border_coords = [[this.y_buffer, this.plot_height, this.x_buffer, this.x_buffer], [this.y_buffer, this.plot_height, this.plot_width, this.plot_width], [this.y_buffer, this.y_buffer, this.x_buffer, this.plot_width], [this.plot_height, this.plot_height, this.x_buffer, this.plot_width]]; + return this.svg.selectAll("line").data(border_coords).enter().append("line").attr("y1", function(d) { + return d[0]; + }).attr("y2", function(d) { + return d[1]; + }).attr("x1", function(d) { + return d[2]; + }).attr("x2", function(d) { + return d[3]; + }).style("stroke", "#000"); + }; - Manhattan_Plot.prototype.create_scales = function() { - this.x_scale = d3.scale.linear().domain([0, d3.max(this.x_coords)]).range([this.x_buffer, this.plot_width]); - return this.y_scale = d3.scale.linear().domain([0, this.y_max]).range([this.plot_height, this.y_buffer]); - }; + Manhattan_Plot.prototype.create_scales = function() { + if ('24' in this.chromosomes) { + console.log("@chromosomes[24]:", this.chromosomes['24']); + console.log("@chromosomes[23]:", this.chromosomes['23']); + console.log("@total_length:", this.total_length); + console.log("d3.max(@xcoords):", d3.max(this.x_coords)); + this.x_scale = d3.scale.linear().domain([0, this.total_length + this.chromosomes['24']]).range([this.x_buffer, this.plot_width]); + } else { + this.x_scale = d3.scale.linear().domain([0, this.total_length + this.chromosomes['20']]).range([this.x_buffer, this.plot_width]); + } + return this.y_scale = d3.scale.linear().domain([this.y_axis_filter, this.y_max]).range([this.plot_height, this.y_buffer]); + }; - Manhattan_Plot.prototype.create_x_axis_tick_values = function() { - var chr_ticks, i, length, tick, tick_count, tick_val, tick_vals, val, _i, _j, _k, _len, _ref, _ref1, _ref2; - tick_vals = []; - for (val = _i = 25, _ref = this.cumulative_chr_lengths[0]; 25 <= _ref ? _i <= _ref : _i >= _ref; val = 25 <= _ref ? ++_i : --_i) { - if (val % 25 === 0) { - tick_vals.push(val); - } + Manhattan_Plot.prototype.create_x_axis_tick_values = function() { + var chr_ticks, i, length, tick, tick_count, tick_val, tick_vals, val, _i, _j, _k, _len, _ref, _ref1, _ref2; + tick_vals = []; + for (val = _i = 25, _ref = this.cumulative_chr_lengths[0]; 25 <= _ref ? _i <= _ref : _i >= _ref; val = 25 <= _ref ? ++_i : --_i) { + if (val % 25 === 0) { + tick_vals.push(val); } - _ref1 = this.cumulative_chr_lengths; - for (i = _j = 0, _len = _ref1.length; _j < _len; i = ++_j) { - length = _ref1[i]; - if (i === 0) { - continue; - } - chr_ticks = []; - tick_count = Math.floor(this.chr_lengths[i] / 25); - tick_val = parseInt(this.cumulative_chr_lengths[i - 1]); - for (tick = _k = 0, _ref2 = tick_count - 1; 0 <= _ref2 ? _k <= _ref2 : _k >= _ref2; tick = 0 <= _ref2 ? ++_k : --_k) { - tick_val += 25; - chr_ticks.push(tick_val); - } - Array.prototype.push.apply(tick_vals, chr_ticks); + } + _ref1 = this.cumulative_chr_lengths; + for (i = _j = 0, _len = _ref1.length; _j < _len; i = ++_j) { + length = _ref1[i]; + if (i === 0) { + continue; + } + chr_ticks = []; + tick_count = Math.floor(this.chr_lengths[i] / 25); + tick_val = parseInt(this.cumulative_chr_lengths[i - 1]); + for (tick = _k = 0, _ref2 = tick_count - 1; 0 <= _ref2 ? _k <= _ref2 : _k >= _ref2; tick = 0 <= _ref2 ? ++_k : --_k) { + tick_val += 25; + chr_ticks.push(tick_val); } - return tick_vals; - }; + Array.prototype.push.apply(tick_vals, chr_ticks); + } + return tick_vals; + }; - Manhattan_Plot.prototype.add_x_axis = function() { - var next_chr, tmp_tick_val, xAxis, - _this = this; - xAxis = d3.svg.axis().scale(this.x_scale).orient("bottom").tickValues(this.create_x_axis_tick_values()); - next_chr = 1; - tmp_tick_val = 0; - xAxis.tickFormat(function(d) { - var next_chr_length, tick_val; - d3.format("d"); - if (d < _this.cumulative_chr_lengths[0]) { - tick_val = d; + Manhattan_Plot.prototype.add_x_axis = function() { + var next_chr, tmp_tick_val, + _this = this; + this.xAxis = d3.svg.axis().scale(this.x_scale).orient("bottom").tickValues(this.create_x_axis_tick_values()); + next_chr = 1; + tmp_tick_val = 0; + this.xAxis.tickFormat(function(d) { + var next_chr_length, tick_val; + d3.format("d"); + if (d < _this.cumulative_chr_lengths[0]) { + tick_val = d; + } else { + next_chr_length = _this.cumulative_chr_lengths[next_chr]; + if (d > next_chr_length) { + next_chr += 1; + tmp_tick_val = 25; + tick_val = tmp_tick_val; } else { - next_chr_length = _this.cumulative_chr_lengths[next_chr]; - if (d > next_chr_length) { - next_chr += 1; - tmp_tick_val = 25; - tick_val = tmp_tick_val; - } else { - tmp_tick_val += 25; - tick_val = tmp_tick_val; - } + tmp_tick_val += 25; + tick_val = tmp_tick_val; } - return tick_val; - }); - return this.svg.append("g").attr("class", "x_axis").attr("transform", "translate(0," + this.plot_height + ")").call(xAxis).selectAll("text").attr("text-anchor", "right").attr("dx", "-1.6em").attr("transform", function(d) { - return "translate(-12,0) rotate(-90)"; - }); - }; + } + return tick_val; + }); + return this.svg.append("g").attr("class", "x_axis").attr("transform", "translate(0," + this.plot_height + ")").call(this.xAxis).selectAll("text").attr("text-anchor", "right").attr("dx", "-1.6em").attr("transform", function(d) { + return "translate(-12,0) rotate(-90)"; + }); + }; - Manhattan_Plot.prototype.add_y_axis = function() { - var yAxis; - yAxis = d3.svg.axis().scale(this.y_scale).orient("left").ticks(5); - return this.svg.append("g").attr("class", "y_axis").attr("transform", "translate(" + this.x_buffer + ",0)").call(yAxis); - }; + Manhattan_Plot.prototype.add_y_axis = function() { + this.yAxis = d3.svg.axis().scale(this.y_scale).orient("left").ticks(5); + return this.svg.append("g").attr("class", "y_axis").attr("transform", "translate(" + this.x_buffer + ",0)").call(this.yAxis); + }; - Manhattan_Plot.prototype.add_chr_lines = function() { - var _this = this; - return this.svg.selectAll("line").data(this.cumulative_chr_lengths, function(d) { - return d; - }).enter().append("line").attr("x1", this.x_scale).attr("x2", this.x_scale).attr("y1", this.y_buffer).attr("y2", this.plot_height).style("stroke", "#ccc"); - }; + Manhattan_Plot.prototype.add_axis_labels = function() { + return this.svg.append("text").attr("transform", "rotate(-90)").attr("y", 0 - (this.plot_height / 2)).attr("x", this.x_buffer).attr("dy", "1em").style("text-anchor", "middle").text("LOD Score"); + }; - Manhattan_Plot.prototype.fill_chr_areas = function() { - var _this = this; - return this.svg.selectAll("rect.chr_fill_area_1").data(_.zip(this.chr_lengths, this.cumulative_chr_lengths), function(d) { - return d; - }).enter().append("rect").attr("class", "chr_fill_area_1").attr("x", function(d, i) { - if (i === 0) { - return _this.x_scale(0); - } else { - return _this.x_scale(_this.cumulative_chr_lengths[i - 1]); - } - }).attr("y", this.y_buffer).attr("width", function(d) { - return _this.x_scale(d[0]); - }).attr("height", this.plot_height - this.y_buffer); - }; + Manhattan_Plot.prototype.add_chr_lines = function() { + var _this = this; + return this.svg.selectAll("line").data(this.cumulative_chr_lengths, function(d) { + return d; + }).enter().append("line").attr("x1", this.x_scale).attr("x2", this.x_scale).attr("y1", this.y_buffer).attr("y2", this.plot_height).style("stroke", "#ccc"); + }; + + Manhattan_Plot.prototype.fill_chr_areas = function() { + var _this = this; + console.log("cumu_chr_lengths:", this.cumulative_chr_lengths); + console.log("example:", this.x_scale(this.cumulative_chr_lengths[0])); + return this.svg.selectAll("rect.chr_fill_area").data(_.zip(this.chr_lengths, this.cumulative_chr_lengths), function(d) { + return d; + }).enter().append("rect").attr("x", function(d) { + if (i === 0) { + return _this.x_scale(0); + } else { + return _this.x_scale(d[1]); + } + }).attr("y", this.y_buffer).attr("width", function(d) { + return _this.x_scale(d[0]); + }).attr("height", this.plot_height - this.y_buffer); + }; - Manhattan_Plot.prototype.add_chr_labels = function() { - var chr_info, chr_names, key, - _this = this; - chr_names = []; - for (key in this.chromosomes) { - chr_names.push(key); + Manhattan_Plot.prototype.fill_chr_areas2 = function() { + var _this = this; + console.log("cumu_chr_lengths:", this.cumulative_chr_lengths); + console.log("example:", this.x_scale(this.cumulative_chr_lengths[0])); + return this.svg.selectAll("rect.chr_fill_area").data(_.zip(this.chr_lengths, this.cumulative_chr_lengths), function(d) { + return d; + }).enter().append("rect").attr("x", function(d) { + if (i === 0) { + return _this.x_scale(0); + } else { + return _this.x_scale(d[1]); } - chr_info = _.zip(chr_names, this.chr_lengths, this.cumulative_chr_lengths); - return this.svg.selectAll("text").data(chr_info, function(d) { - return d; - }).enter().append("text").text(function(d) { + }).attr("y", this.y_buffer).attr("width", function(d) { + return _this.x_scale(d[0]); + }).attr("height", this.plot_height - this.y_buffer).attr("fill", function(d, i) { + return "whitesmoke"; + }); + }; + + Manhattan_Plot.prototype.add_chr_labels = function() { + var chr_info, chr_names, key, + _this = this; + chr_names = []; + for (key in this.chromosomes) { + chr_names.push(key); + } + chr_info = _.zip(chr_names, this.chr_lengths, this.cumulative_chr_lengths); + return this.svg.selectAll("text").data(chr_info, function(d) { + return d; + }).enter().append("text").attr("class", "chr_label").text(function(d) { + if (d[0] === "23") { + return "X"; + } else if (d[0] === "24") { + return "X/Y"; + } else { return d[0]; - }).attr("x", function(d) { - return _this.x_scale(d[2] - d[1] / 2); - }).attr("y", this.plot_height * 0.1).attr("dx", "0em").attr("text-anchor", "middle").attr("font-family", "sans-serif").attr("font-size", "18px").attr("fill", "grey"); - }; + } + }).attr("x", function(d) { + return _this.x_scale(d[2] - d[1] / 2); + }).attr("y", this.plot_height * 0.1).attr("dx", "0em").attr("text-anchor", "middle").attr("font-family", "sans-serif").attr("font-size", "18px").attr("fill", "black").on("click", function(d) { + var this_chr; + this_chr = d; + return _this.redraw_plot(d); + }); + }; + + Manhattan_Plot.prototype.add_plot_points = function() { + var _this = this; + return this.plot_point = this.svg.selectAll("circle").data(this.plot_coordinates).enter().append("circle").attr("cx", function(d) { + return _this.x_scale(d[0]); + }).attr("cy", function(d) { + return _this.y_scale(d[1]); + }).attr("r", 2).attr("id", function(d) { + return "point_" + String(d[2]); + }).classed("circle", true).on("mouseover", function(d) { + var this_id; + console.log("d3.event is:", d3.event); + console.log("d is:", d); + this_id = "point_" + String(d[2]); + return d3.select("#" + this_id).classed("d3_highlight", true).attr("r", 5).attr("fill", "yellow").call(_this.show_marker_in_table(d)); + }).on("mouseout", function(d) { + var this_id; + this_id = "point_" + String(d[2]); + return d3.select("#" + this_id).classed("d3_highlight", false).attr("r", 2).attr("fill", "black"); + }); + }; + + Manhattan_Plot.prototype.redraw_plot = function(chr_ob) { + console.log("chr_name is:", chr_ob[0]); + console.log("chr_length is:", chr_ob[1]); + $('#manhattan_plot').remove(); + $('#manhattan_plot_container').append('<div id="manhattan_plot"></div>'); + return root.chr_plot = new Chr_Manhattan_Plot(600, 1200, chr_ob); + }; + + Manhattan_Plot.prototype.create_zoom_pane = function() { + var zoom; + zoom = d3.behavior.zoom().on("zoom", draw); + return this.svg.append("rect").attr("class", "pane").attr("width", this.plot_width).attr("height", this.plot_height).call(zoom); + }; + + Manhattan_Plot.prototype.draw = function() { + this.svg.select("g.x_axis").call(this.xAxis); + this.svg.select("g.y_axis").call(this.yAxis); + this.svg.select("path.area").attr("d", area); + return this.svg.select("path.line").attr("d", line); + }; - Manhattan_Plot.prototype.add_plot_points = function() { - var _this = this; - return this.svg.selectAll("circle").data(this.plot_coordinates).enter().append("circle").attr("cx", function(d) { - return parseFloat(_this.x_buffer) + ((parseFloat(_this.plot_width) - parseFloat(_this.x_buffer)) * d[0] / parseFloat(_this.x_max)); - }).attr("cy", function(d) { - return _this.plot_height - ((_this.plot_height - _this.y_buffer) * d[1] / _this.y_max); - }).attr("r", 2).attr("id", function(d) { - return "point_" + String(d[2]); - }).classed("circle", true).on("mouseover", function(d) { - var this_id; - console.log("d3.event is:", d3.event); - console.log("d is:", d); - this_id = "point_" + String(d[2]); - return d3.select("#" + this_id).classed("d3_highlight", true).attr("r", 5).attr("fill", "yellow").call(_this.show_marker_in_table(d)); - }).on("mouseout", function(d) { - var this_id; - this_id = "point_" + String(d[2]); - return d3.select("#" + this_id).classed("d3_highlight", false).attr("r", 2).attr("fill", "black").call(_this.show_marker_in_table()); - }); - }; + return Manhattan_Plot; - return Manhattan_Plot; + })(); - })(); - console.time('Create manhattan plot'); - new Manhattan_Plot(600, 1200); - return console.timeEnd('Create manhattan plot'); - }); + root.Manhattan_Plot = new Manhattan_Plot(600, 1200); }).call(this); diff --git a/wqflask/wqflask/static/new/javascript/show_trait.coffee b/wqflask/wqflask/static/new/javascript/show_trait.coffee index 1df033d6..84e465e8 100644 --- a/wqflask/wqflask/static/new/javascript/show_trait.coffee +++ b/wqflask/wqflask/static/new/javascript/show_trait.coffee @@ -64,8 +64,10 @@ $ -> sample_lists = js_data.sample_lists sample_group_types = js_data.sample_group_types - $("#update_bar_chart.btn-group").button() + #if $("#update_bar_chart").length + # $("#update_bar_chart.btn-group").button() root.bar_chart = new Bar_Chart(sample_lists[0]) + root.histogram = new Histogram(sample_lists[0]) new Box_Plot(sample_lists[0]) $('.bar_chart_samples_group').change -> @@ -73,13 +75,12 @@ $ -> $('#bar_chart_container').append('<div id="bar_chart"></div>') group = $(this).val() if group == "samples_primary" - new Bar_Chart(sample_lists[0]) + root.bar_chart = new Bar_Chart(sample_lists[0]) else if group == "samples_other" - new Bar_Chart(sample_lists[1]) + root.bar_chart = new Bar_Chart(sample_lists[1]) else if group == "samples_all" all_samples = sample_lists[0].concat sample_lists[1] - new Bar_Chart(all_samples) - #$(".btn-group").button() + root.bar_chart = new Bar_Chart(all_samples) $('.box_plot_samples_group').change -> $('#box_plot').remove() @@ -93,18 +94,18 @@ $ -> all_samples = sample_lists[0].concat sample_lists[1] new Box_Plot(all_samples) - + hide_tabs = (start) -> for x in [start..10] $("#stats_tabs" + x).hide() + # Changes stats table between all, bxd only and non-bxd, etc. stats_mdp_change = -> selected = $(this).val() hide_tabs(0) $("#stats_tabs" + selected).show() - #$(".stats_mdp").change(stats_mdp_change) change_stats_value = (sample_sets, category, value_type, decimal_places)-> id = "#" + process_id(category, value_type) @@ -124,18 +125,16 @@ $ -> console.log("*-* the_value:", the_value) console.log("*-* current_value:", current_value) if the_value != current_value + console.log("object:", $(id).html(the_value)) $(id).html(the_value).effect("highlight") # We go ahead and always change the title value if we have it if title_value $(id).attr('title', title_value) + update_stat_values = (sample_sets)-> for category in ['samples_primary', 'samples_other', 'samples_all'] - #change_stats_value(sample_sets, category, "n_of_samples", 0) - - #for stat in ["mean", "median", "std_dev", "std_error", "min", "max"] - #for stat in (row.vn for row in Stat_Table_Rows) for row in Stat_Table_Rows console.log("Calling change_stats_value") change_stats_value(sample_sets, category, row.vn, row.digits) diff --git a/wqflask/wqflask/static/new/javascript/show_trait.js b/wqflask/wqflask/static/new/javascript/show_trait.js index 90fa8228..d4e01e6d 100644 --- a/wqflask/wqflask/static/new/javascript/show_trait.js +++ b/wqflask/wqflask/static/new/javascript/show_trait.js @@ -61,8 +61,8 @@ var block_by_attribute_value, block_by_index, block_outliers, change_stats_value, create_value_dropdown, edit_data_change, export_sample_table_data, get_sample_table_data, hide_no_value, hide_tabs, make_table, on_corr_method_change, populate_sample_attributes_values_dropdown, process_id, reset_samples_table, sample_group_types, sample_lists, show_hide_outliers, stats_mdp_change, update_stat_values; sample_lists = js_data.sample_lists; sample_group_types = js_data.sample_group_types; - $("#update_bar_chart.btn-group").button(); root.bar_chart = new Bar_Chart(sample_lists[0]); + root.histogram = new Histogram(sample_lists[0]); new Box_Plot(sample_lists[0]); $('.bar_chart_samples_group').change(function() { var all_samples, group; @@ -70,12 +70,12 @@ $('#bar_chart_container').append('<div id="bar_chart"></div>'); group = $(this).val(); if (group === "samples_primary") { - return new Bar_Chart(sample_lists[0]); + return root.bar_chart = new Bar_Chart(sample_lists[0]); } else if (group === "samples_other") { - return new Bar_Chart(sample_lists[1]); + return root.bar_chart = new Bar_Chart(sample_lists[1]); } else if (group === "samples_all") { all_samples = sample_lists[0].concat(sample_lists[1]); - return new Bar_Chart(all_samples); + return root.bar_chart = new Bar_Chart(all_samples); } }); $('.box_plot_samples_group').change(function() { @@ -123,6 +123,7 @@ console.log("*-* the_value:", the_value); console.log("*-* current_value:", current_value); if (the_value !== current_value) { + console.log("object:", $(id).html(the_value)); $(id).html(the_value).effect("highlight"); } if (title_value) { diff --git a/wqflask/wqflask/static/new/packages/DataTables/js/dataTables.naturalSort.js b/wqflask/wqflask/static/new/packages/DataTables/js/dataTables.naturalSort.js new file mode 100644 index 00000000..c9e26682 --- /dev/null +++ b/wqflask/wqflask/static/new/packages/DataTables/js/dataTables.naturalSort.js @@ -0,0 +1,56 @@ +(function() { + +/* + * Natural Sort algorithm for Javascript - Version 0.7 - Released under MIT license + * Author: Jim Palmer (based on chunking idea from Dave Koelle) + * Contributors: Mike Grier (mgrier.com), Clint Priest, Kyle Adams, guillermo + * See: http://js-naturalsort.googlecode.com/svn/trunk/naturalSort.js + */ +function naturalSort (a, b) { + var re = /(^-?[0-9]+(\.?[0-9]*)[df]?e?[0-9]?$|^0x[0-9a-f]+$|[0-9]+)/gi, + sre = /(^[ ]*|[ ]*$)/g, + dre = /(^([\w ]+,?[\w ]+)?[\w ]+,?[\w ]+\d+:\d+(:\d+)?[\w ]?|^\d{1,4}[\/\-]\d{1,4}[\/\-]\d{1,4}|^\w+, \w+ \d+, \d{4})/, + hre = /^0x[0-9a-f]+$/i, + ore = /^0/, + // convert all to strings and trim() + x = a.toString().replace(sre, '') || '', + y = b.toString().replace(sre, '') || '', + // chunk/tokenize + xN = x.replace(re, '\0$1\0').replace(/\0$/,'').replace(/^\0/,'').split('\0'), + yN = y.replace(re, '\0$1\0').replace(/\0$/,'').replace(/^\0/,'').split('\0'), + // numeric, hex or date detection + xD = parseInt(x.match(hre)) || (xN.length != 1 && x.match(dre) && Date.parse(x)), + yD = parseInt(y.match(hre)) || xD && y.match(dre) && Date.parse(y) || null; + // first try and sort Hex codes or Dates + if (yD) + if ( xD < yD ) return -1; + else if ( xD > yD ) return 1; + // natural sorting through split numeric strings and default strings + for(var cLoc=0, numS=Math.max(xN.length, yN.length); cLoc < numS; cLoc++) { + // find floats not starting with '0', string or 0 if not defined (Clint Priest) + var oFxNcL = !(xN[cLoc] || '').match(ore) && parseFloat(xN[cLoc]) || xN[cLoc] || 0; + var oFyNcL = !(yN[cLoc] || '').match(ore) && parseFloat(yN[cLoc]) || yN[cLoc] || 0; + // handle numeric vs string comparison - number < string - (Kyle Adams) + if (isNaN(oFxNcL) !== isNaN(oFyNcL)) return (isNaN(oFxNcL)) ? 1 : -1; + // rely on string comparison if different types - i.e. '02' < 2 != '02' < '2' + else if (typeof oFxNcL !== typeof oFyNcL) { + oFxNcL += ''; + oFyNcL += ''; + } + if (oFxNcL < oFyNcL) return -1; + if (oFxNcL > oFyNcL) return 1; + } + return 0; +} + +jQuery.extend( jQuery.fn.dataTableExt.oSort, { + "natural-asc": function ( a, b ) { + return naturalSort(a,b); + }, + + "natural-desc": function ( a, b ) { + return naturalSort(a,b) * -1; + } +} ); + +}()); \ No newline at end of file diff --git a/wqflask/wqflask/templates/index_page.html b/wqflask/wqflask/templates/index_page.html index d177a7bd..a7d7b513 100644 --- a/wqflask/wqflask/templates/index_page.html +++ b/wqflask/wqflask/templates/index_page.html @@ -17,7 +17,7 @@ <div class="row"> <div class="span3 bs-docs-sidebar"> <ul class="nav nav-list bs-docs-sidenav"> - <li><a href="#quick-search"><i class="icon-chevron-right"></i> Quick Search</a></li> +<!-- <li><a href="#quick-search"><i class="icon-chevron-right"></i> Quick Search</a></li>--> <li><a href="#search"><i class="icon-chevron-right"></i> Search</a></li> <li><a href="#getting-started"><i class="icon-chevron-right"></i> Getting started</a></li> <li><a href="#advanced"><i class="icon-chevron-right"></i> Advanced commands</a></li> @@ -27,7 +27,7 @@ </div> <div class="span9"> - <section id="quick-search"> +<!-- <section id="quick-search"> <div class="page-header"> <h1>Quick search</h1> </div> @@ -52,7 +52,7 @@ </div> </fieldset> </form> - </section> + </section>--> <section id="search"> <div class="page-header"> <h1>Select and search</h1> diff --git a/wqflask/wqflask/templates/interval_mapping.html b/wqflask/wqflask/templates/interval_mapping.html index e4e08388..e4b93bf4 100644 --- a/wqflask/wqflask/templates/interval_mapping.html +++ b/wqflask/wqflask/templates/interval_mapping.html @@ -77,7 +77,6 @@ <script language="javascript" type="text/javascript" src="/static/packages/TableTools/media/js/TableTools.min.js"></script> <script language="javascript" type="text/javascript" src="/static/packages/underscore/underscore-min.js"></script> - <script type="text/javascript" charset="utf-8"> $(document).ready( function () { console.time("Creating table"); diff --git a/wqflask/wqflask/templates/marker_regression.html b/wqflask/wqflask/templates/marker_regression.html index 64d2e9b7..05fb9845 100644 --- a/wqflask/wqflask/templates/marker_regression.html +++ b/wqflask/wqflask/templates/marker_regression.html @@ -18,14 +18,17 @@ Manhattan Plot </h2> </div> - <div id="manhattan_plots" class="manhattan_plots"> - + <div id="manhattan_plot_container" class="manhattan_plot_container"> + <div id="manhattan_plot" class="manhattan_plots"> + + </div> </div> <div> <h2> Genome Association Results </h2> </div> + <table cellpadding="0" cellspacing="0" border="0" id="qtl_results" class="table table-hover table-striped table-bordered"> <thead> <tr> @@ -38,17 +41,18 @@ </thead> <tbody> {% for marker in qtl_results %} - <tr> - <td>{{loop.index}}</td> - <td>{{marker.lod_score}}</td> - <td>{{marker.chr}}</td> - <td>{{marker.Mb}}</td> - <td>{{marker.name}}</td> - </tr> + {% if marker.lod_score > lod_cutoff %} + <tr> + <td>{{loop.index}}</td> + <td>{{marker.lod_score}}</td> + <td>{{marker.chr}}</td> + <td>{{marker.Mb}}</td> + <td>{{marker.name}}</td> + </tr> + {% endif %} {% endfor %} </tbody> </table> - </div> <!-- End of body --> @@ -61,15 +65,16 @@ </script> <!--[if lt IE 9]> - <script language="javascript" type="text/javascript" src="/static/packages/jqplot/excanvas.js"></script> +<!-- <script language="javascript" type="text/javascript" src="/static/packages/jqplot/excanvas.js"></script>--> <![endif]--> <script language="javascript" type="text/javascript" src="http://d3js.org/d3.v3.min.js"></script> - <script language="javascript" type="text/javascript" src="/static/new/javascript/marker_regression.js"></script> <script language="javascript" type="text/javascript" src="/static/new/packages/DataTables/js/jquery.js"></script> <script language="javascript" type="text/javascript" src="/static/new/packages/DataTables/js/jquery.dataTables.min.js"></script> <script language="javascript" type="text/javascript" src="/static/packages/DT_bootstrap/DT_bootstrap.js"></script> <script language="javascript" type="text/javascript" src="/static/packages/TableTools/media/js/TableTools.min.js"></script> <script language="javascript" type="text/javascript" src="/static/packages/underscore/underscore-min.js"></script> + <script language="javascript" type="text/javascript" src="/static/new/javascript/marker_regression.js"></script> + <script language="javascript" type="text/javascript" src="/static/new/javascript/chr_manhattan_plot.js"></script> <script type="text/javascript" charset="utf-8"> diff --git a/wqflask/wqflask/templates/show_trait.html b/wqflask/wqflask/templates/show_trait.html index 86891bb0..e15d043b 100644 --- a/wqflask/wqflask/templates/show_trait.html +++ b/wqflask/wqflask/templates/show_trait.html @@ -58,9 +58,49 @@ <script type="text/javascript" src="/static/new/javascript/box.js"></script> <script type="text/javascript" src="/static/new/javascript/get_traits_from_collection.js"></script> <script type="text/javascript" src="/static/new/javascript/bar_chart.js"></script> + <script type="text/javascript" src="/static/new/javascript/histogram.js"></script> <script type="text/javascript" src="/static/new/javascript/box_plot.js"></script> <script type="text/javascript" src="/static/new/javascript/show_trait_mapping_tools.js"></script> <script type="text/javascript" src="/static/new/javascript/show_trait.js"></script> <script type="text/javascript" src="/static/new/javascript/validation.js"></script> + + <script language="javascript" type="text/javascript" src="/static/new/packages/DataTables/js/jquery.dataTables.min.js"></script> + <script language="javascript" type="text/javascript" src="/static/new/packages/DataTables/js/dataTables.naturalSort.js"></script> + <script language="javascript" type="text/javascript" src="/static/packages/DT_bootstrap/DT_bootstrap.js"></script> + <script language="javascript" type="text/javascript" src="/static/packages/TableTools/media/js/TableTools.min.js"></script> + + <script type="text/javascript" charset="utf-8"> + $(document).ready( function () { + console.time("Creating table"); + $('#samples_primary, #samples_other').dataTable( { + //"sDom": "<<'span3'l><'span3'T><'span4'f>'row-fluid'r>t<'row-fluid'<'span6'i><'span6'p>>", + "aoColumns": [ + { "sType": "natural" }, + null, + null, + { "bSortable": false }, + null + ], + "sDom": "ftr", + "oTableTools": { + "aButtons": [ + "copy", + "print", + { + "sExtends": "collection", + "sButtonText": 'Save <span class="caret" />', + "aButtons": [ "csv", "xls", "pdf" ] + } + ], + "sSwfPath": "/static/packages/TableTools/media/swf/copy_csv_xls_pdf.swf" + }, + "bPaginate": false, + "bLengthChange": true, + "bDeferRender": true, + "bSortClasses": false + } ); + console.timeEnd("Creating table"); + }); + </script> {% endblock %} diff --git a/wqflask/wqflask/templates/show_trait_edit_data.html b/wqflask/wqflask/templates/show_trait_edit_data.html index 84c606b9..e7df3b13 100644 --- a/wqflask/wqflask/templates/show_trait_edit_data.html +++ b/wqflask/wqflask/templates/show_trait_edit_data.html @@ -82,75 +82,73 @@ <div> <h3>{{ sample_type.header }}</h3> - <table class="table table-hover table-striped" {# Todo: Enable sorting on table #} + <table cellpadding="0" cellspacing="0" border="0" class="table table-hover table-striped table-bordered" id="samples_{{ sample_type.sample_group_type }}"> - <tr> - <th>Index</th> - - <th>Sample</th> - - <th>Value</th> - {% if sample_type.se_exists() %} - <th> </th> - - <th>SE</th> - {% endif %} - - {% for attribute in sample_type.attributes|sort() %} - <th> - {{ sample_type.attributes[attribute].name }} - </th> + <thead> + <tr> + <td>Index</td> + <td>Sample</td> + <td>Value</td> + {% if sample_type.se_exists() %} + <td> </td> + <td>SE</td> + {% endif %} + {% for attribute in sample_type.attributes|sort() %} + <td> + {{ sample_type.attributes[attribute].name }} + </td> + {% endfor %} + </tr> + </thead> + <tbody> + {% for sample in sample_type.sample_list %} + <tr class="{{ sample.class_outlier }} value_se" id="{{ sample.this_id }}"> + <td class="column_name-Index"> + {{ loop.index }} + <input type="checkbox" name="selectCheck" + class="checkbox edit_sample_checkbox" + value="{{ sample.name }}" checked="checked"> + </td> + + <td class="column_name-Sample"> + <span class="edit_sample_sample_name"> + {{ sample.name }} + </span> + </td> + + {# Todo: Add IDs #} + <td class="column_name-Value"> + <input type="text" data-value="{{ sample.display_value }}" name="{{ 'value:' + sample.name }}" + class="trait_value_input edit_sample_value" + value="{{ sample.display_value }}" + size=8 maxlength=8 + > + </td> + + {% if sample_type.se_exists() %} + <td> + ± + </td> + + {# Todo: Add IDs #} + <td class="column_name-SE"> + <input type="text" data-value="{{ sample.display_variance }}" name="{{ 'variance:' + sample.name}}" + class="trait_value_input edit_sample_se" + value="{{ sample.display_variance }}" + size=8 maxlength=8 + > + </td> + {% endif %} + + {# Loop through each attribute type and input value #} + {% for attribute in sample_type.attributes|sort() %} + <td class="std_cell column_name-{{ sample_type.attributes[attribute].name.replace(' ', '_') }}"> + {{ sample.extra_attributes[sample_type.attributes[attribute].name] }} + </td> + {% endfor %} + </tr> {% endfor %} - </tr> - - {% for sample in sample_type.sample_list %} - <tr class="{{ sample.class_outlier }} value_se" id="{{ sample.this_id }}"> - <td class="column_name-Index"> - {{ loop.index }} - <input type="checkbox" name="selectCheck" - class="checkbox edit_sample_checkbox" - value="{{ sample.name }}" checked="checked"> - </td> - - <td class="column_name-Sample"> - <span class="edit_sample_sample_name"> - {{ sample.name }} - </span> - </td> - - {# Todo: Add IDs #} - <td class="column_name-Value"> - <input type="text" data-value="{{ sample.display_value }}" name="{{ 'value:' + sample.name }}" - class="trait_value_input edit_sample_value" - value="{{ sample.display_value }}" - size=8 maxlength=8 - > - </td> - - {% if sample_type.se_exists() %} - <td> - ± - </td> - - {# Todo: Add IDs #} - <td class="column_name-SE"> - <input type="text" data-value="{{ sample.display_variance }}" name="{{ 'variance:' + sample.name}}" - class="trait_value_input edit_sample_se" - value="{{ sample.display_variance }}" - size=8 maxlength=8 - > - </td> - {% endif %} - - {# Loop through each attribute type and input value #} - {% for attribute in sample_type.attributes|sort() %} - <td class="std_cell column_name-{{ sample_type.attributes[attribute].name.replace(' ', '_') }}"> - {{ sample.extra_attributes[sample_type.attributes[attribute].name] }} - </td> - {% endfor %} - </tr> - {% endfor %} - + </tbody> </table> </div> {% endfor %} diff --git a/wqflask/wqflask/templates/show_trait_mapping_tools.html b/wqflask/wqflask/templates/show_trait_mapping_tools.html index 58ee8982..cfa49456 100644 --- a/wqflask/wqflask/templates/show_trait_mapping_tools.html +++ b/wqflask/wqflask/templates/show_trait_mapping_tools.html @@ -133,7 +133,7 @@ <div class="controls"> <input name="num_perm" value="2000" type="text" /> </div> - </div> --> + </div> --> <div class="control-group"> <div class="controls"> diff --git a/wqflask/wqflask/templates/show_trait_statistics_new.html b/wqflask/wqflask/templates/show_trait_statistics_new.html index 6d6b1d24..28f7e0c7 100644 --- a/wqflask/wqflask/templates/show_trait_statistics_new.html +++ b/wqflask/wqflask/templates/show_trait_statistics_new.html @@ -8,6 +8,9 @@ <a href="#bar_chart_tab" data-toggle="tab">Bar Chart</a> </li> <li> + <a href="#histogram_tab" data-toggle="tab">Histogram</a> + </li> + <li> <a href="#box_plot_tab" data-toggle="tab">Box Plot</a> </li> </ul> @@ -51,7 +54,20 @@ <div id="bar_chart"></div> </div> </div> - <div class="tab-pane active" id="box_plot_tab"> + <div class="tab-pane" id="histogram_tab"> + {% if sample_groups|length > 1 %} + <select class="histogram_samples_group"> + {% for group, pretty_group in sample_group_types.items() %} + <option value="{{ group }}">{{ pretty_group }}</option> + {% endfor %} + </select> + <br><br> + {% endif %} + <div id="histogram_container"> + <div id="histogram"></div> + </div> + </div> + <div class="tab-pane" id="box_plot_tab"> {% if sample_groups|length > 1 %} <select class="box_plot_samples_group"> {% for group, pretty_group in sample_group_types.items() %} diff --git a/wqflask/wqflask/views.py b/wqflask/wqflask/views.py index 828199c5..89820145 100644 --- a/wqflask/wqflask/views.py +++ b/wqflask/wqflask/views.py @@ -243,7 +243,12 @@ def marker_regression_page(): print(" ---**--- {}: {}".format(type(template_vars.__dict__[item]), item)) #causeerror - Redis.set(key, pickle.dumps(result, pickle.HIGHEST_PROTOCOL)) + + #qtl_length = len(result['js_data']['qtl_results']) + #print("qtl_length:", qtl_length) + pickled_result = pickle.dumps(result, pickle.HIGHEST_PROTOCOL) + print("pickled result length:", len(pickled_result)) + Redis.set(key, pickled_result) Redis.expire(key, 60*60) with Bench("Rendering template"): |